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  • ?SPARC T4?????????????·???? : Netra SPARC T4-1

    - by user13138700
    ?SPARC T4???????????????·??????? Netra SPARC T4-1 ???? Netra SPARC T4-2 ?2012?1?10??????????3?15??????????????(????) ?????????? Netra SPARC T4-1 ? 4core ???( T4 ???????? 4core ???)(*)???????????????????????????(*)( Netra SPARC T4-1 ?????? 4core ???? 8core ????????) ??? prtdiag ????? pginfo ??????????????? 8????/1core ???? prtdiag ????????4core=32???????????????pginfo ?????????????????core ???????????????????? # ./prtdiag -v System Configuration: Oracle Corporation sun4v Netra SPARC T4-1 ???????: 130560 M ??? ================================ ?? CPU ================================ CPU ID Frequency Implementation Status ------ --------- ---------------------- ------- 0 2848 MHz SPARC-T4 on-line 1 2848 MHz SPARC-T4 on-line 2 2848 MHz SPARC-T4 on-line 3 2848 MHz SPARC-T4 on-line 4 2848 MHz SPARC-T4 on-line 5 2848 MHz SPARC-T4 on-line 6 2848 MHz SPARC-T4 on-line 7 2848 MHz SPARC-T4 on-line 8 2848 MHz SPARC-T4 on-line 9 2848 MHz SPARC-T4 on-line 10 2848 MHz SPARC-T4 on-line 11 2848 MHz SPARC-T4 on-line 12 2848 MHz SPARC-T4 on-line 13 2848 MHz SPARC-T4 on-line 14 2848 MHz SPARC-T4 on-line 15 2848 MHz SPARC-T4 on-line 16 2848 MHz SPARC-T4 on-line 17 2848 MHz SPARC-T4 on-line 18 2848 MHz SPARC-T4 on-line 19 2848 MHz SPARC-T4 on-line 20 2848 MHz SPARC-T4 on-line 21 2848 MHz SPARC-T4 on-line 22 2848 MHz SPARC-T4 on-line 23 2848 MHz SPARC-T4 on-line 24 2848 MHz SPARC-T4 on-line 25 2848 MHz SPARC-T4 on-line 26 2848 MHz SPARC-T4 on-line 27 2848 MHz SPARC-T4 on-line 28 2848 MHz SPARC-T4 on-line 29 2848 MHz SPARC-T4 on-line 30 2848 MHz SPARC-T4 on-line 31 2848 MHz SPARC-T4 on-line ======================= Physical Memory Configuration ======================== ???? # pginfo -p -T 0 (System [system,chip]) CPUs: 0-31 `-- 3 (Data_Pipe_to_memory [system,chip]) CPUs: 0-31 |-- 2 (Floating_Point_Unit [core]) CPUs: 0-7 | `-- 1 (Integer_Pipeline [core]) CPUs: 0-7 |-- 5 (Floating_Point_Unit [core]) CPUs: 8-15 | `-- 4 (Integer_Pipeline [core]) CPUs: 8-15 |-- 7 (Floating_Point_Unit [core]) CPUs: 16-23 | `-- 6 (Integer_Pipeline [core]) CPUs: 16-23 `-- 9 (Floating_Point_Unit [core]) CPUs: 24-31 `-- 8 (Integer_Pipeline [core]) CPUs: 24-31 T4 ????????????????????????????????????????????????? T3 ?????(S2 core)?????T4 ?????(S3 core)?????????????5???????????? T3 ?????(S2 core)?????????????????????????(????????)?????????????????????????????????????????????·???????????????????????????????????????? ????T4 ????????????????????????????T4 ??????????·??????? Netra SPARC T4-1 4core ????????????????????????????????????T3 ???????????????????????????? ?????????Netra SPARC T4-1 ??????????????? Netra SPARC T4-1 ?? Computing 1 x SPARC T4 4?? 32???? or 8 ?? 64 ???? 2.85GHz CPU (1?????8????) 16 x DDR3 DIMM (?? 256GB ?????16GB DIMM ???) I/O and Storage 3 x Low Profile PCI-Express Gen2 ???? (2 x 10Gb Ethernet XAUI ???????) 2 x Full-height Half-length PCI-Express Gen2 ???? 4 x 10/100/1000 Ethernet ???????? 4 x 2.5” SAS2 HDD 4 x USB ??? (?? 2, ?? 2) RAS and Management and Power Supply ???? (RAID????), ????PSU ?????????? ILOM?????????????? 2N (1+1) , AC ???? DC ?? Support OS Oracle Solaris 10 10/9, 9/10, 8/11, Oracle Solaris 11 11/11 Oracle VM Server for SPARC 2.1 (LDoms) ???? ??? NEBS Level3?? ??????21” 19”(EIA-310D),23”,24”,600mm????? ?????(?????)????????? ????SPARC T4 ????????SPARC T4 ?????????????????????????(4???)???????????? Oracle OpenWorld Tokyo 2012 ?3??(4/4(?)?4/5(?)?4/6(?))?????????????????????&?????????????????SPARC T4 ?????????????????????????????????·?????????????????SPARC T4 ???????????????????!? Oracle OpenWorld Tokyo 2012 http://www.oracle.com/openworld/jp-ja/index.html ????·???????????? 4/6(?) Develop D3-13 (14:00 - 14:45) ???????????49 ??? ?????? 7264 ???????????????

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  • SPARC T4 ??????: SPARC T4 ??????????!!

    - by user13138700
    ?? 2011 ? 9 ?? SPARC T4 CPU ???????? SPARC T4 ????????????????2011??10?????????????????????????? ????????????????????SPARC T4 ?????????????????????????????????????????????????????????? SPARC T4 CPU ???? SPARC T4 ?????????????????????????????????? ??????????????????????4/4, 4/5, 4/6 ? 3???????? Oracle Open World 2012 ???????? Oracle Open World 2012 Tokyo ?? Oracle ?????&????? ??? Oracle Solaris ????????????·????????? SPARC&Solaris ??????????????SPARC&Solaris ????????????????????????????????????????????????????????????????????????? Oracle OpenWorld Tokyo 2012 ???? URL http://www.oracle.com/openworld/jp-ja/index.html ?????? 7264 ??????????????? ????Oracle Open World 2012 Tokyo ?????????????????????????SPARC T4 ????? ????????????????? SPARC T4 ????????? SPARC T3 ????????(S2??)??????????????????????????(S3??)??????????????????? ???????" T " ???????????????(?)?????? SPARC T1/T2/T3 ???????????????????????????(????????)????????????????????????? ?SPARC T4 ????????????????????????????? ?SPARC T4 ???????DB?????????????????????????????? ???????????????? ????????????????????????????????????????????? ???? SPARC T3 ???????????????????????????2???????????? ????????????????????????????????????????????????????? ?????????????? SPARC T4 ????????????????????????????????????SPARC T4 ????????? SPARC T4 ??????????????????????????????????????????? ?????????????? T4 ??????????????????? SPARC ???????????????????????????????????????????????????????????????????&??????????? ?????????????????????????????????????????????????????????Web?????????????DB?????????????????????????????????????? (????????????) ???????????? SPARC T4 ????????????????????????????? < T4 ???????? > ??? SPARC ??(S3??)??? x5??????????????????? x2????????????????????? Crypto (?????)?????????? ?????????????????????????/???????????????? ?????? 1, 2,& 4 ??????????? < T4 ????? ??????? > 8x SPARC S3 ?? (64????/???) 4MB ?? L3 ????? (8???/16???) 8x9 ????? 4x DDR3 ??????????? @6.4Gbps 6x ?????????? @9.6Gbps 2x8 PCIe 2.0 (5GTS) 2x10Gb XAUI ??????? < S3???????????? > ALU : Arithmetic Logic Unit BRU : Branch Logic Unit FGU : Flouting-point Graphics Unit IRF : Integer Register File FRF : Flouting-point Register File WRF : Working Register File MMU : Memory Management Unit LSU : Load Store Unit Crypto(SPU) : Streaming Processing Unit TRU : Trap Logic Unit < S3????????? > ????? 8????/?? ?????? Out-of-Order ?? 16???????????????? ????????????? ???????????? ??????? ????????? 64???? ITLB ? 128???? DTLB 64KB 4??? L1 ?????????????? 128KB 8??? ???? L2 ????? < T4 ???????? vs T3 ???????? > T4 ????????????? Out-Of-Order ???? Pick ???????? In-Order ?? Pick ?????? Commit ??????? Out-Of-Order ?? Commit ?????? In-Order ?? < T4 ?????????? > ???????????vs????????????????????????????? ????????Active??????????????????? ???????????????????????? ??????????????????? < T4vsT1/T2/T3 ??????? > SPARC T4 ???? T3????????Web??????????? DB?????????????????????????????? ????????????????????SPARC T4 ?????&Solaris ?????????????(????????)??????????????????????????????????????????????????????????!!? ????Oracle Open World 2012 Tokyo ????????????????SPARC T4 ?????????????????????? 4/4, 4/5, 4/6 ?3????????????????????????????????????????????????????????????????????????????????????? ????????????????? URL http://www.oracle.com/openworld/jp-ja/exhibit/index.html

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  • T4 Template error - Assembly Directive cannot locate referenced assembly in Visual Studio 2010 proje

    - by CodeSniper
    I ran into the following error recently in Visual Studio 2010 while trying to port Phil Haack’s excellent T4CSS template which was originally built for Visual Studio 2008.   The Problem Error Compiling transformation: Metadata file 'dotless.Core' could not be found In “T4 speak”, this simply means that you have an Assembly directive in your T4 template but the T4 engine was not able to locate or load the referenced assembly. In the case of the T4CSS Template, this was a showstopper for making it work in Visual Studio 2010. On a side note: The T4CSS template is a sweet little wrapper to allow you to use DotLessCss to generate static .css files from .less files rather than using their default HttpHandler or command-line tool.    If you haven't tried DotLessCSS yet, go check it out now!  In short, it is a tool that allows you to templatize and program your CSS files so that you can use variables, expressions, and mixins within your CSS which enables rapid changes and a lot of developer-flexibility as you evolve your CSS and UI. Back to our regularly scheduled program… Anyhow, this post isn't about DotLessCss, its about the T4 Templates and the errors I ran into when converting them from Visual Studio 2008 to Visual Studio 2010. In VS2010, there were quite a few changes to the T4 Template Engine; most were excellent changes, but this one bit me with T4CSS: “Project assemblies are no longer used to resolve template assembly directives.” In VS2008, if you wanted to reference a custom assembly in your T4 Template (.tt file) you would simply right click on your project, choose Add Reference and select that assembly.  Afterwards you were allowed to use the following syntax in your T4 template to tell it to look at the local references: <#@ assembly name="dotless.Core.dll" #> This told the engine to look in the “usual place” for the assembly, which is your project references. However, this is exactly what they changed in VS2010.  They now basically sandbox the T4 Engine to keep your T4 assemblies separate from your project assemblies.  This can come in handy if you want to support different versions of an assembly referenced both by your T4 templates and your project. Who broke the build?  Oh, Microsoft Did! In our case, this change causes a problem since the templates are no longer compatible when upgrading to VS 2010 – thus its a breaking change.  So, how do we make this work in VS 2010? Luckily, Microsoft now offers several options for referencing assemblies from T4 Templates: GAC your assemblies and use Namespace Reference or Fully Qualified Type Name Use a hard-coded Fully Qualified UNC path Copy assembly to Visual Studio "Public Assemblies Folder" and use Namespace Reference or Fully Qualified Type Name.  Use or Define a Windows Environment Variable to build a Fully Qualified UNC path. Use a Visual Studio Macro to build a Fully Qualified UNC path. Option #1 & 2 were already supported in Visual Studio 2008, so if you want to keep your templates compatible with both Visual Studio versions, then you would have to adopt one of these approaches. Yakkety Yak, use the GAC! Option #1 requires an additional pre-build step to GAC the referenced assembly, which could be a pain.  But, if you go that route, then after you GAC, all you need is a simple type name or namespace reference such as: <#@ assembly name="dotless.Core" #> Hard Coding aint that hard! The other option of using hard-coded paths in Option #2 is pretty impractical in most situations since each developer would have to use the same local project folder paths, or modify this setting each time for their local machines as well as for production deployment.  However, if you want to go that route, simply use the following assembly directive style: <#@ assembly name="C:\Code\Lib\dotless.Core.dll" #> Lets go Public! Option #3, the Visual Studio Public Assemblies Folder, is the recommended place to put commonly used tools and libraries that are only needed for Visual Studio.  Think of it like a VS-only GAC.  This is likely the best place for something like dotLessCSS and is my preferred solution.  However, you will need to either use an installer or a pre-build action to copy the assembly to the right folder location.   Normally this is located at:  C:\Program Files (x86)\Microsoft Visual Studio 10.0\Common7\IDE\PublicAssemblies Once you have copied your assembly there, you use the type name or namespace syntax again: <#@ assembly name="dotless.Core" #> Save the Environment! Option #4, using a Windows Environment Variable, is interesting for enterprise use where you may have standard locations for files, but less useful for demo-code, frameworks, and products where you don't have control over the local system.  The syntax for including a environment variable in your assembly directive looks like the following, just as you would expect: <#@ assembly name="%mypath%\dotless.Core.dll" #> “mypath” is a Windows environment variable you setup that points to some fully qualified UNC path on your system.  In the right situation this can be a great solution such as one where you use a msi installer for deployment, or where you have a pre-existing environment variable you can re-use. OMG Macros! Finally, Option #5 is a very nice option if you want to keep your T4 template’s assembly reference local and relative to the project or solution without muddying-up your dev environment or GAC with extra deployments.  An example looks like this: <#@ assembly name="$(SolutionDir)lib\dotless.Core.dll" #> In this example, I’m using the “SolutionDir” VS macro so I can reference an assembly in a “/lib” folder at the root of the solution.   This is just one of the many macros you can use.  If you are familiar with creating Pre/Post-build Event scripts, you can use its dialog to look at all of the different VS macros available. This option gives the best solution for local assemblies without the hassle of extra installers or other setup before the build.   However, its still not compatible with Visual Studio 2008, so if you have a T4 Template you want to use with both, then you may have to create multiple .tt files, one for each IDE version, or require the developer to set a value in the .tt file manually.   I’m not sure if T4 Templates support any form of compiler switches like “#if (VS2010)”  statements, but it would definitely be nice in this case to switch between this option and one of the ones more compatible with VS 2008. Conclusion As you can see, we went from 3 options with Visual Studio 2008, to 5 options (plus one problem) with Visual Studio 2010.  As a whole, I think the changes are great, but the short-term growing pains during the migration may be annoying until we get used to our new found power. Hopefully this all made sense and was helpful to you.  If nothing else, I’ll just use it as a reference the next time I need to port a T4 template to Visual Studio 2010.  Happy T4 templating, and “May the fourth be with you!”

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  • How to tell if SPARC T4 crypto is being used?

    - by danx
    A question that often comes up when running applications on SPARC T4 systems is "How can I tell if hardware crypto accleration is being used?" To review, the SPARC T4 processor includes a crypto unit that supports several crypto instructions. For hardware crypto these include 11 AES instructions, 4 xmul* instructions (for AES GCM carryless multiply), mont for Montgomery multiply (optimizes RSA and DSA), and 5 des_* instructions (for DES3). For hardware hash algorithm optimization, the T4 has the md5, sha1, sha256, and sha512 instructions (the last two are used for SHA-224 an SHA-384). First off, it's easy to tell if the processor T4 crypto instructions—use the isainfo -v command and look for "sparcv9" and "aes" (and other hash and crypto algorithms) in the output: $ isainfo -v 64-bit sparcv9 applications crc32c cbcond pause mont mpmul sha512 sha256 sha1 md5 camellia kasumi des aes ima hpc vis3 fmaf asi_blk_init vis2 vis popc These instructions are not-privileged, so are available for direct use in user-level applications and libraries (such as OpenSSL). Here is the "openssl speed -evp" command shown with the built-in t4 engine and with the pkcs11 engine. Both run the T4 AES instructions, but the t4 engine is faster than the pkcs11 engine because it has less overhead (especially for smaller packet sizes): t-4 $ /usr/bin/openssl version OpenSSL 1.0.0j 10 May 2012 t-4 $ /usr/bin/openssl engine (t4) SPARC T4 engine support (dynamic) Dynamic engine loading support (pkcs11) PKCS #11 engine support t-4 $ /usr/bin/openssl speed -evp aes-128-cbc # t4 engine used by default . . . The 'numbers' are in 1000s of bytes per second processed. type 16 bytes 64 bytes 256 bytes 1024 bytes 8192 bytes aes-128-cbc 487777.10k 816822.21k 986012.59k 1017029.97k 1053543.08k t-4 $ /usr/bin/openssl speed -engine pkcs11 -evp aes-128-cbc engine "pkcs11" set. . . . The 'numbers' are in 1000s of bytes per second processed. type 16 bytes 64 bytes 256 bytes 1024 bytes 8192 bytes aes-128-cbc 31703.58k 116636.39k 350672.81k 696170.50k 993599.49k Note: The "-evp" flag indicates use the OpenSSL "EnVeloPe" API, which gives more accurate results. That's because it tells OpenSSL to use the same API that external programs use when calling OpenSSL libcrypto functions, evp(3openssl). DTrace Shows if T4 Crypto Functions Are Used OK, good enough, the isainfo(1) command shows the instructions are present, but how does one know if they are being used? Chi-Chang Lin, who works on Oracle Solaris performance, wrote a Dtrace script to show if T4 instructions are being executed. To show the T4 instructions are being used, run the following Dtrace script. Look for functions named "t4" and "yf" in the output. The OpenSSL T4 engine uses functions named "t4" and the PKCS#11 engine uses functions named "yf". To demonstrate, I'll first run "openssl speed" with the built-in t4 engine then with the pkcs11 engine. The performance numbers are not valid due to dtrace probes slowing things down. t-4 # dtrace -Z -n ' pid$target::*yf*:entry,pid$target::*t4_*:entry{ @[probemod, probefunc] = count();}' \ -c "/usr/bin/openssl speed -evp aes-128-cbc" dtrace: description 'pid$target::*yf*:entry' matched 101 probes . . . dtrace: pid 2029 has exited libcrypto.so.1.0.0 ENGINE_load_t4 1 libcrypto.so.1.0.0 t4_DH 1 libcrypto.so.1.0.0 t4_DSA 1 libcrypto.so.1.0.0 t4_RSA 1 libcrypto.so.1.0.0 t4_destroy 1 libcrypto.so.1.0.0 t4_free_aes_ctr_NIDs 1 libcrypto.so.1.0.0 t4_init 1 libcrypto.so.1.0.0 t4_add_NID 3 libcrypto.so.1.0.0 t4_aes_expand128 5 libcrypto.so.1.0.0 t4_cipher_init_aes 5 libcrypto.so.1.0.0 t4_get_all_ciphers 6 libcrypto.so.1.0.0 t4_get_all_digests 59 libcrypto.so.1.0.0 t4_digest_final_sha1 65 libcrypto.so.1.0.0 t4_digest_init_sha1 65 libcrypto.so.1.0.0 t4_sha1_multiblock 126 libcrypto.so.1.0.0 t4_digest_update_sha1 261 libcrypto.so.1.0.0 t4_aes128_cbc_encrypt 1432979 libcrypto.so.1.0.0 t4_aes128_load_keys_for_encrypt 1432979 libcrypto.so.1.0.0 t4_cipher_do_aes_128_cbc 1432979 t-4 # dtrace -Z -n 'pid$target::*yf*:entry{ @[probemod, probefunc] = count();}   pid$target::*yf*:entry,pid$target::*t4_*:entry{ @[probemod, probefunc] = count();}' \ -c "/usr/bin/openssl speed -engine pkcs11 -evp aes-128-cbc" dtrace: description 'pid$target::*yf*:entry' matched 101 probes engine "pkcs11" set. . . . dtrace: pid 2033 has exited libcrypto.so.1.0.0 ENGINE_load_t4 1 libcrypto.so.1.0.0 t4_DH 1 libcrypto.so.1.0.0 t4_DSA 1 libcrypto.so.1.0.0 t4_RSA 1 libcrypto.so.1.0.0 t4_destroy 1 libcrypto.so.1.0.0 t4_free_aes_ctr_NIDs 1 libcrypto.so.1.0.0 t4_get_all_ciphers 1 libcrypto.so.1.0.0 t4_get_all_digests 1 libsoftcrypto.so.1 rijndael_key_setup_enc_yf 1 libsoftcrypto.so.1 yf_aes_expand128 1 libcrypto.so.1.0.0 t4_add_NID 3 libsoftcrypto.so.1 yf_aes128_cbc_encrypt 1542330 libsoftcrypto.so.1 yf_aes128_load_keys_for_encrypt 1542330 So, as shown above the OpenSSL built-in t4 engine executes t4_* functions (which are hand-coded assembly executing the T4 AES instructions) and the OpenSSL pkcs11 engine executes *yf* functions. Programmatic Use of OpenSSL T4 engine The OpenSSL t4 engine is used automatically with the /usr/bin/openssl command line. Chi-Chang Lin also points out that if you're calling the OpenSSL API (libcrypto.so) from a program, you must call ENGINE_load_built_engines(), otherwise the built-in t4 engine will not be loaded. You do not call ENGINE_set_default(). That's because "openssl speed -evp" test calls ENGINE_load_built_engines() even though the "-engine" option wasn't specified. OpenSSL T4 engine Availability The OpenSSL t4 engine is available with Solaris 11 and 11.1. For Solaris 10 08/11 (U10), you need to use the OpenSSL pkcs311 engine. The OpenSSL t4 engine is distributed only with the version of OpenSSL distributed with Solaris (and not third-party or self-compiled versions of OpenSSL). The OpenSSL engine implements the AES cipher for Solaris 11, released 11/2011. For Solaris 11.1, released 11/2012, the OpenSSL engine adds optimization for the MD5, SHA-1, and SHA-2 hash algorithms, and DES-3. Although the T4 processor has Camillia and Kasumi block cipher instructions, these are not implemented in the OpenSSL T4 engine. The following charts may help view availability of optimizations. The first chart shows what's available with Solaris CLIs and APIs, the second chart shows what's available in Solaris OpenSSL. Native Solaris Optimization for SPARC T4 This table is shows Solaris native CLI and API support. As such, they are all available with the OpenSSL pkcs11 engine. CLIs: "openssl -engine pkcs11", encrypt(1), decrypt(1), mac(1), digest(1), MD5sum(1), SHA1sum(1), SHA224sum(1), SHA256sum(1), SHA384sum(1), SHA512sum(1) APIs: PKCS#11 library libpkcs11(3LIB) (incluDES Openssl pkcs11 engine), libMD(3LIB), and Solaris kernel modules AlgorithmSolaris 1008/11 (U10)Solaris 11Solaris 11.1 AES-ECB, AES-CBC, AES-CTR, AES-CBC AES-CFB128 XXX DES3-ECB, DES3-CBC, DES2-ECB, DES2-CBC, DES-ECB, DES-CBC XXX bignum Montgomery multiply (RSA, DSA) XXX MD5, SHA-1, SHA-256, SHA-384, SHA-512 XXX SHA-224 X ARCFOUR (RC4) X Solaris OpenSSL T4 Engine Optimization This table is for the Solaris OpenSSL built-in t4 engine. Algorithms listed above are also available through the OpenSSL pkcs11 engine. CLI: openssl(1openssl) APIs: openssl(5), engine(3openssl), evp(3openssl), libcrypto crypto(3openssl) AlgorithmSolaris 11Solaris 11SRU2Solaris 11.1 AES-ECB, AES-CBC, AES-CTR, AES-CBC AES-CFB128 XXX DES3-ECB, DES3-CBC, DES-ECB, DES-CBC X bignum Montgomery multiply (RSA, DSA) X MD5, SHA-1, SHA-256, SHA-384, SHA-512 XX SHA-224 X Source Code Availability Solaris Most of the T4 assembly code that called the new T4 crypto instructions was written by Ferenc Rákóczi of the Solaris Security group, with assistance from others. You can download the Solaris source for this and other parts of Solaris as a few zip files at the Oracle Download website. The relevant source files are generally under directories usr/src/common/crypto/{aes,arcfour,des,md5,modes,sha1,sha2}}/sun4v/. and usr/src/common/bignum/sun4v/. Solaris 11 binary is available from the Oracle Solaris 11 download website. OpenSSL t4 engine The source for the OpenSSL t4 engine, which is based on the Solaris source above, is viewable through the OpenGrok source code browser in directory src/components/openssl/openssl-1.0.0/engines/t4 . You can download the source from the same website or through Mercurial source code management, hg(1). Conclusion Oracle Solaris with SPARC T4 provides a rich set of accelerated cryptographic and hash algorithms. Using the latest update, Solaris 11.1, provides the best set of optimized algorithms, but alternatives are often available, sometimes slightly slower, for releases back to Solaris 10 08/11 (U10). Reference See also these earlier blogs. SPARC T4 OpenSSL Engine by myself, Dan Anderson (2011), discusses the Openssl T4 engine and reviews the SPARC T4 processor for the Solaris 11 release. Exciting Crypto Advances with the T4 processor and Oracle Solaris 11 by Valerie Fenwick (2011) discusses crypto algorithms that were optimized for the T4 processor with the Solaris 11 FCS (11/11) and Solaris 10 08/11 (U10) release. T4 Crypto Cheat Sheet by Stefan Hinker (2012) discusses how to make T4 crypto optimization available to various consumers (such as SSH, Java, OpenSSL, Apache, etc.) High Performance Security For Oracle Database and Fusion Middleware Applications using SPARC T4 (PDF, 2012) discusses SPARC T4 and its usage to optimize application security. Configuring Oracle iPlanet WebServer / Oracle Traffic Director to use crypto accelerators on T4-1 servers by Meena Vyas (2012)

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  • SPARC T4-4 Beats 8-CPU IBM POWER7 on TPC-H @3000GB Benchmark

    - by Brian
    Oracle's SPARC T4-4 server delivered a world record TPC-H @3000GB benchmark result for systems with four processors. This result beats eight processor results from IBM (POWER7) and HP (x86). The SPARC T4-4 server also delivered better performance per core than these eight processor systems from IBM and HP. Comparisons below are based upon system to system comparisons, highlighting Oracle's complete software and hardware solution. This database world record result used Oracle's Sun Storage 2540-M2 arrays (rotating disk) connected to a SPARC T4-4 server running Oracle Solaris 11 and Oracle Database 11g Release 2 demonstrating the power of Oracle's integrated hardware and software solution. The SPARC T4-4 server based configuration achieved a TPC-H scale factor 3000 world record for four processor systems of 205,792 QphH@3000GB with price/performance of $4.10/QphH@3000GB. The SPARC T4-4 server with four SPARC T4 processors (total of 32 cores) is 7% faster than the IBM Power 780 server with eight POWER7 processors (total of 32 cores) on the TPC-H @3000GB benchmark. The SPARC T4-4 server is 36% better in price performance compared to the IBM Power 780 server on the TPC-H @3000GB Benchmark. The SPARC T4-4 server is 29% faster than the IBM Power 780 for data loading. The SPARC T4-4 server is up to 3.4 times faster than the IBM Power 780 server for the Refresh Function. The SPARC T4-4 server with four SPARC T4 processors is 27% faster than the HP ProLiant DL980 G7 server with eight x86 processors on the TPC-H @3000GB benchmark. The SPARC T4-4 server is 52% faster than the HP ProLiant DL980 G7 server for data loading. The SPARC T4-4 server is up to 3.2 times faster than the HP ProLiant DL980 G7 for the Refresh Function. The SPARC T4-4 server achieved a peak IO rate from the Oracle database of 17 GB/sec. This rate was independent of the storage used, as demonstrated by the TPC-H @3000TB benchmark which used twelve Sun Storage 2540-M2 arrays (rotating disk) and the TPC-H @1000TB benchmark which used four Sun Storage F5100 Flash Array devices (flash storage). [*] The SPARC T4-4 server showed linear scaling from TPC-H @1000GB to TPC-H @3000GB. This demonstrates that the SPARC T4-4 server can handle the increasingly larger databases required of DSS systems. [*] The SPARC T4-4 server benchmark results demonstrate a complete solution of building Decision Support Systems including data loading, business questions and refreshing data. Each phase usually has a time constraint and the SPARC T4-4 server shows superior performance during each phase. [*] The TPC believes that comparisons of results published with different scale factors are misleading and discourages such comparisons. Performance Landscape The table lists the leading TPC-H @3000GB results for non-clustered systems. TPC-H @3000GB, Non-Clustered Systems System Processor P/C/T – Memory Composite(QphH) $/perf($/QphH) Power(QppH) Throughput(QthH) Database Available SPARC Enterprise M9000 3.0 GHz SPARC64 VII+ 64/256/256 – 1024 GB 386,478.3 $18.19 316,835.8 471,428.6 Oracle 11g R2 09/22/11 SPARC T4-4 3.0 GHz SPARC T4 4/32/256 – 1024 GB 205,792.0 $4.10 190,325.1 222,515.9 Oracle 11g R2 05/31/12 SPARC Enterprise M9000 2.88 GHz SPARC64 VII 32/128/256 – 512 GB 198,907.5 $15.27 182,350.7 216,967.7 Oracle 11g R2 12/09/10 IBM Power 780 4.1 GHz POWER7 8/32/128 – 1024 GB 192,001.1 $6.37 210,368.4 175,237.4 Sybase 15.4 11/30/11 HP ProLiant DL980 G7 2.27 GHz Intel Xeon X7560 8/64/128 – 512 GB 162,601.7 $2.68 185,297.7 142,685.6 SQL Server 2008 10/13/10 P/C/T = Processors, Cores, Threads QphH = the Composite Metric (bigger is better) $/QphH = the Price/Performance metric in USD (smaller is better) QppH = the Power Numerical Quantity QthH = the Throughput Numerical Quantity The following table lists data load times and refresh function times during the power run. TPC-H @3000GB, Non-Clustered Systems Database Load & Database Refresh System Processor Data Loading(h:m:s) T4Advan RF1(sec) T4Advan RF2(sec) T4Advan SPARC T4-4 3.0 GHz SPARC T4 04:08:29 1.0x 67.1 1.0x 39.5 1.0x IBM Power 780 4.1 GHz POWER7 05:51:50 1.5x 147.3 2.2x 133.2 3.4x HP ProLiant DL980 G7 2.27 GHz Intel Xeon X7560 08:35:17 2.1x 173.0 2.6x 126.3 3.2x Data Loading = database load time RF1 = power test first refresh transaction RF2 = power test second refresh transaction T4 Advan = the ratio of time to T4 time Complete benchmark results found at the TPC benchmark website http://www.tpc.org. Configuration Summary and Results Hardware Configuration: SPARC T4-4 server 4 x SPARC T4 3.0 GHz processors (total of 32 cores, 128 threads) 1024 GB memory 8 x internal SAS (8 x 300 GB) disk drives External Storage: 12 x Sun Storage 2540-M2 array storage, each with 12 x 15K RPM 300 GB drives, 2 controllers, 2 GB cache Software Configuration: Oracle Solaris 11 11/11 Oracle Database 11g Release 2 Enterprise Edition Audited Results: Database Size: 3000 GB (Scale Factor 3000) TPC-H Composite: 205,792.0 QphH@3000GB Price/performance: $4.10/QphH@3000GB Available: 05/31/2012 Total 3 year Cost: $843,656 TPC-H Power: 190,325.1 TPC-H Throughput: 222,515.9 Database Load Time: 4:08:29 Benchmark Description The TPC-H benchmark is a performance benchmark established by the Transaction Processing Council (TPC) to demonstrate Data Warehousing/Decision Support Systems (DSS). TPC-H measurements are produced for customers to evaluate the performance of various DSS systems. These queries and updates are executed against a standard database under controlled conditions. Performance projections and comparisons between different TPC-H Database sizes (100GB, 300GB, 1000GB, 3000GB, 10000GB, 30000GB and 100000GB) are not allowed by the TPC. TPC-H is a data warehousing-oriented, non-industry-specific benchmark that consists of a large number of complex queries typical of decision support applications. It also includes some insert and delete activity that is intended to simulate loading and purging data from a warehouse. TPC-H measures the combined performance of a particular database manager on a specific computer system. The main performance metric reported by TPC-H is called the TPC-H Composite Query-per-Hour Performance Metric (QphH@SF, where SF is the number of GB of raw data, referred to as the scale factor). QphH@SF is intended to summarize the ability of the system to process queries in both single and multiple user modes. The benchmark requires reporting of price/performance, which is the ratio of the total HW/SW cost plus 3 years maintenance to the QphH. A secondary metric is the storage efficiency, which is the ratio of total configured disk space in GB to the scale factor. Key Points and Best Practices Twelve Sun Storage 2540-M2 arrays were used for the benchmark. Each Sun Storage 2540-M2 array contains 12 15K RPM drives and is connected to a single dual port 8Gb FC HBA using 2 ports. Each Sun Storage 2540-M2 array showed 1.5 GB/sec for sequential read operations and showed linear scaling, achieving 18 GB/sec with twelve Sun Storage 2540-M2 arrays. These were stand alone IO tests. The peak IO rate measured from the Oracle database was 17 GB/sec. Oracle Solaris 11 11/11 required very little system tuning. Some vendors try to make the point that storage ratios are of customer concern. However, storage ratio size has more to do with disk layout and the increasing capacities of disks – so this is not an important metric in which to compare systems. The SPARC T4-4 server and Oracle Solaris efficiently managed the system load of over one thousand Oracle Database parallel processes. Six Sun Storage 2540-M2 arrays were mirrored to another six Sun Storage 2540-M2 arrays on which all of the Oracle database files were placed. IO performance was high and balanced across all the arrays. The TPC-H Refresh Function (RF) simulates periodical refresh portion of Data Warehouse by adding new sales and deleting old sales data. Parallel DML (parallel insert and delete in this case) and database log performance are a key for this function and the SPARC T4-4 server outperformed both the IBM POWER7 server and HP ProLiant DL980 G7 server. (See the RF columns above.) See Also Transaction Processing Performance Council (TPC) Home Page Ideas International Benchmark Page SPARC T4-4 Server oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Sun Storage 2540-M2 Array oracle.com OTN Disclosure Statement TPC-H, QphH, $/QphH are trademarks of Transaction Processing Performance Council (TPC). For more information, see www.tpc.org. SPARC T4-4 205,792.0 QphH@3000GB, $4.10/QphH@3000GB, available 5/31/12, 4 processors, 32 cores, 256 threads; IBM Power 780 QphH@3000GB, 192,001.1 QphH@3000GB, $6.37/QphH@3000GB, available 11/30/11, 8 processors, 32 cores, 128 threads; HP ProLiant DL980 G7 162,601.7 QphH@3000GB, $2.68/QphH@3000GB available 10/13/10, 8 processors, 64 cores, 128 threads.

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  • World Record Oracle E-Business Consolidated Workload on SPARC T4-2

    - by Brian
    Oracle set a World Record for the Oracle E-Business Suite Standard Medium multiple-online module benchmark using Oracle's SPARC T4-2 and SPARC T4-4 servers which ran the application and database. Oracle's SPARC T4 servers demonstrate performance leadership and world-record results on Oracle E-Business Suite Applications R12 OLTP benchmark by publishing the first result using multiple concurrent online application modules with Oracle Database 11g Release 2 running Solaris.   This results shows that a multi-tier configuration of SPARC T4 servers running the Oracle E-Business Suite R12.1.2 application and Oracle Database 11g Release 2 is capable of supporting 4,100 online users with outstanding response-times, executing a mix of complex transactions consolidating 4 Oracle E-Business modules (iProcurement, Order Management, Customer Service and HR Self-Service).   The SPARC T4-2 server in the application tier utilized about 65% and the SPARC T4-4 server in the database tier utilized about 30%, providing significant headroom for additional Oracle E-Business Suite R12.1.2 processing modules, more online users, and future growth.   Oracle E-Business Suite Applications were run in Oracle Solaris Containers on SPARC T4 servers and provides a consolidation platform for multiple E-Business instances.   Performance Landscape Multiple Online Modules (Self-Service, Order-Management, iProcurement, Customer-Service) Medium Configuration System Users AverageResponse Time 90th PercentileResponse Time SPARC T4-2 4,100 2.08 sec 2.52 sec Configuration Summary Application Tier Configuration: 1 x SPARC T4-2 server 2 x SPARC T4 processors, 2.85 GHz 256 GB memory 3 x 300 GB internal disks Oracle Solaris 10 Oracle E-Business Suite 12.1.2 Database Tier Configuration: 1 x SPARC T4-4 server 4 x SPARC T4 processors, 3.0 GHz 256 GB memory 2 x 300 GB internal disks Oracle Solaris 10 Oracle Solaris Containers Oracle Database 11g Release 2 Storage Configuration: 1 x Sun Storage F5100 Flash Array (80 x 24 GB flash modules) Benchmark Description The Oracle R12 E-Business Suite Standard Benchmark combines online transaction execution by simulated users with multiple online concurrent modules to model a typical scenario for a global enterprise. The online component exercises the common UI flows which are most frequently used by a majority of our customers. This benchmark utilized four concurrent flows of OLTP transactions, for Order to Cash, iProcurement, Customer Service and HR Self-Service and measured the response times. The selected flows model simultaneous business activities inclusive of managing customers, services, products and employees. See Also Oracle R12 E-Business Suite Standard Benchmark Results Oracle R12 E-Business Suite Standard Benchmark Overview Oracle R12 E-Business Benchmark Description E-Business Suite Applications R2 (R12.1.2) Online Benchmark - Using Oracle Database 11g on Oracle's SPARC T4-2 and Oracle's SPARC T4-4 Servers oracle.com SPARC T4-2 Server oracle.com OTN SPARC T4-4 Server oracle.com OTN Oracle E-Business Suite oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Disclosure Statement Oracle E-Business Suite R12 medium multiple-online module benchmark, SPARC T4-2, SPARC T4, 2.85 GHz, 2 chips, 16 cores, 128 threads, 256 GB memory, SPARC T4-4, SPARC T4, 3.0 GHz, 4 chips, 32 cores, 256 threads, 256 GB memory, average response time 2.08 sec, 90th percentile response time 2.52 sec, Oracle Solaris 10, Oracle Solaris Containers, Oracle E-Business Suite 12.1.2, Oracle Database 11g Release 2, Results as of 9/30/2012.

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  • Improved Performance on PeopleSoft Combined Benchmark using SPARC T4-4

    - by Brian
    Oracle's SPARC T4-4 server running Oracle's PeopleSoft HCM 9.1 combined online and batch benchmark achieved a world record 18,000 concurrent users experiencing subsecond response time while executing a PeopleSoft Payroll batch job of 500,000 employees in 32.4 minutes. This result was obtained with a SPARC T4-4 server running Oracle Database 11g Release 2, a SPARC T4-4 server running PeopleSoft HCM 9.1 application server and a SPARC T4-2 server running Oracle WebLogic Server in the web tier. The SPARC T4-4 server running the application tier used Oracle Solaris Zones which provide a flexible, scalable and manageable virtualization environment. The average CPU utilization on the SPARC T4-2 server in the web tier was 17%, on the SPARC T4-4 server in the application tier it was 59%, and on the SPARC T4-4 server in the database tier was 47% (online and batch) leaving significant headroom for additional processing across the three tiers. The SPARC T4-4 server used for the database tier hosted Oracle Database 11g Release 2 using Oracle Automatic Storage Management (ASM) for database files management with I/O performance equivalent to raw devices. Performance Landscape Results are presented for the PeopleSoft HRMS Self-Service and Payroll combined benchmark. The new result with 128 streams shows significant improvement in the payroll batch processing time with little impact on the self-service component response time. PeopleSoft HRMS Self-Service and Payroll Benchmark Systems Users Ave Response Search (sec) Ave Response Save (sec) Batch Time (min) Streams SPARC T4-2 (web) SPARC T4-4 (app) SPARC T4-4 (db) 18,000 0.988 0.539 32.4 128 SPARC T4-2 (web) SPARC T4-4 (app) SPARC T4-4 (db) 18,000 0.944 0.503 43.3 64 The following results are for the PeopleSoft HRMS Self-Service benchmark that was previous run. The results are not directly comparable with the combined results because they do not include the payroll component. PeopleSoft HRMS Self-Service 9.1 Benchmark Systems Users Ave Response Search (sec) Ave Response Save (sec) Batch Time (min) Streams SPARC T4-2 (web) SPARC T4-4 (app) 2x SPARC T4-2 (db) 18,000 1.048 0.742 N/A N/A The following results are for the PeopleSoft Payroll benchmark that was previous run. The results are not directly comparable with the combined results because they do not include the self-service component. PeopleSoft Payroll (N.A.) 9.1 - 500K Employees (7 Million SQL PayCalc, Unicode) Systems Users Ave Response Search (sec) Ave Response Save (sec) Batch Time (min) Streams SPARC T4-4 (db) N/A N/A N/A 30.84 96 Configuration Summary Application Configuration: 1 x SPARC T4-4 server with 4 x SPARC T4 processors, 3.0 GHz 512 GB memory Oracle Solaris 11 11/11 PeopleTools 8.52 PeopleSoft HCM 9.1 Oracle Tuxedo, Version 10.3.0.0, 64-bit, Patch Level 031 Java Platform, Standard Edition Development Kit 6 Update 32 Database Configuration: 1 x SPARC T4-4 server with 4 x SPARC T4 processors, 3.0 GHz 256 GB memory Oracle Solaris 11 11/11 Oracle Database 11g Release 2 PeopleTools 8.52 Oracle Tuxedo, Version 10.3.0.0, 64-bit, Patch Level 031 Micro Focus Server Express (COBOL v 5.1.00) Web Tier Configuration: 1 x SPARC T4-2 server with 2 x SPARC T4 processors, 2.85 GHz 256 GB memory Oracle Solaris 11 11/11 PeopleTools 8.52 Oracle WebLogic Server 10.3.4 Java Platform, Standard Edition Development Kit 6 Update 32 Storage Configuration: 1 x Sun Server X2-4 as a COMSTAR head for data 4 x Intel Xeon X7550, 2.0 GHz 128 GB memory 1 x Sun Storage F5100 Flash Array (80 flash modules) 1 x Sun Storage F5100 Flash Array (40 flash modules) 1 x Sun Fire X4275 as a COMSTAR head for redo logs 12 x 2 TB SAS disks with Niwot Raid controller Benchmark Description This benchmark combines PeopleSoft HCM 9.1 HR Self Service online and PeopleSoft Payroll batch workloads to run on a unified database deployed on Oracle Database 11g Release 2. The PeopleSoft HRSS benchmark kit is a Oracle standard benchmark kit run by all platform vendors to measure the performance. It's an OLTP benchmark where DB SQLs are moderately complex. The results are certified by Oracle and a white paper is published. PeopleSoft HR SS defines a business transaction as a series of HTML pages that guide a user through a particular scenario. Users are defined as corporate Employees, Managers and HR administrators. The benchmark consist of 14 scenarios which emulate users performing typical HCM transactions such as viewing paycheck, promoting and hiring employees, updating employee profile and other typical HCM application transactions. All these transactions are well-defined in the PeopleSoft HR Self-Service 9.1 benchmark kit. This benchmark metric is the weighted average response search/save time for all the transactions. The PeopleSoft 9.1 Payroll (North America) benchmark demonstrates system performance for a range of processing volumes in a specific configuration. This workload represents large batch runs typical of a ERP environment during a mass update. The benchmark measures five application business process run times for a database representing large organization. They are Paysheet Creation, Payroll Calculation, Payroll Confirmation, Print Advice forms, and Create Direct Deposit File. The benchmark metric is the cumulative elapsed time taken to complete the Paysheet Creation, Payroll Calculation and Payroll Confirmation business application processes. The benchmark metrics are taken for each respective benchmark while running simultaneously on the same database back-end. Specifically, the payroll batch processes are started when the online workload reaches steady state (the maximum number of online users) and overlap with online transactions for the duration of the steady state. Key Points and Best Practices Two PeopleSoft Domain sets with 200 application servers each on a SPARC T4-4 server were hosted in 2 separate Oracle Solaris Zones to demonstrate consolidation of multiple application servers, ease of administration and performance tuning. Each Oracle Solaris Zone was bound to a separate processor set, each containing 15 cores (total 120 threads). The default set (1 core from first and third processor socket, total 16 threads) was used for network and disk interrupt handling. This was done to improve performance by reducing memory access latency by using the physical memory closest to the processors and offload I/O interrupt handling to default set threads, freeing up cpu resources for Application Servers threads and balancing application workload across 240 threads. A total of 128 PeopleSoft streams server processes where used on the database node to complete payroll batch job of 500,000 employees in 32.4 minutes. See Also Oracle PeopleSoft Benchmark White Papers oracle.com SPARC T4-2 Server oracle.com OTN SPARC T4-4 Server oracle.com OTN PeopleSoft Enterprise Human Capital Managementoracle.com OTN PeopleSoft Enterprise Human Capital Management (Payroll) oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 oracle.com OTN Disclosure Statement Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 8 November 2012.

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  • I have written an SQL query but I want to optimize it [closed]

    - by ankit gupta
    is there any way to do this using minimum no of joins and select? 2 tables are involved in this operation transaction_pci_details and transaction SELECT t6.transaction_pci_details_id, t6.terminal_id, t6.transaction_no, t6.transaction_id, t6.transaction_type, t6.reversal_flag, t6.transmission_date_time, t6.retrivel_ref_no, t6.card_no,t6.card_type, t6.expires_on, t6.transaction_amount, t6.currency_code, t6.response_code, t6.action_code, t6.message_reason_code, t6.merchant_id, t6.auth_code, t6.actual_trans_amnt, t6.bal_card_amnt, t5.sales_person_id FROM TRANSACTION AS t5 INNER JOIN ( SELECT t4.transaction_pci_details_id, t4.terminal_id, t4.transaction_no, t4.transaction_id, t4.transaction_type, t4.reversal_flag, t4.transmission_date_time, t4.retrivel_ref_no, t4.card_no, t4.card_type, t4.expires_on, t4.transaction_amount, t4.currency_code, t4.response_code, t4.action_code, t3.message_reason_code, t4.merchant_id, t4.auth_code, t4.actual_trans_amnt, t4.bal_card_amnt FROM ( SELECT* FROM transaction_pci_details WHERE message_reason_code LIKE '%OUT%'|| message_reason_code LIKE '%FAILED%' /*we can add date here*/ UNION ALL SELECT t2.transaction_pci_details_id, t2.terminal_id, t2.transaction_no, t2.transaction_id, t2.transaction_type, t2.reversal_flag, t2.transmission_date_time, t2.retrivel_ref_no, t2.card_no, t2.card_type, t2.expires_on, t2.transaction_amount, t2.currency_code, t2.response_code, t2.action_code, t2.message_reason_code, t2.merchant_id, t2.auth_code, t2.actual_trans_amnt, t2.bal_card_amnt FROM ( SELECT transaction_id FROM TRANSACTION WHERE transaction_type_id = 8 ) AS t1 INNER JOIN ( SELECT * FROM transaction_pci_details WHERE message_reason_code LIKE '%appro%' /*we can add date here*/ ) AS t2 ON t1.transaction_id = t2.transaction_id ) AS t3 INNER JOIN ( SELECT* FROM transaction_pci_details WHERE action_code LIKE '%REQ%' /*we can add date here*/ ) AS t4 ON t3.transaction_pci_details_id - t4.transaction_pci_details_id = 1 ) AS t6 ON t5.transaction_id = t6.transaction_id

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  • World Record Siebel PSPP Benchmark on SPARC T4 Servers

    - by Brian
    Oracle's SPARC T4 servers set a new World Record for Oracle's Siebel Platform Sizing and Performance Program (PSPP) benchmark suite. The result used Oracle's Siebel Customer Relationship Management (CRM) Industry Applications Release 8.1.1.4 and Oracle Database 11g Release 2 running Oracle Solaris on three SPARC T4-2 and two SPARC T4-1 servers. The SPARC T4 servers running the Siebel PSPP 8.1.1.4 workload which includes Siebel Call Center and Order Management System demonstrates impressive throughput performance of the SPARC T4 processor by achieving 29,000 users. This is the first Siebel PSPP 8.1.1.4 benchmark supporting 29,000 concurrent users with a rate of 239,748 Business Transactions/hour. The benchmark demonstrates vertical and horizontal scalability of Siebel CRM Release 8.1.1.4 on SPARC T4 servers. Performance Landscape Systems Txn/hr Users Call Center Order Management Response Times (sec) 1 x SPARC T4-1 (1 x SPARC T4 2.85 GHz) – Web 3 x SPARC T4-2 (2 x SPARC T4 2.85 GHz) – App/Gateway 1 x SPARC T4-1 (1 x SPARC T4 2.85 GHz) – DB 239,748 29,000 0.165 0.925 Oracle: Call Center + Order Management Transactions: 197,128 + 42,620 Users: 20300 + 8700 Configuration Summary Web Server Configuration: 1 x SPARC T4-1 server 1 x SPARC T4 processor, 2.85 GHz 128 GB memory Oracle Solaris 10 8/11 iPlanet Web Server 7 Application Server Configuration: 3 x SPARC T4-2 servers, each with 2 x SPARC T4 processor, 2.85 GHz 256 GB memory 3 x 300 GB SAS internal disks Oracle Solaris 10 8/11 Siebel CRM 8.1.1.5 SIA Database Server Configuration: 1 x SPARC T4-1 server 1 x SPARC T4 processor, 2.85 GHz 128 GB memory Oracle Solaris 11 11/11 Oracle Database 11g Release 2 (11.2.0.2) Storage Configuration: 1 x Sun Storage F5100 Flash Array 80 x 24 GB flash modules Benchmark Description Siebel 8.1 PSPP benchmark includes Call Center and Order Management: Siebel Financial Services Call Center – Provides the most complete solution for sales and service, allowing customer service and telesales representatives to provide superior customer support, improve customer loyalty, and increase revenues through cross-selling and up-selling. High-level description of the use cases tested: Incoming Call Creates Opportunity, Quote and Order and Incoming Call Creates Service Request . Three complex business transactions are executed simultaneously for specific number of concurrent users. The ratios of these 3 scenarios were 30%, 40%, 30% respectively, which together were totaling 70% of all transactions simulated in this benchmark. Between each user operation and the next one, the think time averaged approximately 10, 13, and 35 seconds respectively. Siebel Order Management – Oracle's Siebel Order Management allows employees such as salespeople and call center agents to create and manage quotes and orders through their entire life cycle. Siebel Order Management can be tightly integrated with back-office applications allowing users to perform tasks such as checking credit, confirming availability, and monitoring the fulfillment process. High-level description of the use cases tested: Order & Order Items Creation and Order Updates. Two complex Order Management transactions were executed simultaneously for specific number of concurrent users concurrently with aforementioned three Call Center scenarios above. The ratio of these 2 scenarios was 50% each, which together were totaling 30% of all transactions simulated in this benchmark. Between each user operation and the next one, the think time averaged approximately 20 and 67 seconds respectively. Key Points and Best Practices No processor cores or cache were activated or deactivated on the SPARC T-Series systems to achieve special benchmark effects. See Also Siebel White Papers SPARC T4-1 Server oracle.com OTN SPARC T4-2 Server oracle.com OTN Siebel CRM oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Disclosure Statement Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 30 September 2012.

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  • Interesting articles and blogs on SPARC T4

    - by mv
    Interesting articles and blogs on SPARC T4 processor   I have consolidated all the interesting information I could get on SPARC T4 processor and its hardware cryptographic capabilities.  Hope its useful. 1. Advantages of SPARC T4 processor  Most important points in this T4 announcement are : "The SPARC T4 processor was designed from the ground up for high speed security and has a cryptographic stream processing unit (SPU) integrated directly into each processor core. These accelerators support 16 industry standard security ciphers and enable high speed encryption at rates 3 to 5 times that of competing processors. By integrating encryption capabilities directly inside the instruction pipeline, the SPARC T4 processor eliminates the performance and cost barriers typically associated with secure computing and makes it possible to deliver high security levels without impacting the user experience." Data Sheet has more details on these  : "New on-chip Encryption Instruction Accelerators with direct non-privileged support for 16 industry-standard cryptographic algorithms plus random number generation in each of the eight cores: AES, Camellia, CRC32c, DES, 3DES, DH, DSA, ECC, Kasumi, MD5, RSA, SHA-1, SHA-224, SHA-256, SHA-384, SHA-512" I ran "isainfo -v" command on Solaris 11 Sparc T4-1 system. It shows the new instructions as expected  : $ isainfo -v 64-bit sparcv9 applications crc32c cbcond pause mont mpmul sha512 sha256 sha1 md5 camellia kasumi des aes ima hpc vis3 fmaf asi_blk_init vis2 vis popc 32-bit sparc applications crc32c cbcond pause mont mpmul sha512 sha256 sha1 md5 camellia kasumi des aes ima hpc vis3 fmaf asi_blk_init vis2 vis popc v8plus div32 mul32  2.  Dan Anderson's Blog have some interesting points about how these can be used : "New T4 crypto instructions include: aes_kexpand0, aes_kexpand1, aes_kexpand2,         aes_eround01, aes_eround23, aes_eround01_l, aes_eround_23_l, aes_dround01, aes_dround23, aes_dround01_l, aes_dround_23_l.       Having SPARC T4 hardware crypto instructions is all well and good, but how do we access it ?      The software is available with Solaris 11 and is used automatically if you are running Solaris a SPARC T4.  It is used internally in the kernel through kernel crypto modules.  It is available in user space through the PKCS#11 library." 3.   Dans' Blog on Where's the Crypto Libraries? Although this was written in 2009 but still is very useful  "Here's a brief tour of the major crypto libraries shown in the digraph:   The libpkcs11 library contains the PKCS#11 API (C_\*() functions, such as C_Initialize()). That in turn calls library pkcs11_softtoken or pkcs11_kernel, for userland or kernel crypto providers. The latter is used mostly for hardware-assisted cryptography (such as n2cp for Niagara2 SPARC processors), as that is performed more efficiently in kernel space with the "kCF" module (Kernel Crypto Framework). Additionally, for Solaris 10, strong crypto algorithms were split off in separate libraries, pkcs11_softtoken_extra libcryptoutil contains low-level utility functions to help implement cryptography. libsoftcrypto (OpenSolaris and Solaris Nevada only) implements several symmetric-key crypto algorithms in software, such as AES, RC4, and DES3, and the bignum library (used for RSA). libmd implements MD5, SHA, and SHA2 message digest algorithms" 4. Difference in T3 and T4 Diagram in this blog is good and self explanatory. Jeff's blog also highlights the differences  "The T4 servers have improved crypto acceleration, described at https://blogs.oracle.com/DanX/entry/sparc_t4_openssl_engine. It is "just built in" so administrators no longer have to assign crypto accelerator units to domains - it "just happens". Every physical or virtual CPU on a SPARC-T4 has full access to hardware based crypto acceleration at all times. .... For completeness sake, it's worth noting that the T4 adds more crypto algorithms, and accelerates Camelia, CRC32c, and more SHA-x." 5. About performance counters In this blog, performance counters are explained : "Note that unlike T3 and before, T4 crypto doesn't require kernel modules like ncp or n2cp, there is no visibility of crypto hardware with kstats or cryptoadm. T4 does provide hardware counters for crypto operations.  You can see these using cpustat: cpustat -c pic0=Instr_FGU_crypto 5 You can check the general crypto support of the hardware and OS with the command "isainfo -v". Since T4 crypto's implementation now allows direct userland access, there are no "crypto units" visible to cryptoadm.  " For more details refer Martin's blog as well. 6. How to turn off  SPARC T4 or Intel AES-NI crypto acceleration  I found this interesting blog from Darren about how to turn off  SPARC T4 or Intel AES-NI crypto acceleration. "One of the new Solaris 11 features of the linker/loader is the ability to have a single ELF object that has multiple different implementations of the same functions that are selected at runtime based on the capabilities of the machine.   The alternate to this is having the application coded to call getisax(2) system call and make the choice itself.  We use this functionality of the linker/loader when we build the userland libraries for the Solaris Cryptographic Framework (specifically libmd.so and libsoftcrypto.so) The Solaris linker/loader allows control of a lot of its functionality via environment variables, we can use that to control the version of the cryptographic functions we run.  To do this we simply export the LD_HWCAP environment variable with values that tell ld.so.1 to not select the HWCAP section matching certain features even if isainfo says they are present.  This will work for consumers of the Solaris Cryptographic Framework that use the Solaris PKCS#11 libraries or use libmd.so interfaces directly.  For SPARC T4 : export LD_HWCAP="-aes -des -md5 -sha256 -sha512 -mont -mpul" .. For Intel systems with AES-NI support: export LD_HWCAP="-aes"" Note that LD_HWCAP is explained in  http://docs.oracle.com/cd/E23823_01/html/816-5165/ld.so.1-1.html "LD_HWCAP, LD_HWCAP_32, and LD_HWCAP_64 -  Identifies an alternative hardware capabilities value... A “-” prefix results in the capabilities that follow being removed from the alternative capabilities." 7. Whitepaper on SPARC T4 Servers—Optimized for End-to-End Data Center Computing This Whitepaper on SPARC T4 Servers—Optimized for End-to-End Data Center Computing explains more details.  It has DTrace scripts which may come in handy : "To ensure the hardware-assisted cryptographic acceleration is configured to use and working with the security scenarios, it is recommended to use the following Solaris DTrace script. #!/usr/sbin/dtrace -s pid$1:libsoftcrypto:yf*:entry, pid$target:libsoftcrypto:rsa*:entry, pid$1:libmd:yf*:entry { @[probefunc] = count(); } tick-1sec { printa(@ops); trunc(@ops); }" Note that I have slightly modified the D Script to have RSA "libsoftcrypto:rsa*:entry" as well as per recommendations from Chi-Chang Lin. 8. References http://www.oracle.com/us/corporate/features/sparc-t4-announcement-494846.html http://www.oracle.com/us/products/servers-storage/servers/sparc-enterprise/t-series/sparc-t4-1-ds-487858.pdf https://blogs.oracle.com/DanX/entry/sparc_t4_openssl_engine https://blogs.oracle.com/DanX/entry/where_s_the_crypto_libraries https://blogs.oracle.com/darren/entry/howto_turn_off_sparc_t4 http://docs.oracle.com/cd/E23823_01/html/816-5165/ld.so.1-1.html   https://blogs.oracle.com/hardware/entry/unleash_the_power_of_cryptography https://blogs.oracle.com/cmt/entry/t4_crypto_cheat_sheet https://blogs.oracle.com/martinm/entry/t4_performance_counters_explained  https://blogs.oracle.com/jsavit/entry/no_mau_required_on_a http://www.oracle.com/us/products/servers-storage/servers/sparc-enterprise/t-series/sparc-t4-business-wp-524472.pdf

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  • SPARC T4-4 Delivers World Record First Result on PeopleSoft Combined Benchmark

    - by Brian
    Oracle's SPARC T4-4 servers running Oracle's PeopleSoft HCM 9.1 combined online and batch benchmark achieved World Record 18,000 concurrent users while executing a PeopleSoft Payroll batch job of 500,000 employees in 43.32 minutes and maintaining online users response time at < 2 seconds. This world record is the first to run online and batch workloads concurrently. This result was obtained with a SPARC T4-4 server running Oracle Database 11g Release 2, a SPARC T4-4 server running PeopleSoft HCM 9.1 application server and a SPARC T4-2 server running Oracle WebLogic Server in the web tier. The SPARC T4-4 server running the application tier used Oracle Solaris Zones which provide a flexible, scalable and manageable virtualization environment. The average CPU utilization on the SPARC T4-2 server in the web tier was 17%, on the SPARC T4-4 server in the application tier it was 59%, and on the SPARC T4-4 server in the database tier was 35% (online and batch) leaving significant headroom for additional processing across the three tiers. The SPARC T4-4 server used for the database tier hosted Oracle Database 11g Release 2 using Oracle Automatic Storage Management (ASM) for database files management with I/O performance equivalent to raw devices. This is the first three tier mixed workload (online and batch) PeopleSoft benchmark also processing PeopleSoft payroll batch workload. Performance Landscape PeopleSoft HR Self-Service and Payroll Benchmark Systems Users Ave Response Search (sec) Ave Response Save (sec) Batch Time (min) Streams SPARC T4-2 (web) SPARC T4-4 (app) SPARC T4-2 (db) 18,000 0.944 0.503 43.32 64 Configuration Summary Application Configuration: 1 x SPARC T4-4 server with 4 x SPARC T4 processors, 3.0 GHz 512 GB memory 5 x 300 GB SAS internal disks 1 x 100 GB and 2 x 300 GB internal SSDs 2 x 10 Gbe HBA Oracle Solaris 11 11/11 PeopleTools 8.52 PeopleSoft HCM 9.1 Oracle Tuxedo, Version 10.3.0.0, 64-bit, Patch Level 031 Java Platform, Standard Edition Development Kit 6 Update 32 Database Configuration: 1 x SPARC T4-4 server with 4 x SPARC T4 processors, 3.0 GHz 256 GB memory 3 x 300 GB SAS internal disks Oracle Solaris 11 11/11 Oracle Database 11g Release 2 Web Tier Configuration: 1 x SPARC T4-2 server with 2 x SPARC T4 processors, 2.85 GHz 256 GB memory 2 x 300 GB SAS internal disks 1 x 100 GB internal SSD Oracle Solaris 11 11/11 PeopleTools 8.52 Oracle WebLogic Server 10.3.4 Java Platform, Standard Edition Development Kit 6 Update 32 Storage Configuration: 1 x Sun Server X2-4 as a COMSTAR head for data 4 x Intel Xeon X7550, 2.0 GHz 128 GB memory 1 x Sun Storage F5100 Flash Array (80 flash modules) 1 x Sun Storage F5100 Flash Array (40 flash modules) 1 x Sun Fire X4275 as a COMSTAR head for redo logs 12 x 2 TB SAS disks with Niwot Raid controller Benchmark Description This benchmark combines PeopleSoft HCM 9.1 HR Self Service online and PeopleSoft Payroll batch workloads to run on a unified database deployed on Oracle Database 11g Release 2. The PeopleSoft HRSS benchmark kit is a Oracle standard benchmark kit run by all platform vendors to measure the performance. It's an OLTP benchmark where DB SQLs are moderately complex. The results are certified by Oracle and a white paper is published. PeopleSoft HR SS defines a business transaction as a series of HTML pages that guide a user through a particular scenario. Users are defined as corporate Employees, Managers and HR administrators. The benchmark consist of 14 scenarios which emulate users performing typical HCM transactions such as viewing paycheck, promoting and hiring employees, updating employee profile and other typical HCM application transactions. All these transactions are well-defined in the PeopleSoft HR Self-Service 9.1 benchmark kit. This benchmark metric is the weighted average response search/save time for all the transactions. The PeopleSoft 9.1 Payroll (North America) benchmark demonstrates system performance for a range of processing volumes in a specific configuration. This workload represents large batch runs typical of a ERP environment during a mass update. The benchmark measures five application business process run times for a database representing large organization. They are Paysheet Creation, Payroll Calculation, Payroll Confirmation, Print Advice forms, and Create Direct Deposit File. The benchmark metric is the cumulative elapsed time taken to complete the Paysheet Creation, Payroll Calculation and Payroll Confirmation business application processes. The benchmark metrics are taken for each respective benchmark while running simultaneously on the same database back-end. Specifically, the payroll batch processes are started when the online workload reaches steady state (the maximum number of online users) and overlap with online transactions for the duration of the steady state. Key Points and Best Practices Two Oracle PeopleSoft Domain sets with 200 application servers each on a SPARC T4-4 server were hosted in 2 separate Oracle Solaris Zones to demonstrate consolidation of multiple application servers, ease of administration and performance tuning. Each Oracle Solaris Zone was bound to a separate processor set, each containing 15 cores (total 120 threads). The default set (1 core from first and third processor socket, total 16 threads) was used for network and disk interrupt handling. This was done to improve performance by reducing memory access latency by using the physical memory closest to the processors and offload I/O interrupt handling to default set threads, freeing up cpu resources for Application Servers threads and balancing application workload across 240 threads. See Also Oracle PeopleSoft Benchmark White Papers oracle.com SPARC T4-2 Server oracle.com OTN SPARC T4-4 Server oracle.com OTN PeopleSoft Enterprise Human Capital Management oracle.com OTN PeopleSoft Enterprise Human Capital Management (Payroll) oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Disclosure Statement Oracle's PeopleSoft HR and Payroll combined benchmark, www.oracle.com/us/solutions/benchmark/apps-benchmark/peoplesoft-167486.html, results 09/30/2012.

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  • Real Excel Templates I

    - by Tim Dexter
    As promised, I'm starting to document the new Excel templates that I teased you all with a few weeks back. Leslie is buried in 11g documentation and will not get to officially documenting the templates for a while. I'll do my best to be professional and not ramble on about this and that, although the weather here has finally turned and its 'scorchio' here in Colorado today. Maybe our stand of Aspen will finally come into leaf ... but I digress. Preamble These templates are not actually that new, I helped in a small way to develop them a few years back with Excel 'meistress' Shirley for a company that was trying to use the Report Manager(RR) Excel FSG outputs under EBS 12. The functionality they needed was just not there in the RR FSG templates, the templates are actually XSL that is created from the the RR Excel template builder and fed to BIP for processing. Think of Excel from our RTF templates and you'll be there ie not really Excel but HTML masquerading as Excel. Although still under controlled release in EBS they have now made their way to the standlone release and are willing to share their Excel goodness. You get everything you have with hte Excel Analyzer Excel templates plus so much more. Therein lies a question, what will happen to the Analyzer templates? My understanding is that both will come together into a single Excel template format some time in the post-11g release world. The new XLSX format for Exce 2007/10 is also in the mix too so watch this space. What more do these templates offer? Well, you can structure data in the Excel output. Similar to RTF templates you can create sheets of data that have master-detail n relationships. Although the analyzer templates can do this, you have to get into macros whereas BIP will do this all for you. You can also use native XSL functions in your data to manipulate it prior to rendering. BP functions are not currently supported. The most impressive, for me at least, is the sheet 'bursting'. You can split your hierarchical data across multiple sheets and dynamically name those sheets. Finally, you of course, still get all the native Excel functionality. Pre-reqs You must be on 10.1.3.4.1 plus the latest rollup patch, 9546699. You can patch upa BIP instance running with OBIEE, no problem You need Excel 2000 or above to build the templates Some patience - there is no Excel template builder for these new templates. So its all going to have to be done by hand. Its not that tough but can get a little 'fiddly'. You can not test the template from Excel , it has to be deployed and then run. Limitations The new templates are definitely superior to the Analyzer templates but there are a few limitations. Re-grouping is not supported. You can only follow a data hierarchy not bend it to your will unless you want to get into macros. No support for BIP functions. The templates support native XSL functions only. No template builder Getting Started The templates make the use of named cells and groups of cells to allow BIP to find the insertion point for data points. It also uses a hidden sheet to store calculation mappings from named cells to XML data elements. To start with, in the great BIP tradition, we need some sample XML data. Becasue I wanted to show the master-detail output we need some hierarchical data. If you have not yet gotten into the data templates, now is a good time, I wrote a post a while back starting from the simple to more complex. They generate ideal data sets for these templates. Im working with the following data set: <EMPLOYEES> <LIST_G_DEPT> <G_DEPT> <DEPARTMENT_ID>10</DEPARTMENT_ID> <DEPARTMENT_NAME>Administration</DEPARTMENT_NAME> <LIST_G_EMP> <G_EMP> <EMPLOYEE_ID>200</EMPLOYEE_ID> <EMP_NAME>Jennifer Whalen</EMP_NAME> <EMAIL>JWHALEN</EMAIL> <PHONE_NUMBER>515.123.4444</PHONE_NUMBER> <HIRE_DATE>1987-09-17T00:00:00.000-06:00</HIRE_DATE> <SALARY>4400</SALARY> </G_EMP> </LIST_G_EMP> <TOTAL_EMPS>1</TOTAL_EMPS> <TOTAL_SALARY>4400</TOTAL_SALARY> <AVG_SALARY>4400</AVG_SALARY> <MAX_SALARY>4400</MAX_SALARY> <MIN_SALARY>4400</MIN_SALARY> </G_DEPT> ... <LIST_G_DEPT> <EMPLOYEES> Simple enough to follow and bread and butter stuff for an RTF template. Building the Template For an Excel template we need to start by thinking about how we want to render the data. Come up with a sample output in Excel. Its all dummy data, nothing marked up yet with one row of data for each level. I have the department name and then a repeating row for the employees. You can apply Excel formatting to the layout. The total is going to be derived from a data element. We'll get to Excel functions later. Marking Up Cells Next we need to start marking up the cells with custom names to map them to data elements. The cell names need to follow a specific format: For data grouping, XDO_GROUP_?group_name? For data elements, XDO_?element_name? Notice the question mark delimter, the group_name and element_name are case sensitive. The next step is to find how to name cells; the easiest method is to highlight the cell and then type in the name. You can also find the Name Manager dialog. I use 2007 and its available on the ribbon under the Formulas section Go thorugh the process of naming all the cells for the element values you have. Using my data set from above.You should end up with something like this in your 'Name Manager' dialog. You can update any mistakes you might have made through this dialog. Creating Groups In the image above you can see there are a couple of named group cells. To create these its a simple case of highlighting the cells that make up the group and then naming them. For the EMP group, highlight the employee row and then type in the name, XDO_GROUP?G_EMP? Notice the 10,000 total is outside of the G_EMP group. Its actually named, XDO_?TOTAL_SALARY?, a query calculated value. For the department group, we need to include the department name cell and the sub EMP grouping and name it, XDO_GROUP?G_DEPT? Notice, the 10,000 total is included in the G_DEPT group. This will ensure it repeats at the department level. Lastly, we do need to include a special sheet in the workbook. We will not have anything meaningful in there for now, but it needs to be present. Create a new sheet and name it XDO_METADATA. The name is important as the BIP rendering engine will looking for it. For our current example we do not need anything other than the required stuff in our XDO_METADATA sheet but, it must be present. Easy enough to hide it. Here's what I have: The only cell that is important is the 'Data Constraints:' cell. The rest is optional. To save curious users getting distracted, hide the metadata sheet. Deploying & Running Templates We should now have a usable Excel template. Loading it into a report is easy enough using the browser UI, just like an RTF template. Set the template type to Excel. You will now be able to run the report and hopefully get something like this. You will not get the red highlighting, thats just some conditional formatting I added to the template using Excel functionality. Your dates are probably going to look raw too. I got around this for now using an Excel function on the cell: =--REPLACE(SUBSTITUTE(E8,"T"," "),LEN(E8)-6,6,"") Google to the rescue on that one. Try some other stuff out. To avoid constantly loading the template through the UI. If you have BIP running locally or you can access the reports repository, once you have loaded the template the first time. Just save the template directly into the report folder. I have put together a sample report using a sample data set, available here. Just drop the xml data file, EmpbyDeptExcelData.xml into 'demo files' folder and you should be good to go. Thats the basics, next we'll start using some XSL functions in the template and move onto the 'bursting' across sheets.

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  • jQuery Templates in ASP.NET - Blogs Series

    - by hajan
    In the previous days, I wrote several blog posts related to the great jQuery Templates plugin showing various examples that might help you get started working with the plugin in ASP.NET and VS.NET environment. Here is the list of all five blogs: Introduction to jQuery Templates jQuery Templates - tmpl(), template() and tmplItem() jQuery Templates - {Supported Tags} jQuery Templates with ASP.NET MVC jQuery Templates - XHTML Validation Thank you for reading and wait for my next blogs! All the best, Hajan

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  • T4 Performance Counters explained

    - by user13346607
    Now that T4 is out for a few month some people might have wondered what details of the new pipeline you can monitor. A "cpustat -h" lists a lot of events that can be monitored, and only very few are self-explanatory. I will try to give some insight on all of them, some of these "PIC events" require an in-depth knowledge of T4 pipeline. Over time I will try to explain these, for the time being these events should simply be ignored. (Side note: some counters changed from tape-out 1.1 (*only* used in the T4 beta program) to tape-out 1.2 (used in the systems shipping today) The table only lists the tape-out 1.2 counters) 0 0 1 1058 6033 Oracle Microelectronics 50 14 7077 14.0 Normal 0 false false false EN-US JA X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:Cambria; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin;} pic name (cpustat) Prose Comment Sel-pipe-drain-cycles, Sel-0-[wait|ready], Sel-[1,2] Sel-0-wait counts cycles a strand waits to be selected. Some reasons can be counted in detail; these are: Sel-0-ready: Cycles a strand was ready but not selected, that can signal pipeline oversubscription Sel-1: Cycles only one instruction or µop was selected Sel-2: Cycles two instructions or µops were selected Sel-pipe-drain-cycles: cf. PRM footnote 8 to table 10.2 Pick-any, Pick-[0|1|2|3] Cycles one, two, three, no or at least one instruction or µop is picked Instr_FGU_crypto Number of FGU or crypto instructions executed on that vcpu Instr_ld dto. for load Instr_st dto. for store SPR_ring_ops dto. for SPR ring ops Instr_other dto. for all other instructions not listed above, PRM footnote 7 to table 10.2 lists the instructions Instr_all total number of instructions executed on that vcpu Sw_count_intr Nr of S/W count instructions on that vcpu (sethi %hi(fc000),%g0 (whatever that is))  Atomics nr of atomic ops, which are LDSTUB/a, CASA/XA, and SWAP/A SW_prefetch Nr of PREFETCH or PREFETCHA instructions Block_ld_st Block loads or store on that vcpu IC_miss_nospec, IC_miss_[L2_or_L3|local|remote]\ _hit_nospec Various I$ misses, distinguished by where they hit. All of these count per thread, but only primary events: T4 counts only the first occurence of an I$ miss on a core for a certain instruction. If one strand misses in I$ this miss is counted, but if a second strand on the same core misses while the first miss is being resolved, that second miss is not counted This flavour of I$ misses counts only misses that are caused by instruction that really commit (note the "_nospec") BTC_miss Branch target cache miss ITLB_miss ITLB misses (synchronously counted) ITLB_miss_asynch dto. but asynchronously [I|D]TLB_fill_\ [8KB|64KB|4MB|256MB|2GB|trap] H/W tablewalk events that fill ITLB or DTLB with translation for the corresponding page size. The “_trap” event occurs if the HWTW was not able to fill the corresponding TLB IC_mtag_miss, IC_mtag_miss_\ [ptag_hit|ptag_miss|\ ptag_hit_way_mismatch] I$ micro tag misses, with some options for drill down Fetch-0, Fetch-0-all fetch-0 counts nr of cycles nothing was fetched for this particular strand, fetch-0-all counts cycles nothing was fetched for all strands on a core Instr_buffer_full Cycles the instruction buffer for a strand was full, thereby preventing any fetch BTC_targ_incorrect Counts all occurences of wrongly predicted branch targets from the BTC [PQ|ROB|LB|ROB_LB|SB|\ ROB_SB|LB_SB|RB_LB_SB|\ DTLB_miss]\ _tag_wait ST_q_tag_wait is listed under sl=20. These counters monitor pipeline behaviour therefore they are not strand specific: PQ_...: cycles Rename stage waits for a Pick Queue tag (might signal memory bound workload for single thread mode, cf. Mail from Richard Smith) ROB_...: cycles Select stage waits for a ROB (ReOrderBuffer) tag LB_...: cycles Select stage waits for a Load Buffer tag SB_...: cycles Select stage waits for Store Buffer tag combinations of the above are allowed, although some of these events can overlap, the counter will only be incremented once per cycle if any of these occur DTLB_...: cycles load or store instructions wait at Pick stage for a DTLB miss tag [ID]TLB_HWTW_\ [L2_hit|L3_hit|L3_miss|all] Counters for HWTW accesses caused by either DTLB or ITLB misses. Canbe further detailed by where they hit IC_miss_L2_L3_hit, IC_miss_local_remote_remL3_hit, IC_miss I$ prefetches that were dropped because they either miss in L2$ or L3$ This variant counts misses regardless if the causing instruction commits or not DC_miss_nospec, DC_miss_[L2_L3|local|remote_L3]\ _hit_nospec D$ misses either in general or detailed by where they hit cf. the explanation for the IC_miss in two flavours for an explanation of _nospec and the reasoning for two DC_miss counters DTLB_miss_asynch counts all DTLB misses asynchronously, there is no way to count them synchronously DC_pref_drop_DC_hit, SW_pref_drop_[DC_hit|buffer_full] L1-D$ h/w prefetches that were dropped because of a D$ hit, counted per core. The others count software prefetches per strand [Full|Partial]_RAW_hit_st_[buf|q] Count events where a load wants to get data that has not yet been stored, i. e. it is still inside the pipeline. The data might be either still in the store buffer or in the store queue. If the load's data matches in the SB and in the store queue the data in buffer takes precedence of course since it is younger [IC|DC]_evict_invalid, [IC|DC|L1]_snoop_invalid, [IC|DC|L1]_invalid_all Counter for invalidated cache evictions per core St_q_tag_wait Number of cycles pipeline waits for a store queue tag, of course counted per core Data_pref_[drop_L2|drop_L3|\ hit_L2|hit_L3|\ hit_local|hit_remote] Data prefetches that can be further detailed by either why they were dropped or where they did hit St_hit_[L2|L3], St_L2_[local|remote]_C2C, St_local, St_remote Store events distinguished by where they hit or where they cause a L2 cache-to-cache transfer, i.e. either a transfer from another L2$ on the same die or from a different die DC_miss, DC_miss_\ [L2_L3|local|remote]_hit D$ misses either in general or detailed by where they hit cf. the explanation for the IC_miss in two flavours for an explanation of _nospec and the reasoning for two DC_miss counters L2_[clean|dirty]_evict Per core clean or dirty L2$ evictions L2_fill_buf_full, L2_wb_buf_full, L2_miss_buf_full Per core L2$ buffer events, all count number of cycles that this state was present L2_pipe_stall Per core cycles pipeline stalled because of L2$ Branches Count branches (Tcc, DONE, RETRY, and SIT are not counted as branches) Br_taken Counts taken branches (Tcc, DONE, RETRY, and SIT are not counted as branches) Br_mispred, Br_dir_mispred, Br_trg_mispred, Br_trg_mispred_\ [far_tbl|indir_tbl|ret_stk] Counter for various branch misprediction events.  Cycles_user counts cycles, attribute setting hpriv, nouser, sys controls addess space to count in Commit-[0|1|2], Commit-0-all, Commit-1-or-2 Number of times either no, one, or two µops commit for a strand. Commit-0-all counts number of times no µop commits for the whole core, cf. footnote 11 to table 10.2 in PRM for a more detailed explanation on how this counters interacts with the privilege levels

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  • Oracle TimesTen In-Memory Database Performance on SPARC T4-2

    - by Brian
    The Oracle TimesTen In-Memory Database is optimized to run on Oracle's SPARC T4 processor platforms running Oracle Solaris 11 providing unsurpassed scalability, performance, upgradability, protection of investment and return on investment. The following demonstrate the value of combining Oracle TimesTen In-Memory Database with SPARC T4 servers and Oracle Solaris 11: On a Mobile Call Processing test, the 2-socket SPARC T4-2 server outperforms: Oracle's SPARC Enterprise M4000 server (4 x 2.66 GHz SPARC64 VII+) by 34%. Oracle's SPARC T3-4 (4 x 1.65 GHz SPARC T3) by 2.7x, or 5.4x per processor. Utilizing the TimesTen Performance Throughput Benchmark (TPTBM), the SPARC T4-2 server protects investments with: 2.1x the overall performance of a 4-socket SPARC Enterprise M4000 server in read-only mode and 1.5x the performance in update-only testing. This is 4.2x more performance per processor than the SPARC64 VII+ 2.66 GHz based system. 10x more performance per processor than the SPARC T2+ 1.4 GHz server. 1.6x better performance per processor than the SPARC T3 1.65 GHz based server. In replication testing, the two socket SPARC T4-2 server is over 3x faster than the performance of a four socket SPARC Enterprise T5440 server in both asynchronous replication environment and the highly available 2-Safe replication. This testing emphasizes parallel replication between systems. Performance Landscape Mobile Call Processing Test Performance System Processor Sockets/Cores/Threads Tps SPARC T4-2 SPARC T4, 2.85 GHz 2 16 128 218,400 M4000 SPARC64 VII+, 2.66 GHz 4 16 32 162,900 SPARC T3-4 SPARC T3, 1.65 GHz 4 64 512 80,400 TimesTen Performance Throughput Benchmark (TPTBM) Read-Only System Processor Sockets/Cores/Threads Tps SPARC T3-4 SPARC T3, 1.65 GHz 4 64 512 7.9M SPARC T4-2 SPARC T4, 2.85 GHz 2 16 128 6.5M M4000 SPARC64 VII+, 2.66 GHz 4 16 32 3.1M T5440 SPARC T2+, 1.4 GHz 4 32 256 3.1M TimesTen Performance Throughput Benchmark (TPTBM) Update-Only System Processor Sockets/Cores/Threads Tps SPARC T4-2 SPARC T4, 2.85 GHz 2 16 128 547,800 M4000 SPARC64 VII+, 2.66 GHz 4 16 32 363,800 SPARC T3-4 SPARC T3, 1.65 GHz 4 64 512 240,500 TimesTen Replication Tests System Processor Sockets/Cores/Threads Asynchronous 2-Safe SPARC T4-2 SPARC T4, 2.85 GHz 2 16 128 38,024 13,701 SPARC T5440 SPARC T2+, 1.4 GHz 4 32 256 11,621 4,615 Configuration Summary Hardware Configurations: SPARC T4-2 server 2 x SPARC T4 processors, 2.85 GHz 256 GB memory 1 x 8 Gbs FC Qlogic HBA 1 x 6 Gbs SAS HBA 4 x 300 GB internal disks Sun Storage F5100 Flash Array (40 x 24 GB flash modules) 1 x Sun Fire X4275 server configured as COMSTAR head SPARC T3-4 server 4 x SPARC T3 processors, 1.6 GHz 512 GB memory 1 x 8 Gbs FC Qlogic HBA 8 x 146 GB internal disks 1 x Sun Fire X4275 server configured as COMSTAR head SPARC Enterprise M4000 server 4 x SPARC64 VII+ processors, 2.66 GHz 128 GB memory 1 x 8 Gbs FC Qlogic HBA 1 x 6 Gbs SAS HBA 2 x 146 GB internal disks Sun Storage F5100 Flash Array (40 x 24 GB flash modules) 1 x Sun Fire X4275 server configured as COMSTAR head Software Configuration: Oracle Solaris 11 11/11 Oracle TimesTen 11.2.2.4 Benchmark Descriptions TimesTen Performance Throughput BenchMark (TPTBM) is shipped with TimesTen and measures the total throughput of the system. The workload can test read-only, update-only, delete and insert operations as required. Mobile Call Processing is a customer-based workload for processing calls made by mobile phone subscribers. The workload has a mixture of read-only, update, and insert-only transactions. The peak throughput performance is measured from multiple concurrent processes executing the transactions until a peak performance is reached via saturation of the available resources. Parallel Replication tests using both asynchronous and 2-Safe replication methods. For asynchronous replication, transactions are processed in batches to maximize the throughput capabilities of the replication server and network. In 2-Safe replication, also known as no data-loss or high availability, transactions are replicated between servers immediately emphasizing low latency. For both environments, performance is measured in the number of parallel replication servers and the maximum transactions-per-second for all concurrent processes. See Also SPARC T4-2 Server oracle.com OTN Oracle TimesTen In-Memory Database oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Disclosure Statement Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 1 October 2012.

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  • T4 Implementation Boot Camp

    - by mseika
    T4 Implementation Boot Camp Monday 17th - Tuesday 18th September 9.30 – 16-30 Designed to help you prepare to take the SPARC T4-Based Server Installation Essentials (1Z1-597) exam this two-day Boot Camp is for hardware services/installation engineers with server installations experience who have solid expertise in Oracle Solaris. The SPARC T4-Based Server Installation Essentials Boot Camp consists of five topics: SPARC T4 Server Overview Describes the T4 processor architecture, server architecture, target workloads and its cryptographic and virtualisation capabilities. Oracle Enterprise Installation Standards (EIS) Describes the Oracle Enterprise Installation methodology and explains how and why this makes for an easier, safer and more reliable installation. SPARC T4 Server Installation Describes the actual process of physically installing the server, including testing and validation. Oracle VM Server for SPARC Describes how to install and setup logical domains on a T4 server. SPARC T4 Server Maintenance and Diagnostics Describes how to configure, maintain and upgrade the components in a T4 server. Please register here

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  • T4 Toolbox - mixing class feature and statement blocks

    - by Mauricio Scheffer
    I'm a T4 newbie trying to use T4 Toolbox to generate F# code based on this answer, but it seems that class feature blocks can't be mixed with statement blocks. Here's my code: <#@ template language="C#" hostspecific="True" debug="True" #> <#@ output extension="txt" #> <#@ include file="T4Toolbox.tt" #> <# FSharpTemplate template = new FSharpTemplate(); template.Output.Project = @"..\Library1\Library1.fsproj"; template.Output.File = "Module2.fs"; template.Render(); #> <#+ class FSharpTemplate: Template { public override string TransformText() { #> module Module2 <# for (int i = 0; i < 10; i++) { #> <#= i #> <# } #> <#+ return this.GenerationEnvironment.ToString(); } } #> And I get this error: A Statement cannot appear after the first class feature in the template. Only boilerplate, expressions and other class features are allowed after the first class feature block. So... how can I rewrite the template to achieve this?

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  • Using a :default for file names on include templates in SMARTY 3 [closed]

    - by Yohan Leafheart
    Hello everyone, Although I don't think the question was as good as it could be, let me try to explain better here. I have a site using SMARTY 3 as the template system. I have a template structure similar to the below one: /templates/place1/inner_a.tpl /templates/place1/inner_b.tpl /templates/place2/inner_b.tpl /templates/place2/inner_c.tpl /templates/default/inner_a.tpl /templates/default/inner_b.tpl /templates/default/inner_c.tpl These are getting included on the parent template using {include file="{$temp_folder}/{$inner_template}"} So far great. What I wanted to do is having a default for, in the case that the file "{$temp_folder}/{$inner_template}" does not exists, it uses the equivalent file at "default/{$inner_template}". i.e. If I do {include file="place1/inner_c.tpl"}, since that file does not exists it in fact includes "default/inner_c.tpl" Is it possible?

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  • An Introduction to jQuery Templates

    - by Stephen Walther
    The goal of this blog entry is to provide you with enough information to start working with jQuery Templates. jQuery Templates enable you to display and manipulate data in the browser. For example, you can use jQuery Templates to format and display a set of database records that you have retrieved with an Ajax call. jQuery Templates supports a number of powerful features such as template tags, template composition, and wrapped templates. I’ll concentrate on the features that I think that you will find most useful. In order to focus on the jQuery Templates feature itself, this blog entry is server technology agnostic. All the samples use HTML pages instead of ASP.NET pages. In a future blog entry, I’ll focus on using jQuery Templates with ASP.NET Web Forms and ASP.NET MVC (You can do some pretty powerful things when jQuery Templates are used on the client and ASP.NET is used on the server). Introduction to jQuery Templates The jQuery Templates plugin was developed by the Microsoft ASP.NET team in collaboration with the open-source jQuery team. While working at Microsoft, I wrote the original proposal for jQuery Templates, Dave Reed wrote the original code, and Boris Moore wrote the final code. The jQuery team – especially John Resig – was very involved in each step of the process. Both the jQuery community and ASP.NET communities were very active in providing feedback. jQuery Templates will be included in the jQuery core library (the jQuery.js library) when jQuery 1.5 is released. Until jQuery 1.5 is released, you can download the jQuery Templates plugin from the jQuery Source Code Repository or you can use jQuery Templates directly from the ASP.NET CDN. The documentation for jQuery Templates is already included with the official jQuery documentation at http://api.jQuery.com. The main entry for jQuery templates is located under the topic plugins/templates. A Basic Sample of jQuery Templates Let’s start with a really simple sample of using jQuery Templates. We’ll use the plugin to display a list of books stored in a JavaScript array. Here’s the complete code: <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> <html > <head> <title>Intro</title> <link href="0_Site.css" rel="stylesheet" type="text/css" /> </head> <body> <div id="pageContent"> <h1>ASP.NET Bookstore</h1> <div id="bookContainer"></div> </div> <script id="bookTemplate" type="text/x-jQuery-tmpl"> <div> <img src="BookPictures/${picture}" alt="" /> <h2>${title}</h2> price: ${formatPrice(price)} </div> </script> <script type="text/javascript" src="http://ajax.aspnetcdn.com/ajax/jQuery/jquery-1.4.4.js"></script> <script type="text/javascript" src="http://ajax.aspnetcdn.com/ajax/jquery.templates/beta1/jquery.tmpl.js"></script> <script type="text/javascript"> // Create an array of books var books = [ { title: "ASP.NET 4 Unleashed", price: 37.79, picture: "AspNet4Unleashed.jpg" }, { title: "ASP.NET MVC Unleashed", price: 44.99, picture: "AspNetMvcUnleashed.jpg" }, { title: "ASP.NET Kick Start", price: 4.00, picture: "AspNetKickStart.jpg" }, { title: "ASP.NET MVC Unleashed iPhone", price: 44.99, picture: "AspNetMvcUnleashedIPhone.jpg" }, ]; // Render the books using the template $("#bookTemplate").tmpl(books).appendTo("#bookContainer"); function formatPrice(price) { return "$" + price.toFixed(2); } </script> </body> </html> When you open this page in a browser, a list of books is displayed: There are several things going on in this page which require explanation. First, notice that the page uses both the jQuery 1.4.4 and jQuery Templates libraries. Both libraries are retrieved from the ASP.NET CDN: <script type="text/javascript" src="http://ajax.aspnetcdn.com/ajax/jQuery/jquery-1.4.4.js"></script> <script type="text/javascript" src="http://ajax.aspnetcdn.com/ajax/jquery.templates/beta1/jquery.tmpl.js"></script> You can use the ASP.NET CDN for free (even for production websites). You can learn more about the files included on the ASP.NET CDN by visiting the ASP.NET CDN documentation page. Second, you should notice that the actual template is included in a script tag with a special MIME type: <script id="bookTemplate" type="text/x-jQuery-tmpl"> <div> <img src="BookPictures/${picture}" alt="" /> <h2>${title}</h2> price: ${formatPrice(price)} </div> </script> This template is displayed for each of the books rendered by the template. The template displays a book picture, title, and price. Notice that the SCRIPT tag which wraps the template has a MIME type of text/x-jQuery-tmpl. Why is the template wrapped in a SCRIPT tag and why the strange MIME type? When a browser encounters a SCRIPT tag with an unknown MIME type, it ignores the content of the tag. This is the behavior that you want with a template. You don’t want a browser to attempt to parse the contents of a template because this might cause side effects. For example, the template above includes an <img> tag with a src attribute that points at “BookPictures/${picture}”. You don’t want the browser to attempt to load an image at the URL “BookPictures/${picture}”. Instead, you want to prevent the browser from processing the IMG tag until the ${picture} expression is replaced by with the actual name of an image by the jQuery Templates plugin. If you are not worried about browser side-effects then you can wrap a template inside any HTML tag that you please. For example, the following DIV tag would also work with the jQuery Templates plugin: <div id="bookTemplate" style="display:none"> <div> <h2>${title}</h2> price: ${formatPrice(price)} </div> </div> Notice that the DIV tag includes a style=”display:none” attribute to prevent the template from being displayed until the template is parsed by the jQuery Templates plugin. Third, notice that the expression ${…} is used to display the value of a JavaScript expression within a template. For example, the expression ${title} is used to display the value of the book title property. You can use any JavaScript function that you please within the ${…} expression. For example, in the template above, the book price is formatted with the help of the custom JavaScript formatPrice() function which is defined lower in the page. Fourth, and finally, the template is rendered with the help of the tmpl() method. The following statement selects the bookTemplate and renders an array of books using the bookTemplate. The results are appended to a DIV element named bookContainer by using the standard jQuery appendTo() method. $("#bookTemplate").tmpl(books).appendTo("#bookContainer"); Using Template Tags Within a template, you can use any of the following template tags. {{tmpl}} – Used for template composition. See the section below. {{wrap}} – Used for wrapped templates. See the section below. {{each}} – Used to iterate through a collection. {{if}} – Used to conditionally display template content. {{else}} – Used with {{if}} to conditionally display template content. {{html}} – Used to display the value of an HTML expression without encoding the value. Using ${…} or {{= }} performs HTML encoding automatically. {{= }}-- Used in exactly the same way as ${…}. {{! }} – Used for displaying comments. The contents of a {{!...}} tag are ignored. For example, imagine that you want to display a list of blog entries. Each blog entry could, possibly, have an associated list of categories. The following page illustrates how you can use the { if}} and {{each}} template tags to conditionally display categories for each blog entry:   <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> <html xmlns="http://www.w3.org/1999/xhtml"> <head> <title>each</title> <link href="1_Site.css" rel="stylesheet" type="text/css" /> </head> <body> <div id="blogPostContainer"></div> <script id="blogPostTemplate" type="text/x-jQuery-tmpl"> <h1>${postTitle}</h1> <p> ${postEntry} </p> {{if categories}} Categories: {{each categories}} <i>${$value}</i> {{/each}} {{else}} Uncategorized {{/if}} </script> <script type="text/javascript" src="http://ajax.aspnetcdn.com/ajax/jQuery/jquery-1.4.4.js"></script> <script type="text/javascript" src="http://ajax.aspnetcdn.com/ajax/jquery.templates/beta1/jquery.tmpl.js"></script> <script type="text/javascript"> var blogPosts = [ { postTitle: "How to fix a sink plunger in 5 minutes", postEntry: "Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Maecenas porttitor congue massa. Fusce posuere, magna sed pulvinar ultricies, purus lectus malesuada libero, sit amet commodo magna eros quis urna.", categories: ["HowTo", "Sinks", "Plumbing"] }, { postTitle: "How to remove a broken lightbulb", postEntry: "Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Maecenas porttitor congue massa. Fusce posuere, magna sed pulvinar ultricies, purus lectus malesuada libero, sit amet commodo magna eros quis urna.", categories: ["HowTo", "Lightbulbs", "Electricity"] }, { postTitle: "New associate website", postEntry: "Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Maecenas porttitor congue massa. Fusce posuere, magna sed pulvinar ultricies, purus lectus malesuada libero, sit amet commodo magna eros quis urna." } ]; // Render the blog posts $("#blogPostTemplate").tmpl(blogPosts).appendTo("#blogPostContainer"); </script> </body> </html> When this page is opened in a web browser, the following list of blog posts and categories is displayed: Notice that the first and second blog entries have associated categories but the third blog entry does not. The third blog entry is “Uncategorized”. The template used to render the blog entries and categories looks like this: <script id="blogPostTemplate" type="text/x-jQuery-tmpl"> <h1>${postTitle}</h1> <p> ${postEntry} </p> {{if categories}} Categories: {{each categories}} <i>${$value}</i> {{/each}} {{else}} Uncategorized {{/if}} </script> Notice the special expression $value used within the {{each}} template tag. You can use $value to display the value of the current template item. In this case, $value is used to display the value of each category in the collection of categories. Template Composition When building a fancy page, you might want to build a template out of multiple templates. In other words, you might want to take advantage of template composition. For example, imagine that you want to display a list of products. Some of the products are being sold at their normal price and some of the products are on sale. In that case, you might want to use two different templates for displaying a product: a productTemplate and a productOnSaleTemplate. The following page illustrates how you can use the {{tmpl}} tag to build a template from multiple templates:   <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> <html xmlns="http://www.w3.org/1999/xhtml"> <head> <title>Composition</title> <link href="2_Site.css" rel="stylesheet" type="text/css" /> </head> <body> <div id="pageContainer"> <h1>Products</h1> <div id="productListContainer"></div> <!-- Show list of products using composition --> <script id="productListTemplate" type="text/x-jQuery-tmpl"> <div> {{if onSale}} {{tmpl "#productOnSaleTemplate"}} {{else}} {{tmpl "#productTemplate"}} {{/if}} </div> </script> <!-- Show product --> <script id="productTemplate" type="text/x-jQuery-tmpl"> ${name} </script> <!-- Show product on sale --> <script id="productOnSaleTemplate" type="text/x-jQuery-tmpl"> <b>${name}</b> <img src="images/on_sale.png" alt="On Sale" /> </script> <script type="text/javascript" src="http://ajax.aspnetcdn.com/ajax/jQuery/jquery-1.4.4.js"></script> <script type="text/javascript" src="http://ajax.aspnetcdn.com/ajax/jquery.templates/beta1/jquery.tmpl.js"></script> <script type="text/javascript"> var products = [ { name: "Laptop", onSale: false }, { name: "Apples", onSale: true }, { name: "Comb", onSale: false } ]; $("#productListTemplate").tmpl(products).appendTo("#productListContainer"); </script> </div> </body> </html>   In the page above, the main template used to display the list of products looks like this: <script id="productListTemplate" type="text/x-jQuery-tmpl"> <div> {{if onSale}} {{tmpl "#productOnSaleTemplate"}} {{else}} {{tmpl "#productTemplate"}} {{/if}} </div> </script>   If a product is on sale then the product is displayed with the productOnSaleTemplate (which includes an on sale image): <script id="productOnSaleTemplate" type="text/x-jQuery-tmpl"> <b>${name}</b> <img src="images/on_sale.png" alt="On Sale" /> </script>   Otherwise, the product is displayed with the normal productTemplate (which does not include the on sale image): <script id="productTemplate" type="text/x-jQuery-tmpl"> ${name} </script>   You can pass a parameter to the {{tmpl}} tag. The parameter becomes the data passed to the template rendered by the {{tmpl}} tag. For example, in the previous section, we used the {{each}} template tag to display a list of categories for each blog entry like this: <script id="blogPostTemplate" type="text/x-jQuery-tmpl"> <h1>${postTitle}</h1> <p> ${postEntry} </p> {{if categories}} Categories: {{each categories}} <i>${$value}</i> {{/each}} {{else}} Uncategorized {{/if}} </script>   Another way to create this template is to use template composition like this: <script id="blogPostTemplate" type="text/x-jQuery-tmpl"> <h1>${postTitle}</h1> <p> ${postEntry} </p> {{if categories}} Categories: {{tmpl(categories) "#categoryTemplate"}} {{else}} Uncategorized {{/if}} </script> <script id="categoryTemplate" type="text/x-jQuery-tmpl"> <i>${$data}</i> &nbsp; </script>   Using the {{each}} tag or {{tmpl}} tag is largely a matter of personal preference. Wrapped Templates The {{wrap}} template tag enables you to take a chunk of HTML and transform the HTML into another chunk of HTML (think easy XSLT). When you use the {{wrap}} tag, you work with two templates. The first template contains the HTML being transformed and the second template includes the filter expressions for transforming the HTML. For example, you can use the {{wrap}} template tag to transform a chunk of HTML into an interactive tab strip: When you click any of the tabs, you see the corresponding content. This tab strip was created with the following page: <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> <html xmlns="http://www.w3.org/1999/xhtml"> <head> <title>Wrapped Templates</title> <style type="text/css"> body { font-family: Arial; background-color:black; } .tabs div { display:inline-block; border-bottom: 1px solid black; padding:4px; background-color:gray; cursor:pointer; } .tabs div.tabState_true { background-color:white; border-bottom:1px solid white; } .tabBody { border-top:1px solid white; padding:10px; background-color:white; min-height:400px; width:400px; } </style> </head> <body> <div id="tabsView"></div> <script id="tabsContent" type="text/x-jquery-tmpl"> {{wrap "#tabsWrap"}} <h3>Tab 1</h3> <div> Content of tab 1. Lorem ipsum dolor <b>sit</b> amet, consectetuer adipiscing elit. Maecenas porttitor congue massa. Fusce posuere, magna sed pulvinar ultricies, purus lectus malesuada libero, sit amet commodo magna eros quis urna. </div> <h3>Tab 2</h3> <div> Content of tab 2. Lorem ipsum dolor <b>sit</b> amet, consectetuer adipiscing elit. Maecenas porttitor congue massa. Fusce posuere, magna sed pulvinar ultricies, purus lectus malesuada libero, sit amet commodo magna eros quis urna. </div> <h3>Tab 3</h3> <div> Content of tab 3. Lorem ipsum dolor <b>sit</b> amet, consectetuer adipiscing elit. Maecenas porttitor congue massa. Fusce posuere, magna sed pulvinar ultricies, purus lectus malesuada libero, sit amet commodo magna eros quis urna. </div> {{/wrap}} </script> <script id="tabsWrap" type="text/x-jquery-tmpl"> <div class="tabs"> {{each $item.html("h3", true)}} <div class="tabState_${$index === selectedTabIndex}"> ${$value} </div> {{/each}} </div> <div class="tabBody"> {{html $item.html("div")[selectedTabIndex]}} </div> </script> <script type="text/javascript" src="http://ajax.aspnetcdn.com/ajax/jQuery/jquery-1.4.4.js"></script> <script type="text/javascript" src="http://ajax.aspnetcdn.com/ajax/jquery.templates/beta1/jquery.tmpl.js"></script> <script type="text/javascript"> // Global for tracking selected tab var selectedTabIndex = 0; // Render the tab strip $("#tabsContent").tmpl().appendTo("#tabsView"); // When a tab is clicked, update the tab strip $("#tabsView") .delegate(".tabState_false", "click", function () { var templateItem = $.tmplItem(this); selectedTabIndex = $(this).index(); templateItem.update(); }); </script> </body> </html>   The “source” for the tab strip is contained in the following template: <script id="tabsContent" type="text/x-jquery-tmpl"> {{wrap "#tabsWrap"}} <h3>Tab 1</h3> <div> Content of tab 1. Lorem ipsum dolor <b>sit</b> amet, consectetuer adipiscing elit. Maecenas porttitor congue massa. Fusce posuere, magna sed pulvinar ultricies, purus lectus malesuada libero, sit amet commodo magna eros quis urna. </div> <h3>Tab 2</h3> <div> Content of tab 2. Lorem ipsum dolor <b>sit</b> amet, consectetuer adipiscing elit. Maecenas porttitor congue massa. Fusce posuere, magna sed pulvinar ultricies, purus lectus malesuada libero, sit amet commodo magna eros quis urna. </div> <h3>Tab 3</h3> <div> Content of tab 3. Lorem ipsum dolor <b>sit</b> amet, consectetuer adipiscing elit. Maecenas porttitor congue massa. Fusce posuere, magna sed pulvinar ultricies, purus lectus malesuada libero, sit amet commodo magna eros quis urna. </div> {{/wrap}} </script>   The tab strip is created with a list of H3 elements (which represent each tab) and DIV elements (which represent the body of each tab). Notice that the HTML content is wrapped in the {{wrap}} template tag. This template tag points at the following tabsWrap template: <script id="tabsWrap" type="text/x-jquery-tmpl"> <div class="tabs"> {{each $item.html("h3", true)}} <div class="tabState_${$index === selectedTabIndex}"> ${$value} </div> {{/each}} </div> <div class="tabBody"> {{html $item.html("div")[selectedTabIndex]}} </div> </script> The tabs DIV contains all of the tabs. The {{each}} template tag is used to loop through each of the H3 elements from the source template and render a DIV tag that represents a particular tab. The template item html() method is used to filter content from the “source” HTML template. The html() method accepts a jQuery selector for its first parameter. The tabs are retrieved from the source template by using an h3 filter. The second parameter passed to the html() method – the textOnly parameter -- causes the filter to return the inner text of each h3 element. You can learn more about the html() method at the jQuery website (see the section on $item.html()). The tabBody DIV renders the body of the selected tab. Notice that the {{html}} template tag is used to display the tab body so that HTML content in the body won’t be HTML encoded. The html() method is used, once again, to grab all of the DIV elements from the source HTML template. The selectedTabIndex global variable is used to display the contents of the selected tab. Remote Templates A common feature request for jQuery templates is support for remote templates. Developers want to be able to separate templates into different files. Adding support for remote templates requires only a few lines of extra code (Dave Ward has a nice blog entry on this). For example, the following page uses a remote template from a file named BookTemplate.htm: <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> <html xmlns="http://www.w3.org/1999/xhtml"> <head> <title>Remote Templates</title> <link href="0_Site.css" rel="stylesheet" type="text/css" /> </head> <body> <div id="pageContent"> <h1>ASP.NET Bookstore</h1> <div id="bookContainer"></div> </div> <script type="text/javascript" src="http://ajax.aspnetcdn.com/ajax/jQuery/jquery-1.4.4.js"></script> <script type="text/javascript" src="http://ajax.aspnetcdn.com/ajax/jquery.templates/beta1/jquery.tmpl.js"></script> <script type="text/javascript"> // Create an array of books var books = [ { title: "ASP.NET 4 Unleashed", price: 37.79, picture: "AspNet4Unleashed.jpg" }, { title: "ASP.NET MVC Unleashed", price: 44.99, picture: "AspNetMvcUnleashed.jpg" }, { title: "ASP.NET Kick Start", price: 4.00, picture: "AspNetKickStart.jpg" }, { title: "ASP.NET MVC Unleashed iPhone", price: 44.99, picture: "AspNetMvcUnleashedIPhone.jpg" }, ]; // Get the remote template $.get("BookTemplate.htm", null, function (bookTemplate) { // Render the books using the remote template $.tmpl(bookTemplate, books).appendTo("#bookContainer"); }); function formatPrice(price) { return "$" + price.toFixed(2); } </script> </body> </html>   The remote template is retrieved (and rendered) with the following code: // Get the remote template $.get("BookTemplate.htm", null, function (bookTemplate) { // Render the books using the remote template $.tmpl(bookTemplate, books).appendTo("#bookContainer"); });   This code uses the standard jQuery $.get() method to get the BookTemplate.htm file from the server with an Ajax request. After the BookTemplate.htm file is successfully retrieved, the $.tmpl() method is used to render an array of books with the template. Here’s what the BookTemplate.htm file looks like: <div> <img src="BookPictures/${picture}" alt="" /> <h2>${title}</h2> price: ${formatPrice(price)} </div> Notice that the template in the BooksTemplate.htm file is not wrapped by a SCRIPT element. There is no need to wrap the template in this case because there is no possibility that the template will get interpreted before you want it to be interpreted. If you plan to use the bookTemplate multiple times – for example, you are paging or sorting the books -- then you should compile the template into a function and cache the compiled template function. For example, the following page can be used to page through a list of 100 products (using iPhone style More paging). <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> <html xmlns="http://www.w3.org/1999/xhtml"> <head> <title>Template Caching</title> <link href="6_Site.css" rel="stylesheet" type="text/css" /> </head> <body> <h1>Products</h1> <div id="productContainer"></div> <button id="more">More</button> <script type="text/javascript" src="http://ajax.aspnetcdn.com/ajax/jQuery/jquery-1.4.4.js"></script> <script type="text/javascript" src="http://ajax.aspnetcdn.com/ajax/jquery.templates/beta1/jquery.tmpl.js"></script> <script type="text/javascript"> // Globals var pageIndex = 0; // Create an array of products var products = []; for (var i = 0; i < 100; i++) { products.push({ name: "Product " + (i + 1) }); } // Get the remote template $.get("ProductTemplate.htm", null, function (productTemplate) { // Compile and cache the template $.template("productTemplate", productTemplate); // Render the products renderProducts(0); }); $("#more").click(function () { pageIndex++; renderProducts(); }); function renderProducts() { // Get page of products var pageOfProducts = products.slice(pageIndex * 5, pageIndex * 5 + 5); // Used cached productTemplate to render products $.tmpl("productTemplate", pageOfProducts).appendTo("#productContainer"); } function formatPrice(price) { return "$" + price.toFixed(2); } </script> </body> </html>   The ProductTemplate is retrieved from an external file named ProductTemplate.htm. This template is retrieved only once. Furthermore, it is compiled and cached with the help of the $.template() method: // Get the remote template $.get("ProductTemplate.htm", null, function (productTemplate) { // Compile and cache the template $.template("productTemplate", productTemplate); // Render the products renderProducts(0); });   The $.template() method compiles the HTML representation of the template into a JavaScript function and caches the template function with the name productTemplate. The cached template can be used by calling the $.tmp() method. The productTemplate is used in the renderProducts() method: function renderProducts() { // Get page of products var pageOfProducts = products.slice(pageIndex * 5, pageIndex * 5 + 5); // Used cached productTemplate to render products $.tmpl("productTemplate", pageOfProducts).appendTo("#productContainer"); } In the code above, the first parameter passed to the $.tmpl() method is the name of a cached template. Working with Template Items In this final section, I want to devote some space to discussing Template Items. A new Template Item is created for each rendered instance of a template. For example, if you are displaying a list of 100 products with a template, then 100 Template Items are created. A Template Item has the following properties and methods: data – The data associated with the Template Instance. For example, a product. tmpl – The template associated with the Template Instance. parent – The parent template item if the template is nested. nodes – The HTML content of the template. calls – Used by {{wrap}} template tag. nest – Used by {{tmpl}} template tag. wrap – Used to imperatively enable wrapped templates. html – Used to filter content from a wrapped template. See the above section on wrapped templates. update – Used to re-render a template item. The last method – the update() method -- is especially interesting because it enables you to re-render a template item with new data or even a new template. For example, the following page displays a list of books. When you hover your mouse over any of the books, additional book details are displayed. In the following screenshot, details for ASP.NET Kick Start are displayed. <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> <html xmlns="http://www.w3.org/1999/xhtml"> <head> <title>Template Item</title> <link href="0_Site.css" rel="stylesheet" type="text/css" /> </head> <body> <div id="pageContent"> <h1>ASP.NET Bookstore</h1> <div id="bookContainer"></div> </div> <script id="bookTemplate" type="text/x-jQuery-tmpl"> <div class="bookItem"> <img src="BookPictures/${picture}" alt="" /> <h2>${title}</h2> price: ${formatPrice(price)} </div> </script> <script id="bookDetailsTemplate" type="text/x-jQuery-tmpl"> <div class="bookItem"> <img src="BookPictures/${picture}" alt="" /> <h2>${title}</h2> price: ${formatPrice(price)} <p> ${description} </p> </div> </script> <script type="text/javascript" src="http://ajax.aspnetcdn.com/ajax/jQuery/jquery-1.4.4.js"></script> <script type="text/javascript" src="http://ajax.aspnetcdn.com/ajax/jquery.templates/beta1/jquery.tmpl.js"></script> <script type="text/javascript"> // Create an array of books var books = [ { title: "ASP.NET 4 Unleashed", price: 37.79, picture: "AspNet4Unleashed.jpg", description: "The most comprehensive book on Microsoft’s new ASP.NET 4.. " }, { title: "ASP.NET MVC Unleashed", price: 44.99, picture: "AspNetMvcUnleashed.jpg", description: "Writing for professional programmers, Walther explains the crucial concepts that make the Model-View-Controller (MVC) development paradigm work…" }, { title: "ASP.NET Kick Start", price: 4.00, picture: "AspNetKickStart.jpg", description: "Visual Studio .NET is the premier development environment for creating .NET applications…." }, { title: "ASP.NET MVC Unleashed iPhone", price: 44.99, picture: "AspNetMvcUnleashedIPhone.jpg", description: "ASP.NET MVC Unleashed for the iPhone…" }, ]; // Render the books using the template $("#bookTemplate").tmpl(books).appendTo("#bookContainer"); // Get compiled details template var bookDetailsTemplate = $("#bookDetailsTemplate").template(); // Add hover handler $(".bookItem").mouseenter(function () { // Get template item associated with DIV var templateItem = $(this).tmplItem(); // Change template to compiled template templateItem.tmpl = bookDetailsTemplate; // Re-render template templateItem.update(); }); function formatPrice(price) { return "$" + price.toFixed(2); } </script> </body> </html>   There are two templates used to display a book: bookTemplate and bookDetailsTemplate. When you hover your mouse over a template item, the standard bookTemplate is swapped out for the bookDetailsTemplate. The bookDetailsTemplate displays a book description. The books are rendered with the bookTemplate with the following line of code: // Render the books using the template $("#bookTemplate").tmpl(books).appendTo("#bookContainer");   The following code is used to swap the bookTemplate and the bookDetailsTemplate to show details for a book: // Get compiled details template var bookDetailsTemplate = $("#bookDetailsTemplate").template(); // Add hover handler $(".bookItem").mouseenter(function () { // Get template item associated with DIV var templateItem = $(this).tmplItem(); // Change template to compiled template templateItem.tmpl = bookDetailsTemplate; // Re-render template templateItem.update(); });   When you hover your mouse over a DIV element rendered by the bookTemplate, the mouseenter handler executes. First, this handler retrieves the Template Item associated with the DIV element by calling the tmplItem() method. The tmplItem() method returns a Template Item. Next, a new template is assigned to the Template Item. Notice that a compiled version of the bookDetailsTemplate is assigned to the Template Item’s tmpl property. The template is compiled earlier in the code by calling the template() method. Finally, the Template Item update() method is called to re-render the Template Item with the bookDetailsTemplate instead of the original bookTemplate. Summary This is a long blog entry and I still have not managed to cover all of the features of jQuery Templates J However, I’ve tried to cover the most important features of jQuery Templates such as template composition, template wrapping, and template items. To learn more about jQuery Templates, I recommend that you look at the documentation for jQuery Templates at the official jQuery website. Another great way to learn more about jQuery Templates is to look at the (unminified) source code.

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  • Determining whether a class implements a generic list in a T4 template

    - by James Hollingworth
    I'm writing a T4 template which loads some classes from an assembly, does some analysis of the classes and then generates some code. One particular bit of analysis I need to do is to determine whether the class implements a generic list. I can do this pretty simply in C#, e.g. public class Foo : List<string> { } var t = typeof(Foo); if (t.BaseType != null && t.BaseType.IsGenericType && t.BaseType.GetGenericTypeDefinition() == typeof(List<>))) Console.WriteLine("Win"); However T4 templates use the FXCop introspection engine and so you do not have access to the .net reflection API. I've spent the past couple of hours in Reflector but still can't figure it out. Does anyone have any clues about how to do this?

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  • Talend Enterprise Data Integration overperforms on Oracle SPARC T4

    - by Amir Javanshir
    The SPARC T microprocessor, released in 2005 by Sun Microsystems, and now continued at Oracle, has a good track record in parallel execution and multi-threaded performance. However it was less suited for pure single-threaded workloads. The new SPARC T4 processor is now filling that gap by offering a 5x better single-thread performance over previous generations. Following our long-term relationship with Talend, a fast growing ISV positioned by Gartner in the “Visionaries” quadrant of the “Magic Quadrant for Data Integration Tools”, we decided to test some of their integration components with the T4 chip, more precisely on a T4-1 system, in order to verify first hand if this new processor stands up to its promises. Several tests were performed, mainly focused on: Single-thread performance of the new SPARC T4 processor compared to an older SPARC T2+ processor Overall throughput of the SPARC T4-1 server using multiple threads The tests consisted in reading large amounts of data --ten's of gigabytes--, processing and writing them back to a file or an Oracle 11gR2 database table. They are CPU, memory and IO bound tests. Given the main focus of this project --CPU performance--, bottlenecks were removed as much as possible on the memory and IO sub-systems. When possible, the data to process was put into the ZFS filesystem cache, for instance. Also, two external storage devices were directly attached to the servers under test, each one divided in two ZFS pools for read and write operations. Multi-thread: Testing throughput on the Oracle T4-1 The tests were performed with different number of simultaneous threads (1, 2, 4, 8, 12, 16, 32, 48 and 64) and using different storage devices: Flash, Fibre Channel storage, two stripped internal disks and one single internal disk. All storage devices used ZFS as filesystem and volume management. Each thread read a dedicated 1GB-large file containing 12.5M lines with the following structure: customerID;FirstName;LastName;StreetAddress;City;State;Zip;Cust_Status;Since_DT;Status_DT 1;Ronald;Reagan;South Highway;Santa Fe;Montana;98756;A;04-06-2006;09-08-2008 2;Theodore;Roosevelt;Timberlane Drive;Columbus;Louisiana;75677;A;10-05-2009;27-05-2008 3;Andrew;Madison;S Rustle St;Santa Fe;Arkansas;75677;A;29-04-2005;09-02-2008 4;Dwight;Adams;South Roosevelt Drive;Baton Rouge;Vermont;75677;A;15-02-2004;26-01-2007 […] The following graphs present the results of our tests: Unsurprisingly up to 16 threads, all files fit in the ZFS cache a.k.a L2ARC : once the cache is hot there is no performance difference depending on the underlying storage. From 16 threads upwards however, it is clear that IO becomes a bottleneck, having a good IO subsystem is thus key. Single-disk performance collapses whereas the Sun F5100 and ST6180 arrays allow the T4-1 to scale quite seamlessly. From 32 to 64 threads, the performance is almost constant with just a slow decline. For the database load tests, only the best IO configuration --using external storage devices-- were used, hosting the Oracle table spaces and redo log files. Using the Sun Storage F5100 array allows the T4-1 server to scale up to 48 parallel JVM processes before saturating the CPU. The final result is a staggering 646K lines per second insertion in an Oracle table using 48 parallel threads. Single-thread: Testing the single thread performance Seven different tests were performed on both servers. Given the fact that only one thread, thus one file was read, no IO bottleneck was involved, all data being served from the ZFS cache. Read File ? Filter ? Write File: Read file, filter data, write the filtered data in a new file. The filter is set on the “Status” column: only lines with status set to “A” are selected. This limits each output file to about 500 MB. Read File ? Load Database Table: Read file, insert into a single Oracle table. Average: Read file, compute the average of a numeric column, write the result in a new file. Division & Square Root: Read file, perform a division and square root on a numeric column, write the result data in a new file. Oracle DB Dump: Dump the content of an Oracle table (12.5M rows) into a CSV file. Transform: Read file, transform, write the result data in a new file. The transformations applied are: set the address column to upper case and add an extra column at the end, which is the concatenation of two columns. Sort: Read file, sort a numeric and alpha numeric column, write the result data in a new file. The following table and graph present the final results of the tests: Throughput unit is thousand lines per second processed (K lines/second). Improvement is the % of improvement between the T5140 and T4-1. Test T4-1 (Time s.) T5140 (Time s.) Improvement T4-1 (Throughput) T5140 (Throughput) Read/Filter/Write 125 806 645% 100 16 Read/Load Database 195 1111 570% 64 11 Average 96 557 580% 130 22 Division & Square Root 161 1054 655% 78 12 Oracle DB Dump 164 945 576% 76 13 Transform 159 1124 707% 79 11 Sort 251 1336 532% 50 9 The improvement of single-thread performance is quite dramatic: depending on the tests, the T4 is between 5.4 to 7 times faster than the T2+. It seems clear that the SPARC T4 processor has gone a long way filling the gap in single-thread performance, without sacrifying the multi-threaded capability as it still shows a very impressive scaling on heavy-duty multi-threaded jobs. Finally, as always at Oracle ISV Engineering, we are happy to help our ISV partners test their own applications on our platforms, so don't hesitate to contact us and let's see what the SPARC T4-based systems can do for your application! "As describe in this benchmark, Talend Enterprise Data Integration has overperformed on T4. I was generally happy to see that the T4 gave scaling opportunities for many scenarios like complex aggregations. Row by row insertion in Oracle DB is faster with more than 650,000 rows per seconds without using any bulk Oracle capabilities !" Cedric Carbone, Talend CTO.

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  • World Record Batch Rate on Oracle JD Edwards Consolidated Workload with SPARC T4-2

    - by Brian
    Oracle produced a World Record batch throughput for single system results on Oracle's JD Edwards EnterpriseOne Day-in-the-Life benchmark using Oracle's SPARC T4-2 server running Oracle Solaris Containers and consolidating JD Edwards EnterpriseOne, Oracle WebLogic servers and the Oracle Database 11g Release 2. The workload includes both online and batch workload. The SPARC T4-2 server delivered a result of 8,000 online users while concurrently executing a mix of JD Edwards EnterpriseOne Long and Short batch processes at 95.5 UBEs/min (Universal Batch Engines per minute). In order to obtain this record benchmark result, the JD Edwards EnterpriseOne, Oracle WebLogic and Oracle Database 11g Release 2 servers were executed each in separate Oracle Solaris Containers which enabled optimal system resources distribution and performance together with scalable and manageable virtualization. One SPARC T4-2 server running Oracle Solaris Containers and consolidating JD Edwards EnterpriseOne, Oracle WebLogic servers and the Oracle Database 11g Release 2 utilized only 55% of the available CPU power. The Oracle DB server in a Shared Server configuration allows for optimized CPU resource utilization and significant memory savings on the SPARC T4-2 server without sacrificing performance. This configuration with SPARC T4-2 server has achieved 33% more Users/core, 47% more UBEs/min and 78% more Users/rack unit than the IBM Power 770 server. The SPARC T4-2 server with 2 processors ran the JD Edwards "Day-in-the-Life" benchmark and supported 8,000 concurrent online users while concurrently executing mixed batch workloads at 95.5 UBEs per minute. The IBM Power 770 server with twice as many processors supported only 12,000 concurrent online users while concurrently executing mixed batch workloads at only 65 UBEs per minute. This benchmark demonstrates more than 2x cost savings by consolidating the complete solution in a single SPARC T4-2 server compared to earlier published results of 10,000 users and 67 UBEs per minute on two SPARC T4-2 and SPARC T4-1. The Oracle DB server used mirrored (RAID 1) volumes for the database providing high availability for the data without impacting performance. Performance Landscape JD Edwards EnterpriseOne Day in the Life (DIL) Benchmark Consolidated Online with Batch Workload System Rack Units BatchRate(UBEs/m) Online Users Users /Units Users /Core Version SPARC T4-2 (2 x SPARC T4, 2.85 GHz) 3 95.5 8,000 2,667 500 9.0.2 IBM Power 770 (4 x POWER7, 3.3 GHz, 32 cores) 8 65 12,000 1,500 375 9.0.2 Batch Rate (UBEs/m) — Batch transaction rate in UBEs per minute Configuration Summary Hardware Configuration: 1 x SPARC T4-2 server with 2 x SPARC T4 processors, 2.85 GHz 256 GB memory 4 x 300 GB 10K RPM SAS internal disk 2 x 300 GB internal SSD 2 x Sun Storage F5100 Flash Arrays Software Configuration: Oracle Solaris 10 Oracle Solaris Containers JD Edwards EnterpriseOne 9.0.2 JD Edwards EnterpriseOne Tools (8.98.4.2) Oracle WebLogic Server 11g (10.3.4) Oracle HTTP Server 11g Oracle Database 11g Release 2 (11.2.0.1) Benchmark Description JD Edwards EnterpriseOne is an integrated applications suite of Enterprise Resource Planning (ERP) software. Oracle offers 70 JD Edwards EnterpriseOne application modules to support a diverse set of business operations. Oracle's Day in the Life (DIL) kit is a suite of scripts that exercises most common transactions of JD Edwards EnterpriseOne applications, including business processes such as payroll, sales order, purchase order, work order, and manufacturing processes, such as ship confirmation. These are labeled by industry acronyms such as SCM, CRM, HCM, SRM and FMS. The kit's scripts execute transactions typical of a mid-sized manufacturing company. The workload consists of online transactions and the UBE – Universal Business Engine workload of 61 short and 4 long UBEs. LoadRunner runs the DIL workload, collects the user’s transactions response times and reports the key metric of Combined Weighted Average Transaction Response time. The UBE processes workload runs from the JD Enterprise Application server. Oracle's UBE processes come as three flavors: Short UBEs < 1 minute engage in Business Report and Summary Analysis, Mid UBEs > 1 minute create a large report of Account, Balance, and Full Address, Long UBEs > 2 minutes simulate Payroll, Sales Order, night only jobs. The UBE workload generates large numbers of PDF files reports and log files. The UBE Queues are categorized as the QBATCHD, a single threaded queue for large and medium UBEs, and the QPROCESS queue for short UBEs run concurrently. Oracle's UBE process performance metric is Number of Maximum Concurrent UBE processes at transaction rate, UBEs/minute. Key Points and Best Practices Two JD Edwards EnterpriseOne Application Servers, two Oracle WebLogic Servers 11g Release 1 coupled with two Oracle Web Tier HTTP server instances and one Oracle Database 11g Release 2 database on a single SPARC T4-2 server were hosted in separate Oracle Solaris Containers bound to four processor sets to demonstrate consolidation of multiple applications, web servers and the database with best resource utilizations. Interrupt fencing was configured on all Oracle Solaris Containers to channel the interrupts to processors other than the processor sets used for the JD Edwards Application server, Oracle WebLogic servers and the database server. A Oracle WebLogic vertical cluster was configured on each WebServer Container with twelve managed instances each to load balance users' requests and to provide the infrastructure that enables scaling to high number of users with ease of deployment and high availability. The database log writer was run in the real time RT class and bound to a processor set. The database redo logs were configured on the raw disk partitions. The Oracle Solaris Container running the Enterprise Application server completed 61 Short UBEs, 4 Long UBEs concurrently as the mixed size batch workload. The mixed size UBEs ran concurrently from the Enterprise Application server with the 8,000 online users driven by the LoadRunner. See Also SPARC T4-2 Server oracle.com OTN JD Edwards EnterpriseOne oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Oracle Fusion Middleware oracle.com OTN Disclosure Statement Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 09/30/2012.

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  • Unleash the Power of Cryptography on SPARC T4

    - by B.Koch
    by Rob Ludeman Oracle’s SPARC T4 systems are architected to deliver enhanced value for customer via the inclusion of many integrated features.  One of the best examples of this approach is demonstrated in the on-chip cryptographic support that delivers wire speed encryption capabilities without any impact to application performance.  The Evolution of SPARC Encryption SPARC T-Series systems have a long history of providing this capability, dating back to the release of the first T2000 systems that featured support for on-chip RSA encryption directly in the UltraSPARC T1 processor.  Successive generations have built on this approach by support for additional encryption ciphers that are tightly coupled with the Oracle Solaris 10 and Solaris 11 encryption framework.  While earlier versions of this technology were implemented using co-processors, the SPARC T4 was redesigned with new crypto instructions to eliminate some of the performance overhead associated with the former approach, resulting in much higher performance for encrypted workloads. The Superiority of the SPARC T4 Approach to Crypto As companies continue to engage in more and more e-commerce, the need to provide greater degrees of security for these transactions is more critical than ever before.  Traditional methods of securing data in transit by applications have a number of drawbacks that are addressed by the SPARC T4 cryptographic approach. 1. Performance degradation – cryptography is highly compute intensive and therefore, there is a significant cost when using other architectures without embedded crypto functionality.  This performance penalty impacts the entire system, slowing down performance of web servers (SSL), for example, and potentially bogging down the speed of other business applications.  The SPARC T4 processor enables customers to deliver high levels of security to internal and external customers while not incurring an impact to overall SLAs in their IT environment. 2. Added cost – one of the methods to avoid performance degradation is the addition of add-in cryptographic accelerator cards or external offload engines in other systems.  While these solutions provide a brute force mechanism to avoid the problem of slower system performance, it usually comes at an added cost.  Customers looking to encrypt datacenter traffic without the overhead and expenditure of extra hardware can rely on SPARC T4 systems to deliver the performance necessary without the need to purchase other hardware or add-on cards. 3. Higher complexity – the addition of cryptographic cards or leveraging load balancers to perform encryption tasks results in added complexity from a management standpoint.  With SPARC T4, encryption keys and the framework built into Solaris 10 and 11 means that administrators generally don’t need to spend extra cycles determining how to perform cryptographic functions.  In fact, many of the instructions are built-in and require no user intervention to be utilized.  For example, For OpenSSL on Solaris 11, SPARC T4 crypto is available directly with a new built-in OpenSSL 1.0 engine, called the "t4 engine."  For a deeper technical dive into the new instructions included in SPARC T4, consult Dan Anderson’s blog. Conclusion In summary, SPARC T4 systems offer customers much more value for applications than just increased performance. The integration of key virtualization technologies, embedded encryption, and a true Enterprise Operating System, Oracle Solaris, provides direct business benefits that supersedes the commodity approach to data center computing.   SPARC T4 removes the roadblocks to secure computing by offering integrated crypto accelerators that can save IT organizations in operating cost while delivering higher levels of performance and meeting objectives around compliance. For more on the SPARC T4 family of products, go to here.

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  • Real Excel Templates 1.5

    - by Tim Dexter
    Not the next installment quite yet, just an update from what I knew yesterday. Right after I posted the Real Excel Templates I. Mike from the PM team got in touch to say he and Shirley had just had a meeting with a customer about the Excel Templates and all the fab features. He included BIPs extended functions, data pre-processing, sub templates and other functionality which was great new news. One caveat, much of the really new stuff, is not quite out in the wild yet. Will let you know as soon as I know more. Shirley and I shared a conversation around being able to re-group data in the templates. It's one of the most powerful features of the RTF template. Providing the ultimate flexibility in layouts. As I wrote yesterday, you need hierarchical data for Excel templates. I stand corrected, 'Of course you can do that in Excel, here's an example' said Shirley 'Very cunning Shirley, very cunning' says I. You can basically use the hidden sheet to re-group the data using native XSL. I'll cover the 'how' later. As you can see Excel templates are the new 'black' with lots of attention and more importantly development cycles to take them forward. Looks like we are going to have a great weekend weather wise here in Colorado. The yard work and pond are beckoning. Maybe the trout will be rising and I can give my rusty fly casting skills a run for their money. I need some stupid fish thou :0) See ya'll next week!

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  • how to "think in templates", i.e. how to know that a problem can be solved using templates and how to adapt to it?

    - by sap
    I decided to improve my knowledge of template meta-programming, i know the syntax and rules and been playing with counteless examples from online resources. i understand how powerfull templates can be and how much compile time optimization they can provide but i still cant "think in templates", that is, i cant seem to know by myself if a certain problem could best be solved with templates (instead of something else) and if it can, how to adapt that problem to templates. so what im asking is, is there some kind of online resource or maybe book that teaches how to identify problems that could best be solved with templates and how to adapt that problem. basically i want to learn to "think in templates". already asked on stackoverflow but once again people just redirected me to resources on how to use templates, when im really asking is how to know when to use template meta-programming and how to adapt that problem to templates. thanks in advance.

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