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• How to squeeze the maximum performance out of Unity and GNOME 3?

  - by melvincv

  I see that I do not get good performance with the new Unity desktop, but I should say that Unity has improved a lot since the last edition Ubuntu 11.10. How to squeeze the maximum performance out of 1. Unity 2. GNOME 3 My system specs: -Processors- Intel(R) Pentium(R) Dual CPU E2180 @ 2.00GHz -Memory- Total Memory : 2049996 kB -PCI Devices- Host bridge : Intel Corporation 82G33/G31/P35/P31 Express DRAM Controller (rev 10) PCI bridge : Intel Corporation 82G33/G31/P35/P31 Express PCI Express Root Port (rev 10) (prog-if 00 [Normal decode]) VGA compatible controller : Intel Corporation 82G33/G31 Express Integrated Graphics Controller (rev 10) (prog-if 00 [VGA controller]) USB controller : Intel Corporation N10/ICH 7 Family USB UHCI Controller #1 (rev 01) (prog-if 00 [UHCI]) USB controller : Intel Corporation N10/ICH 7 Family USB UHCI Controller #2 (rev 01) (prog-if 00 [UHCI]) USB controller : Intel Corporation N10/ICH 7 Family USB UHCI Controller #3 (rev 01) (prog-if 00 [UHCI]) USB controller : Intel Corporation N10/ICH 7 Family USB UHCI Controller #4 (rev 01) (prog-if 00 [UHCI]) USB controller : Intel Corporation N10/ICH 7 Family USB2 EHCI Controller (rev 01) (prog-if 20 [EHCI]) PCI bridge : Intel Corporation 82801 PCI Bridge (rev e1) (prog-if 01 [Subtractive decode]) ISA bridge : Intel Corporation 82801GB/GR (ICH7 Family) LPC Interface Bridge (rev 01) IDE interface : Intel Corporation 82801G (ICH7 Family) IDE Controller (rev 01) (prog-if 8a [Master SecP PriP]) IDE interface : Intel Corporation N10/ICH7 Family SATA Controller [IDE mode] (rev 01) (prog-if 8f [Master SecP SecO PriP PriO]) SMBus : Intel Corporation N10/ICH 7 Family SMBus Controller (rev 01) Ethernet controller : Intel Corporation PRO/100 VE Network Connection (rev 01)

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• Premature-Optimization and Performance Anxiety

  - by James Michael Hare

  While writing my post analyzing the new .NET 4 ConcurrentDictionary class (here), I fell into one of the classic blunders that I myself always love to warn about.  After analyzing the differences of time between a Dictionary with locking versus the new ConcurrentDictionary class, I noted that the ConcurrentDictionary was faster with read-heavy multi-threaded operations.  Then, I made the classic blunder of thinking that because the original Dictionary with locking was faster for those write-heavy uses, it was the best choice for those types of tasks.  In short, I fell into the premature-optimization anti-pattern. Basically, the premature-optimization anti-pattern is when a developer is coding very early for a perceived (whether rightly-or-wrongly) performance gain and sacrificing good design and maintainability in the process.  At best, the performance gains are usually negligible and at worst, can either negatively impact performance, or can degrade maintainability so much that time to market suffers or the code becomes very fragile due to the complexity. Keep in mind the distinction above.  I'm not talking about valid performance decisions.  There are decisions one should make when designing and writing an application that are valid performance decisions.  Examples of this are knowing the best data structures for a given situation (Dictionary versus List, for example) and choosing performance algorithms (linear search vs. binary search).  But these in my mind are macro optimizations.  The error is not in deciding to use a better data structure or algorithm, the anti-pattern as stated above is when you attempt to over-optimize early on in such a way that it sacrifices maintainability. In my case, I was actually considering trading the safety and maintainability gains of the ConcurrentDictionary (no locking required) for a slight performance gain by using the Dictionary with locking.  This would have been a mistake as I would be trading maintainability (ConcurrentDictionary requires no locking which helps readability) and safety (ConcurrentDictionary is safe for iteration even while being modified and you don't risk the developer locking incorrectly) -- and I fell for it even when I knew to watch out for it.  I think in my case, and it may be true for others as well, a large part of it was due to the time I was trained as a developer.  I began college in in the 90s when C and C++ was king and hardware speed and memory were still relatively priceless commodities and not to be squandered.  In those days, using a long instead of a short could waste precious resources, and as such, we were taught to try to minimize space and favor performance.  This is why in many cases such early code-bases were very hard to maintain.  I don't know how many times I heard back then to avoid too many function calls because of the overhead -- and in fact just last year I heard a new hire in the company where I work declare that she didn't want to refactor a long method because of function call overhead.  Now back then, that may have been a valid concern, but with today's modern hardware even if you're calling a trivial method in an extremely tight loop (which chances are the JIT compiler would optimize anyway) the results of removing method calls to speed up performance are negligible for the great majority of applications.  Now, obviously, there are those coding applications where speed is absolutely king (for example drivers, computer games, operating systems) where such sacrifices may be made.  But I would strongly advice against such optimization because of it's cost.  Many folks that are performing an optimization think it's always a win-win.  That they're simply adding speed to the application, what could possibly be wrong with that?  What they don't realize is the cost of their choice.  For every piece of straight-forward code that you obfuscate with performance enhancements, you risk the introduction of bugs in the long term technical debt of the application.  It will become so fragile over time that maintenance will become a nightmare.  I've seen such applications in places I have worked.  There are times I've seen applications where the designer was so obsessed with performance that they even designed their own memory management system for their application to try to squeeze out every ounce of performance.  Unfortunately, the application stability often suffers as a result and it is very difficult for anyone other than the original designer to maintain. I've even seen this recently where I heard a C++ developer bemoaning that in VS2010 the iterators are about twice as slow as they used to be because Microsoft added range checking (probably as part of the 0x standard implementation).  To me this was almost a joke.  Twice as slow sounds bad, but it almost never as bad as you think -- especially if you're gaining safety.  The only time twice is really that much slower is when once was too slow to begin with.  Think about it.  2 minutes is slow as a response time because 1 minute is slow.  But if an iterator takes 1 microsecond to move one position and a new, safer iterator takes 2 microseconds, this is trivial!  The only way you'd ever really notice this would be in iterating a collection just for the sake of iterating (i.e. no other operations).  To my mind, the added safety makes the extra time worth it. Always favor safety and maintainability when you can.  I know it can be a hard habit to break, especially if you started out your career early or in a language such as C where they are very performance conscious.  But in reality, these type of micro-optimizations only end up hurting you in the long run. Remember the two laws of optimization.  I'm not sure where I first heard these, but they are so true: For beginners: Do not optimize. For experts: Do not optimize yet. This is so true.  If you're a beginner, resist the urge to optimize at all costs.  And if you are an expert, delay that decision.  As long as you have chosen the right data structures and algorithms for your task, your performance will probably be more than sufficient.  Chances are it will be network, database, or disk hits that will be your slow-down, not your code.  As they say, 98% of your code's bottleneck is in 2% of your code so premature-optimization may add maintenance and safety debt that won't have any measurable impact.  Instead, code for maintainability and safety, and then, and only then, when you find a true bottleneck, then you should go back and optimize further.

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• SQL Server "Long running transaction" performance counter: why no workee?

  - by Sleepless

  Please explain to me the following observation: I have the following piece of T-SQL code that I run from SSMS: BEGIN TRAN SELECT COUNT (*) FROM m WHERE m.[x] = 123456 or m.[y] IN (SELECT f.x FROM f) SELECT COUNT (*) FROM m WHERE m.[x] = 123456 or m.[y] IN (SELECT f.x FROM f) COMMIT TRAN The query takes about twenty seconds to run. I have no other user queries running on the server. Under these circumstances, I would expect the performance counter "MSSQL$SQLInstanceName:Transactions\Longest Transaction Running Time" to rise constantly up to a value of 20 and then drop rapidly. Instead, it rises to around 12 within two seconds and then oscillates between 12 and 14 for the duration of the query after which it drops again. According to the MS docs, the counter measures "The length of time (in seconds) since the start of the transaction that has been active longer than any other current transaction." But apparently, it doesn't. What gives?

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• How to avoid Memory "Hard Fault/sec"

  - by Flavio Oliveira

  i've a problem on my windows 2008 server x64, and i cannot understand how can i solve it. i'm looking to Resource Monitor and see about 100 to 200 hard faults/sec. and generally the machine is slow. As i've readed a bit it is caused by a "memory Page" that is no longer available on physical memory and causes a io operations (disk) and it is a problem. The current hardware is a intel core2duo E8400 (3.0GHz) with 6GB RAM on a Windows Server Web 64-bit. Actually the machine have about 2GB Ram used what having 4Gb available to use, Why is the machine requires that high level of Disk operations? what can i do to increase the performance? Im experiencing a memory issues? what should be my starting point?

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• Why MySQL sat for 2 minutes doing nothing?

  - by Alex R

  This was a one-time thing, not reproducible... But I saved the show innodb status output. Can anybody tell what's going on here? The simple insert took almost 3 minutes to complete. | InnoDB | | ===================================== 110201 15:58:10 INNODB MONITOR OUTPUT ===================================== Per second averages calculated from the last 34 seconds ---------- SEMAPHORES ---------- OS WAIT ARRAY INFO: reservation count 11963, signal count 11766 --Thread 1824 has waited at .\btr\btr0cur.c line 443 for 118.00 seconds the sema phore: S-lock on RW-latch at 09D6453C created in file .\buf\buf0buf.c line 550 a writer (thread id 1824) has reserved it in mode wait exclusive number of readers 1, waiters flag 1 Last time read locked in file .\buf\buf0flu.c line 599 Last time write locked in file .\btr\btr0cur.c line 443 Mutex spin waits 0, rounds 527817, OS waits 7133 RW-shared spins 2532, OS waits 1226; RW-excl spins 1652, OS waits 1118 ------------ TRANSACTIONS ------------ Trx id counter 0 95830 Purge done for trx's n:o < 0 95814 undo n:o < 0 0 History list length 11 LIST OF TRANSACTIONS FOR EACH SESSION: ---TRANSACTION 0 0, not started, OS thread id 3704 MySQL thread id 551, query id 2702112 localhost 127.0.0.1 root show innodb status ---TRANSACTION 0 95829, not started, OS thread id 3132 MySQL thread id 534, query id 2702020 localhost 127.0.0.1 root ---TRANSACTION 0 95828, not started, OS thread id 3152 MySQL thread id 527, query id 2701973 localhost 127.0.0.1 root ---TRANSACTION 0 95827, ACTIVE 118 sec, OS thread id 1824 inserting, thread decl ared inside InnoDB 500 mysql tables in use 1, locked 1 1 lock struct(s), heap size 320, 0 row lock(s) MySQL thread id 526, query id 2701972 localhost 127.0.0.1 root update INSERT INTO log_searchcriteria (userid,search_criteria,date,search_type) VALUES ( NAME_CONST('userid',NULL), NAME_CONST('search_criteria',_latin1' SELECT SQL_C ALC_FOUND_ROWS idx_search.CTCX_LATITUDE, idx_search.CTCX_LONGITUDE, idx_search.b uilding_id, idx_search.LN_LIST_NUMBER, idx_search.LP_LIST_PRICE, idx_search.HSN_ ADRESS_HOUSE_NUMBER, idx_search.STR_ADDRESS_STREET, idx_search.CP_ADDRESS_COMPAS S_POINT, idx_search.UN_UNIT, idx_search.CIT_CITY, idx_search.ZP_ZIP_CODE, idx_se arch.AR_AREA_NAME, idx_search.BR_BEDROOMS, idx_search.BTH_BATHS, idx_search.ST_S TATUS, idx_search.CTCX_STYLE_TYPE, idx_s -------- FILE I/O -------- I/O thread 0 state: wait Windows aio (insert buffer thread) I/O thread 1 state: wait Windows aio (log thread) I/O thread 2 state: wait Windows aio (read thread) I/O thread 3 state: wait Windows aio (write thread) Pending normal aio reads: 0, aio writes: 1, ibuf aio reads: 0, log i/o's: 0, sync i/o's: 0 Pending flushes (fsync) log: 0; buffer pool: 0 151006 OS file reads, 120758 OS file writes, 6844 OS fsyncs 0.00 reads/s, 0 avg bytes/read, 0.00 writes/s, 0.00 fsyncs/s ------------------------------------- INSERT BUFFER AND ADAPTIVE HASH INDEX ------------------------------------- Ibuf: size 1, free list len 5, seg size 7, 24664 inserts, 24664 merged recs, 4612 merges Hash table size 553253, node heap has 629 buffer(s) 0.00 hash searches/s, 0.00 non-hash searches/s --- LOG --- Log sequence number 5 2318193115 Log flushed up to 5 2318193115 Last checkpoint at 5 2318129891 0 pending log writes, 0 pending chkp writes 3036 log i/o's done, 0.00 log i/o's/second ---------------------- BUFFER POOL AND MEMORY ---------------------- Total memory allocated 213459462; in additional pool allocated 1720192 Dictionary memory allocated 240416 Buffer pool size 8192 Free buffers 0 Database pages 7563 Modified db pages 18 Pending reads 0 Pending writes: LRU 0, flush list 18, single page 0 Pages read 150973, created 28788, written 115137 0.00 reads/s, 0.00 creates/s, 0.00 writes/s No buffer pool page gets since the last printout -------------- ROW OPERATIONS -------------- 1 queries inside InnoDB, 0 queries in queue 1 read views open inside InnoDB Main thread id 2992, state: flushing buffer pool pages Number of rows inserted 794294, updated 89203, deleted 13698, read 1453084305 0.00 inserts/s, 0.00 updates/s, 0.00 deletes/s, 0.00 reads/s ---------------------------- END OF INNODB MONITOR OUTPUT ============================ Thanks

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• SQL server peformance, virtual memory usage

  - by user45641

  Hello, I have a very large DB used mostly for analytics. The performance overall is very sluggish. I just noticed that when running the query below, the amount of virtual memory used greatly exceeds the amount of physical memory available. Currently, physical memory is 10GB (10238 MB) whereas the virtual memory returns significantly more - 8388607 MB. That seems really wrong, but I'm at a bit of a loss on how to proceed. USE [master]; GO select cpu_count , hyperthread_ratio , physical_memory_in_bytes / 1048576 as 'mem_MB' , virtual_memory_in_bytes / 1048576 as 'virtual_mem_MB' , max_workers_count , os_error_mode , os_priority_class from sys.dm_os_sys_info

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• Benchmarking Java programs

  - by stefan-ock

  For university, I perform bytecode modifications and analyze their influence on performance of Java programs. Therefore, I need Java programs---in best case used in production---and appropriate benchmarks. For instance, I already got HyperSQL and measure its performance by the benchmark program PolePosition. The Java programs running on a JVM without JIT compiler. Thanks for your help! P.S.: I cannot use programs to benchmark the performance of the JVM or of the Java language itself (such as Wide Finder).

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• Can compressing Program Files save space *and* give a significant boost to SSD performance?

  - by Christopher Galpin

  Considering solid-state disk space is still an expensive resource, compressing large folders has appeal. Thanks to VirtualStore, could Program Files be a case where it might even improve performance? Discovery In particular I have been reading: SSD and NTFS Compression Speed Increase? Does NTFS compression slow SSD/flash performance? Will somebody benchmark whole disk compression (HD,SSD) please? (may have to scroll up) The first link is particularly dreamy, but maybe head a little too far in the clouds. The third link has this sexy semi-log graph (logarithmic scale!). Quote (with notes): Using highly compressable data (IOmeter), you get at most a 30x performance increase [for reads], and at least a 49x performance DECREASE [for writes]. Assuming I interpreted and clarified that sentence correctly, this single user's benchmark has me incredibly interested. Although write performance tanks wretchedly, read performance still soars. It gave me an idea. Idea: VirtualStore It so happens that thanks to sanity saving security features introduced in Windows Vista, write access to certain folders such as Program Files is virtualized for non-administrator processes. Which means, in normal (non-elevated) usage, a program or game's attempt to write data to its install location in Program Files (which is perhaps a poor location) is redirected to %UserProfile%\AppData\Local\VirtualStore, somewhere entirely different. Thus, to my understanding, writes to Program Files should primarily only occur when installing an application. This makes compressing it not only a huge source of space gain, but also a potential candidate for performance gain. Testing The beginning of this post has me a bit timid, it suggests benchmarking NTFS compression on a whole drive is difficult because turning it off "doesn't decompress the objects". However it seems to me the compact command is perfectly capable of doing so for both drives and individual folders. Could it be only marking them for decompression the next time the OS reads from them? I need to find the answer before I begin my own testing.

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• Performance question: Inverting an array of pointers in-place vs array of values

  - by Anders

  The background for asking this question is that I am solving a linearized equation system (Ax=b), where A is a matrix (typically of dimension less than 100x100) and x and b are vectors. I am using a direct method, meaning that I first invert A, then find the solution by x=A^(-1)b. This step is repated in an iterative process until convergence. The way I'm doing it now, using a matrix library (MTL4): For every iteration I copy all coeffiecients of A (values) in to the matrix object, then invert. This the easiest and safest option. Using an array of pointers instead: For my particular case, the coefficients of A happen to be updated between each iteration. These coefficients are stored in different variables (some are arrays, some are not). Would there be a potential for performance gain if I set up A as an array containing pointers to these coefficient variables, then inverting A in-place? The nice thing about the last option is that once I have set up the pointers in A before the first iteration, I would not need to copy any values between successive iterations. The values which are pointed to in A would automatically be updated between iterations. So the performance question boils down to this, as I see it: - The matrix inversion process takes roughly the same amount of time, assuming de-referencing of pointers is non-expensive. - The array of pointers does not need the extra memory for matrix A containing values. - The array of pointers option does not have to copy all NxN values of A between each iteration. - The values that are pointed to the array of pointers option are generally NOT ordered in memory. Hopefully, all values lie relatively close in memory, but *A[0][1] is generally not next to *A[0][0] etc. Any comments to this? Will the last remark affect performance negatively, thus weighing up for the positive performance effects?

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• Performance impact: What is the optimal payload for SqlBulkCopy.WriteToServer()?

  - by Linchi Shea

  For many years, I have been using a C# program to generate the TPC-C compliant data for testing. The program relies on the SqlBulkCopy class to load the data generated by the program into the SQL Server tables. In general, the performance of this C# data loader is satisfactory. Lately however, I found myself in a situation where I needed to generate a much larger amount of data than I typically do and the data needed to be loaded within a confined time frame. So I was driven to look into the code...(read more)

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• Performance triage

  - by Dave

  Folks often ask me how to approach a suspected performance issue. My personal strategy is informed by the fact that I work on concurrency issues. (When you have a hammer everything looks like a nail, but I'll try to keep this general). A good starting point is to ask yourself if the observed performance matches your expectations. Expectations might be derived from known system performance limits, prototypes, and other software or environments that are comparable to your particular system-under-test. Some simple comparisons and microbenchmarks can be useful at this stage. It's also useful to write some very simple programs to validate some of the reported or expected system limits. Can that disk controller really tolerate and sustain 500 reads per second? To reduce the number of confounding factors it's better to try to answer that question with a very simple targeted program. And finally, nothing beats having familiarity with the technologies that underlying your particular layer. On the topic of confounding factors, as our technology stacks become deeper and less transparent, we often find our own technology working against us in some unexpected way to choke performance rather than simply running into some fundamental system limit. A good example is the warm-up time needed by just-in-time compilers in Java Virtual Machines. I won't delve too far into that particular hole except to say that it's rare to find good benchmarks and methodology for java code. Another example is power management on x86. Power management is great, but it can take a while for the CPUs to throttle up from low(er) frequencies to full throttle. And while I love "turbo" mode, it makes benchmarking applications with multiple threads a chore as you have to remember to turn it off and then back on otherwise short single-threaded runs may look abnormally fast compared to runs with higher thread counts. In general for performance characterization I disable turbo mode and fix the power governor at "performance" state. Another source of complexity is the scheduler, which I've discussed in prior blog entries. Lets say I have a running application and I want to better understand its behavior and performance. We'll presume it's warmed up, is under load, and is an execution mode representative of what we think the norm would be. It should be in steady-state, if a steady-state mode even exists. On Solaris the very first thing I'll do is take a set of "pstack" samples. Pstack briefly stops the process and walks each of the stacks, reporting symbolic information (if available) for each frame. For Java, pstack has been augmented to understand java frames, and even report inlining. A few pstack samples can provide powerful insight into what's actually going on inside the program. You'll be able to see calling patterns, which threads are blocked on what system calls or synchronization constructs, memory allocation, etc. If your code is CPU-bound then you'll get a good sense where the cycles are being spent. (I should caution that normal C/C++ inlining can diffuse an otherwise "hot" method into other methods. This is a rare instance where pstack sampling might not immediately point to the key problem). At this point you'll need to reconcile what you're seeing with pstack and your mental model of what you think the program should be doing. They're often rather different. And generally if there's a key performance issue, you'll spot it with a moderate number of samples. I'll also use OS-level observability tools to lock for the existence of bottlenecks where threads contend for locks; other situations where threads are blocked; and the distribution of threads over the system. On Solaris some good tools are mpstat and too a lesser degree, vmstat. Try running "mpstat -a 5" in one window while the application program runs concurrently. One key measure is the voluntary context switch rate "vctx" or "csw" which reflects threads descheduling themselves. It's also good to look at the user; system; and idle CPU percentages. This can give a broad but useful understanding if your threads are mostly parked or mostly running. For instance if your program makes heavy use of malloc/free, then it might be the case you're contending on the central malloc lock in the default allocator. In that case you'd see malloc calling lock in the stack traces, observe a high csw/vctx rate as threads block for the malloc lock, and your "usr" time would be less than expected. Solaris dtrace is a wonderful and invaluable performance tool as well, but in a sense you have to frame and articulate a meaningful and specific question to get a useful answer, so I tend not to use it for first-order screening of problems. It's also most effective for OS and software-level performance issues as opposed to HW-level issues. For that reason I recommend mpstat & pstack as my the 1st step in performance triage. If some other OS-level issue is evident then it's good to switch to dtrace to drill more deeply into the problem. Only after I've ruled out OS-level issues do I switch to using hardware performance counters to look for architectural impediments.

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• Disabling CPU management

  - by Tiffany Walker

  If I add the following processor.max_cstate=0 to the kernel command line for boot up, does that disable all CPU power management and throttling? I also found: http://www.experts-exchange.com/OS/Linux/Administration/A_3492-Avoiding-CPU-speed-scaling-in-modern-Linux-distributions-Running-CPU-at-full-speed-Tips.html The link talks of Change CPU governor from 'ondemand' to 'performance' for all CPUs/cores and disabling kondemand from kernel. Server is for web hosting UPDATES: 2.6.32-379.1.1.lve1.1.7.6.el6.x86_64 #1 SMP Sat Aug 4 09:56:37 EDT 2012 x86_64 x86_64 x86_64 GNU/Linux . # dmidecode 2.11 SMBIOS 2.6 present. 74 structures occupying 2878 bytes. Table at 0x0009F000. Handle 0x0000, DMI type 0, 24 bytes BIOS Information Vendor: American Megatrends Inc. Version: 1.0c Release Date: 05/27/2010 Address: 0xF0000 Runtime Size: 64 kB ROM Size: 4096 kB Characteristics: ISA is supported PCI is supported PNP is supported BIOS is upgradeable BIOS shadowing is allowed ESCD support is available Boot from CD is supported Selectable boot is supported BIOS ROM is socketed EDD is supported 5.25"/1.2 MB floppy services are supported (int 13h) 3.5"/720 kB floppy services are supported (int 13h) 3.5"/2.88 MB floppy services are supported (int 13h) Print screen service is supported (int 5h) 8042 keyboard services are supported (int 9h) Serial services are supported (int 14h) Printer services are supported (int 17h) CGA/mono video services are supported (int 10h) ACPI is supported USB legacy is supported LS-120 boot is supported ATAPI Zip drive boot is supported BIOS boot specification is supported Targeted content distribution is supported BIOS Revision: 8.16 Handle 0x0001, DMI type 1, 27 bytes System Information Manufacturer: Supermicro Product Name: X8SIE Version: 0123456789 Serial Number: 0123456789 UUID: 49434D53-0200-9033-2500-33902500D52C Wake-up Type: Power Switch SKU Number: To Be Filled By O.E.M. Family: To Be Filled By O.E.M. Handle 0x0002, DMI type 2, 15 bytes Base Board Information Manufacturer: Supermicro Product Name: X8SIE Version: 0123456789 Serial Number: VM11S61561 Asset Tag: To Be Filled By O.E.M. Features: Board is a hosting board Board is replaceable Location In Chassis: To Be Filled By O.E.M. Chassis Handle: 0x0003 Type: Motherboard Contained Object Handles: 0 Handle 0x0003, DMI type 3, 21 bytes Chassis Information Manufacturer: Supermicro Type: Sealed-case PC Lock: Not Present Version: 0123456789 Serial Number: 0123456789 Asset Tag: To Be Filled By O.E.M. Boot-up State: Safe Power Supply State: Safe Thermal State: Safe Security Status: None OEM Information: 0x00000000 Height: Unspecified Number Of Power Cords: 1 Contained Elements: 0

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• Very long (>300s) request processing time on Apache Server serving static content from particular IP

  - by Ron Bieber

  We are running an Apache 2.2 server for a very large web site. Over the past few months we have been having some users reporting slow response times, while others (including our resources, both on the internal network and our home networks) do not see any degradation in performance. After a ton of investigation, we finally found a "Deny from none" statement in our configuration that was causing reverse DNS lookups (which were timing out) that solved the bulk of our issues, but we still have some customers that we are seeing in the Apache logs (using %D in the log format) with request processing times of 300s for images, css, javascript and other static content. We've checked all Deny / Allow statements for reoccurrence of "none", as well as all other things we know of that would cause reverse DNS lookups (such as using "REMOTE_HOST" in rewrite rules, using %a instead of %h in our log format configuration) as well as verified that HostnameLookups is set to "Off". As an aside, we've also validated that reverse DNS lookups for folks having this problem do not time out - so I'm fairly certain DNS is not an issue in this case. I've run out of ideas. Are there any Apache configuration scenarios that someone can point me to that I might be missing that would cause request times for static content to take so long only for certain users? Thank you in advance.

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• F# performance in scientific computing

  - by aaa

  hello. I am curious as to how F# performance compares to C++ performance? I asked a similar question with regards to Java, and the impression I got was that Java is not suitable for heavy numbercrunching. I have read that F# is supposed to be more scalable and more performant, but how is this real-world performance compares to C++? specific questions about current implementation are: How well does it do floating-point? Does it allow vector instructions how friendly is it towards optimizing compilers? How big a memory foot print does it have? Does it allow fine-grained control over memory locality? does it have capacity for distributed memory processors, for example Cray? what features does it have that may be of interest to computational science where heavy number processing is involved? Are there actual scientific computing implementations that use it? Thanks

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• VS2010 + Resharper 5 performance issues

  - by Jeremy Roberts

  I have been using VS2010 with Resharper 5 for several weeks and am having a performance issue. Sometimes when typing, the cursor will lag and the keystrokes won't show instantaneously. Also, scrolling will lag at times. There is a forum thread started and JetBrains has been responding. Several people (including myself) have added their voice and uploaded some performance profiles. If anyone here has has this issue, I would encourage you to visit the thread and let JetBrains know about it. Has anyone had this problem and have a suggestion to restore performance?

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• Measuring Web Page Performance on Client vs. Server

  - by Yaakov Ellis

  I am working with a web page (ASP.net 3.5) that is very complicated and in certain circumstances has major performance issues. It uses Ajax (through the Telerik AjaxManager) for most of its functionality. I would like to be able to measure in some way the amounts of time for the following, for each request: On client submitting request to server Client-to-Server On server initializing request On server processing request Server-to-Client Client rendering, JavaScript processing I have monitored the database traffic and cannot find any obvious culprit. On the other hand, I have a suspicion that some of the Ajax interactions are causing performance issues. However, until I have a way to track the times involved, make a baseline measurement, and measure performance as I tweak, it will be hard to work on the issue. So what is the best way to measure all of these? Is there one tool that can do it? Combination of FireBug and logging inserted into different places in the page life-cycle?

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• Looking for SQL Server Performance Monitor Tools

  - by the-locster

  I may be approaching this problem from the wrong angle but what I'm thinking of is some kind of performance monitor tool for SQl server that works in a similar way to code performance tools, e.g. I;d like to see an output of how many times each stored procedure was called, average executuion time and possibly various resource usage stats such as cache/index utilisation, resultign disk access and table scans, etc. As far as I can tell the performance monitor that comes with SQL Server just logs the various calls but doesn't report he variosu stats I'm looking for. Potentially I just need a tool to analyze the log output?

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• Performance Counters Registry validation

  - by anchandra

  I have a C# application that adds some performance counters when it starts up. But if the registry HKEY_LOCAL_MACHINE-SOFTWARE-Microsoft-Windows NT-CurrentVersion-Perflib is corrupted (missing or invalid data), the operation of checking the existence of the performance counters (PerformanceCounterCategory.Exists(category) takes a really long time (around 30 secs) before finally throwing exception (InvalidOperation: Category does not exist). My question is how can i verify the validity of the registry before trying to add the performance counters (and what validity means) or if there is a way i can timeout the perf counter operations, so that it doesn't take 30 seconds to get an exception.

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• Entity Framework associations killing performance

  - by Chris

  Here is the performance test i am looking at. I have 8 different entities that are table per type. Some of the entities contain over 100 thousand rows. This particular application does several recursive calculations on the client so I think it may be best to preload the data instead of lazy loading. If there are no associations I can load the entire database in about 3 seconds. As I add associations in any way the performance starts to drastically decline. I am loading all the data the same way (just calling toList() on the entity attached to the context). I ran the test with edmx generated classes and self tracking entities and had similar results. I am sure if I were to try and deal with the associations myself, similar to how I would in a dataset, the performance problem would go away. On the other hand I am pretty sure this is not how the entity framework was intended to being used. Any thoughts or ideas?

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• Performance statistics hooks

  - by tinny

  Lets be honest, most software that developers produce has quite modest performance requirements. E.g. Systems perhaps serving 100's of requests per second, if that. But lets assume for a moment (or even dream) that you where perhaps involved in the "next big thing" (whatever that means) and you wanted to put some sort of performance statistics logging in place to help you out when all those users come flying in. Performance statistics logging, how would you approach this requirement? Perhaps you would use some sort of generic framework for this? Or roll your own solution? What would you log? How granular? Or would you not even bother putting anything in place and rather deal with this issue when it actually became an issue? It would be really interesting to hear your thoughts on this topic.

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• azure performance

  - by Dave K

  I've moved my app from a dedicated server to azure (and sql azure), and have noticed substantial performance degradation. obviously not having the database and web server on the same piece of hardware is much of it, but I'm curious what other people have found in migrating to azure, and if there is anything any of you would suggest I do to improve it. Right now I'm considering moving back to my dedicated server... So in summary, are there any rules of thumb for this, existing research (wasn't able to find much) or other pieces of advice on improving the performance of the app? has anyone else found the same to be true, and improved their site's performance in some way? it's built in C# on asp.net mvc 2. Thanks!

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• Is code clearness killing application performance?

  - by Jorge Córdoba

  As today's code is getting more complex by the minute, code needs to be designed to be maintainable - meaning easy to read, and easy to understand. That being said, I can't help but remember the programs that ran a couple of years ago such as Winamp or some games in which you needed a high performance program because your 486 100 Mhz wouldn't play mp3s with that beautiful mp3 player which consumed all of your CPU cycles. Now I run Media Player (or whatever), start playing an mp3 and it eats up a 25-30% of one of my four cores. Come on!! If a 486 can do it, how can the playback take up so much processor to do the same? I'm a developer myself, and I always used to advise: keep your code simple, don't prematurely optimize for performance. It seems that we've gone from "trying to get it to use the least amount of CPU as possible" to "if it doesn't take too much CPU is all right". So, do you think we are killing performance by ignoring optimizations?

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• Oracle, slow performance when using sub select

  - by Wyass

  I have a view that is very slow if you fetch all rows. But if I select a subset (providing an ID in the where clause) the performance is very good. I cannot hardcode the ID so I create a sub select to get the ID from another table. The sub select only returns one ID. Now the performance is very slow and it seems like Oracle is evaluating the whole view before using the where clause. Can I somehow help Oracle so SQL 2 and 3 have the same performance? I’m using Oracle 10g 1 slow select * from ci.my_slow_view 2 fast select * from ci.my_slow_view where id = 1; 3 slow select * from ci.my_slow_view where id in (select id from active_ids)

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• Apache2 benchmarks - very poor performance

  - by andrzejp

  I have two servers on which I test the configuration of apache2. The first server: 4GB of RAM, AMD Athlon (tm) 64 X2 Dual Core Processor 5600 + Apache 2.2.3, mod_php, mpm prefork: Settings: Timeout 100 KeepAlive On MaxKeepAliveRequests 150 KeepAliveTimeout 4 <IfModule Mpm_prefork_module> StartServers 7 MinSpareServers 15 MaxSpareServers 30 MaxClients 250 MaxRequestsPerChild 2000 </ IfModule> Compiled in modules: core.c mod_log_config.c mod_logio.c prefork.c http_core.c mod_so.c Second server: 8GB of RAM, Intel (R) Core (TM) i7 CPU [email protected] Apache 2.2.9, **fcgid, mpm worker, suexec** PHP scripts are running via fcgi-wrapper Settings: Timeout 100 KeepAlive On MaxKeepAliveRequests 100 KeepAliveTimeout 4 <IfModule Mpm_worker_module> StartServers 10 MaxClients 200 MinSpareThreads 25 MaxSpareThreads 75 ThreadsPerChild 25 MaxRequestsPerChild 1000 </ IfModule> Compiled in modules: core.c mod_log_config.c mod_logio.c worker.c http_core.c mod_so.c The following test results, which are very strange! New server (dynamic content - php via fcgid+suexec): Server Software: Apache/2.2.9 Server Hostname: XXXXXXXX Server Port: 80 Document Path: XXXXXXX Document Length: 179512 bytes Concurrency Level: 10 Time taken for tests: 0.26276 seconds Complete requests: 1000 Failed requests: 0 Total transferred: 179935000 bytes HTML transferred: 179512000 bytes Requests per second: 38.06 Transfer rate: 6847.88 kb/s received Connnection Times (ms) min avg max Connect: 2 4 54 Processing: 161 257 449 Total: 163 261 503 Old server (dynamic content - mod_php): Server Software: Apache/2.2.3 Server Hostname: XXXXXX Server Port: 80 Document Path: XXXXXX Document Length: 187537 bytes Concurrency Level: 10 Time taken for tests: 173.073 seconds Complete requests: 1000 Failed requests: 22 (Connect: 0, Length: 22, Exceptions: 0) Total transferred: 188003372 bytes HTML transferred: 187546372 bytes Requests per second: 5777.91 Transfer rate: 1086267.40 kb/s received Connnection Times (ms) min avg max Connect: 3 3 28 Processing: 298 1724 26615 Total: 301 1727 26643 Old server: Static content (jpg file) Server Software: Apache/2.2.3 Server Hostname: xxxxxxxxx Server Port: 80 Document Path: /images/top2.gif Document Length: 40486 bytes Concurrency Level: 100 Time taken for tests: 3.558 seconds Complete requests: 1000 Failed requests: 0 Write errors: 0 Total transferred: 40864400 bytes HTML transferred: 40557482 bytes Requests per second: 281.09 [#/sec] (mean) Time per request: 355.753 [ms] (mean) Time per request: 3.558 [ms] (mean, across all concurrent requests) Transfer rate: 11217.51 [Kbytes/sec] received Connection Times (ms) min mean[+/-sd] median max Connect: 3 11 4.5 12 23 Processing: 40 329 61.4 339 1009 Waiting: 6 282 55.2 293 737 Total: 43 340 63.0 351 1020 New server - static content (jpg file) Server Software: Apache/2.2.9 Server Hostname: XXXXX Server Port: 80 Document Path: /images/top2.gif Document Length: 40486 bytes Concurrency Level: 100 Time taken for tests: 3.571531 seconds Complete requests: 1000 Failed requests: 0 Write errors: 0 Total transferred: 41282792 bytes HTML transferred: 41030080 bytes Requests per second: 279.99 [#/sec] (mean) Time per request: 357.153 [ms] (mean) Time per request: 3.572 [ms] (mean, across all concurrent requests) Transfer rate: 11287.88 [Kbytes/sec] received Connection Times (ms) min mean[+/-sd] median max Connect: 2 63 24.8 66 119 Processing: 124 278 31.8 282 391 Waiting: 3 70 28.5 66 164 Total: 126 341 35.9 350 443 I noticed that in the apache error.log is a lot of entries: [notice] mod_fcgid: call /www/XXXXX/public_html/forum/index.php with wrapper /www/php-fcgi-scripts/XXXXXX/php-fcgi-starter What I have omitted, or do not understand? Such a difference in requests per second? Is it possible? What could be the cause?

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• openvpn TCP/UDP slow SSH/SMB performance

  - by Petr Latal

  I have question about strange behavior of my openVPN configuration on Debian lenny. I have 2 server configs (one proto tcp-server based and one proto udp based). ISP bandwidth is 7Mbit/7Mbit. When I uses proto tcp-server my download server rate is fine around 6,4 Mbit/s, but upload rate is about 3Mbit/s. When I uses proto udp, my download server rate is around 3Mbit/s and upload rate around 6,4Mbit/s. I tried to handle the MTU, MSSFIX and cipher on/off on server and client configs to synchronize rates, but without solution. Here is TCP based SERVER config: mode server tls-server port 1194 proto tcp-server dev tap0 ifconfig 11.10.15.1 255.255.255.0 ifconfig-pool 11.10.15.2 11.10.15.20 255.255.255.0 push "route 192.168.1.0 255.255.255.0" push "dhcp-option DNS 192.168.1.200" push "route-gateway 11.10.15.1" push "dhcp-option WINS 192.168.1.200" route-up /etc/openvpn/routeup.sh duplicate-cn ca /etc/openvpn/ca.crt cert /etc/openvpn/server.crt key /etc/openvpn/server.key dh /etc/openvpn/dh2048.pem log-append /var/log/openvpn.log status /var/run/vpn.status 10 user nobody group nogroup keepalive 10 120 comp-lzo verb 3 script-security 3 plugin /usr/lib/openvpn/openvpn-auth-pam.so system-auth persist-tun persist-key mssfix cipher BF-CBC Here is UDP based SERVER config: port 1194 proto udp dev tun0 local xx.xx.xx.xx server 11.10.15.0 255.255.255.0 ca /etc/openvpn/ca.crt cert /etc/openvpn/server.crt key /etc/openvpn/server.key dh /etc/openvpn/dh2048.pem log-append /var/log/openvpn.log status /var/run/vpn.status 10 user nobody group nogroup keepalive 10 120 comp-lzo verb 3 duplicate-cn script-security 3 plugin /usr/lib/openvpn/openvpn-auth-pam.so system-auth persist-tun persist-key tun-mtu 1500 mssfix 1212 client-to-client ifconfig-pool-persist ipp.txt Here is TCP/UDP based windows CLIENT config: remote xx.xx.xx.xx --socket-flags TCP_NODELAY tls-client port 1194 proto tcp-client #proto udp dev tap #dev tun pull ca ca.crt cert latis.crt key latis.key mute 0 comp-lzo adaptive verb 3 resolv-retry infinite nobind persist-key auth-user-pass auth-nocache script-security 2 mssfix cipher BF-CBC

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