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• Is JSF really ready to deliver high performance web applications?

  - by aklin81

  I have heard a lot of good about JSF but as far as I know people also had lots of serious complains with this technology in the past, not aware of how much the situation has improved. We are considering JSF as a probable technology for a social network project. But we are not aware of the performance scores of JSF neither we could really come across any existing high performance website that had been using JSF. People complain about its performance scalability issues. We are still not very sure if we are doing the right thing by choosing jsf, and thus would like to hear from you all about this and take your inputs into consideration. Is it possible to configure JSF to satisfy the high performance needs of social networking service ? Also till what extent is it possible to survive with the current problems in JSF.

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• Romanian parter Omnilogic Delivers “No Limits” Scalability, Performance, Security, and Affordability through Next-Generation, Enterprise-Grade Engineered Systems

  - by swalker

  Omnilogic SRL is a leading technology and information systems provider in Romania and central and Eastern Europe. An Oracle Value-Added Distributor Partner, Omnilogic resells Oracle software, hardware, and engineered systems to Oracle Partner Network members and provides specialized training, support, and testing facilities. Independent software vendors (ISVs) also use Omnilogic’s demonstration and testing facilities to upgrade the performance and efficiency of their solutions and those of their customers by migrating them from competitor technologies to Oracle platforms. Omnilogic also has a dedicated offering for ISV solutions, based on Oracle technology in a hosting service provider model. Omnilogic wanted to help Oracle Partners and ISVs migrate solutions to Oracle Exadata and sell Oracle Exadata to end-customers. It installed Oracle Exadata Database Machine X2-2 Quarter Rack at its data center to create a demonstration and testing environment. Demonstrations proved that Oracle Exadata achieved processing speeds up to 100 times faster than competitor systems, cut typical back-up times from 6 hours to 20 minutes, and stored 10 times more data. Oracle Partners and ISVs learned that migrating solutions to Oracle Exadata’s preconfigured, pre-integrated hardware and software can be completed rapidly, at low cost, without business disruption, and with reduced ongoing operating costs. Challenges A word from Omnilogic “Oracle Exadata is the new killer application—the smartest solution on the market. There is no competition.” – Sorin Dragomir, Chief Operating Officer, Omnilogic SRL Enable Oracle Partners in Romania and central and eastern Europe to achieve Oracle Exadata Ready status by providing facilities to test and optimize existing applications and build real-life proofs of concept (POCs) for new solutions on Oracle Exadata Database Machine Provide technical support and demonstration facilities for ISVs migrating their customers’ solutions from competitor technologies to Oracle Exadata to maximize performance, scalability, and security; optimize hardware and datacenter space; cut maintenance costs; and improve return on investment Demonstrate power of Oracle Exadata’s high-performance, high-capacity engineered systems for customer-facing businesses, such as government organizations, telecommunications, banking and insurance, and utility companies, which typically require continuous availability to support very large data volumes Showcase Oracle Exadata’s unchallenged online transaction processing (OLTP) capabilities that cut application run times to provide unrivalled query turnaround and user response speeds while significantly reducing back-up times and eliminating risk of unplanned outages Capitalize on providing a world-class training and demonstration environment for Oracle Exadata to accelerate sales with Oracle Partners Solutions Created a testing environment to enable Oracle Partners and ISVs to test their own solutions and those of their customers on Oracle Exadata running on Oracle Enterprise Linux or Oracle Solaris Express to benchmark performance prior to migration Leveraged expertise on Oracle Exadata to offer Oracle Exadata training, migration, support seminars and to showcase live demonstrations for Oracle Partners Proved how Oracle Exadata’s pre-engineered systems, that come assembled, configured, and ready to run, reduce deployment time and cost, minimize risk, and help customers achieve the full performance potential immediately after go live Increased processing speeds 10-fold and with zero data loss for a telecommunications provider’s client-facing customer relationship management solution Achieved performance improvements of between 6 and 100 times faster for financial and utility company applications currently running on IBM, Microsoft, or SAP HANA platforms Showed how daily closure procedures carried out overnight by banks, insurance companies, and other financial institutions to analyze each day’s business, can typically be cut from around six hours to 20 minutes, some 18 times faster, when running on Oracle Exadata Simulated concurrent back-ups while running applications under normal working conditions to prove that Oracle Exadata-based solutions can be backed up during business hours without causing bottlenecks or impacting the end-user experience Demonstrated that Oracle Exadata’s built-in analytics, data mining and OLTP capabilities make it the highest-performance, lowest-cost choice for large data warehousing operations Showed how Oracle Exadata’s columnar compression and intelligent storage architecture allows 10 times more data to be stored than on competitor platforms Demonstrated how Oracle Exadata cuts hardware requirements significantly by consolidating workloads on to fewer servers which delivers greater power efficiency and lower operating costs that competing systems from IBM and other manufacturers Proved to ISVs that migrating solutions to Oracle Exadata’s preconfigured, pre-integrated hardware and software can be completed rapidly, at low cost, and with minimal business disruption Demonstrated how storage servers, database servers, and network switches can be added incrementally and inexpensively to the Oracle Exadata platform to support business expansion On track to grow revenues by 10% in year one and by 15% annually thereafter through increased business generated from Oracle Partners and ISVs

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• Mongodb performance on Windows

  - by Chris

  I've been researching nosql options available for .NET lately and MongoDB is emerging as a clear winner in terms of availability and support, so tonight I decided to give it a go. I downloaded version 1.2.4 (Windows x64 binary) from the mongodb site and ran it with the following options: C:\mongodb\bin>mkdir data C:\mongodb\bin>mongod -dbpath ./data --cpu --quiet I then loaded up the latest mongodb-csharp driver from http://github.com/samus/mongodb-csharp and immediately ran the benchmark program. Having heard about how "amazingly fast" MongoDB is, I was rather shocked at the poor benchmark performance. Starting Tests encode (small).........................................320000 00:00:00.0156250 encode (medium)........................................80000 00:00:00.0625000 encode (large).........................................1818 00:00:02.7500000 decode (small).........................................320000 00:00:00.0156250 decode (medium)........................................160000 00:00:00.0312500 decode (large).........................................2370 00:00:02.1093750 insert (small, no index)...............................2176 00:00:02.2968750 insert (medium, no index)..............................2269 00:00:02.2031250 insert (large, no index)...............................778 00:00:06.4218750 insert (small, indexed)................................2051 00:00:02.4375000 insert (medium, indexed)...............................2133 00:00:02.3437500 insert (large, indexed)................................835 00:00:05.9843750 batch insert (small, no index).........................53333 00:00:00.0937500 batch insert (medium, no index)........................26666 00:00:00.1875000 batch insert (large, no index).........................1114 00:00:04.4843750 find_one (small, no index).............................350 00:00:14.2812500 find_one (medium, no index)............................204 00:00:24.4687500 find_one (large, no index).............................135 00:00:37.0156250 find_one (small, indexed)..............................352 00:00:14.1718750 find_one (medium, indexed).............................184 00:00:27.0937500 find_one (large, indexed)..............................128 00:00:38.9062500 find (small, no index).................................516 00:00:09.6718750 find (medium, no index)................................316 00:00:15.7812500 find (large, no index).................................216 00:00:23.0468750 find (small, indexed)..................................532 00:00:09.3906250 find (medium, indexed).................................346 00:00:14.4375000 find (large, indexed)..................................212 00:00:23.5468750 find range (small, indexed)............................440 00:00:11.3593750 find range (medium, indexed)...........................294 00:00:16.9531250 find range (large, indexed)............................199 00:00:25.0625000 Press any key to continue... For starters, I can get better non-batch insert performance from SQL Server Express. What really struck me, however, was the slow performance of the find_nnnn queries. Why is retrieving data from MongoDB so slow? What am I missing? Edit: This was all on the local machine, no network latency or anything. MongoDB's CPU usage ran at about 75% the entire time the test was running. Edit 2: Also, I ran a trace on the benchmark program and confirmed that 50% of the CPU time spent was waiting for MongoDB to return data, so it's not a performance issue with the C# driver.

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• Performance Optimization &ndash; It Is Faster When You Can Measure It

  - by Alois Kraus

  Performance optimization in bigger systems is hard because the measured numbers can vary greatly depending on the measurement method of your choice. To measure execution timing of specific methods in your application you usually use Time Measurement Method Potential Pitfalls Stopwatch Most accurate method on recent processors. Internally it uses the RDTSC instruction. Since the counter is processor specific you can get greatly different values when your thread is scheduled to another core or the core goes into a power saving mode. But things do change luckily: Intel's Designer's vol3b, section 16.11.1 "16.11.1 Invariant TSC The time stamp counter in newer processors may support an enhancement, referred to as invariant TSC. Processor's support for invariant TSC is indicated by CPUID.80000007H:EDX[8]. The invariant TSC will run at a constant rate in all ACPI P-, C-. and T-states. This is the architectural behavior moving forward. On processors with invariant TSC support, the OS may use the TSC for wall clock timer services (instead of ACPI or HPET timers). TSC reads are much more efficient and do not incur the overhead associated with a ring transition or access to a platform resource." DateTime.Now Good but it has only a resolution of 16ms which can be not enough if you want more accuracy.   Reporting Method Potential Pitfalls Console.WriteLine Ok if not called too often. Debug.Print Are you really measuring performance with Debug Builds? Shame on you. Trace.WriteLine Better but you need to plug in some good output listener like a trace file. But be aware that the first time you call this method it will read your app.config and deserialize your system.diagnostics section which does also take time.   In general it is a good idea to use some tracing library which does measure the timing for you and you only need to decorate some methods with tracing so you can later verify if something has changed for the better or worse. In my previous article I did compare measuring performance with quantum mechanics. This analogy does work surprising well. When you measure a quantum system there is a lower limit how accurately you can measure something. The Heisenberg uncertainty relation does tell us that you cannot measure of a quantum system the impulse and location of a particle at the same time with infinite accuracy. For programmers the two variables are execution time and memory allocations. If you try to measure the timings of all methods in your application you will need to store them somewhere. The fastest storage space besides the CPU cache is the memory. But if your timing values do consume all available memory there is no memory left for the actual application to run. On the other hand if you try to record all memory allocations of your application you will also need to store the data somewhere. This will cost you memory and execution time. These constraints are always there and regardless how good the marketing of tool vendors for performance and memory profilers are: Any measurement will disturb the system in a non predictable way. Commercial tool vendors will tell you they do calculate this overhead and subtract it from the measured values to give you the most accurate values but in reality it is not entirely true. After falling into the trap to trust the profiler timings several times I have got into the habit to Measure with a profiler to get an idea where potential bottlenecks are. Measure again with tracing only the specific methods to check if this method is really worth optimizing. Optimize it Measure again. Be surprised that your optimization has made things worse. Think harder Implement something that really works. Measure again Finished! - Or look for the next bottleneck. Recently I have looked into issues with serialization performance. For serialization DataContractSerializer was used and I was not sure if XML is really the most optimal wire format. After looking around I have found protobuf-net which uses Googles Protocol Buffer format which is a compact binary serialization format. What is good for Google should be good for us. A small sample app to check out performance was a matter of minutes: using ProtoBuf; using System; using System.Diagnostics; using System.IO; using System.Reflection; using System.Runtime.Serialization; [DataContract, Serializable] class Data { [DataMember(Order=1)] public int IntValue { get; set; } [DataMember(Order = 2)] public string StringValue { get; set; } [DataMember(Order = 3)] public bool IsActivated { get; set; } [DataMember(Order = 4)] public BindingFlags Flags { get; set; } } class Program { static MemoryStream _Stream = new MemoryStream(); static MemoryStream Stream { get { _Stream.Position = 0; _Stream.SetLength(0); return _Stream; } } static void Main(string[] args) { DataContractSerializer ser = new DataContractSerializer(typeof(Data)); Data data = new Data { IntValue = 100, IsActivated = true, StringValue = "Hi this is a small string value to check if serialization does work as expected" }; var sw = Stopwatch.StartNew(); int Runs = 1000 * 1000; for (int i = 0; i < Runs; i++) { //ser.WriteObject(Stream, data); Serializer.Serialize<Data>(Stream, data); } sw.Stop(); Console.WriteLine("Did take {0:N0}ms for {1:N0} objects", sw.Elapsed.TotalMilliseconds, Runs); Console.ReadLine(); } } The results are indeed promising: Serializer Time in ms N objects protobuf-net   807 1000000 DataContract 4402 1000000 Nearly a factor 5 faster and a much more compact wire format. Lets use it! After switching over to protbuf-net the transfered wire data has dropped by a factor two (good) and the performance has worsened by nearly a factor two. How is that possible? We have measured it? Protobuf-net is much faster! As it turns out protobuf-net is faster but it has a cost: For the first time a type is de/serialized it does use some very smart code-gen which does not come for free. Lets try to measure this one by setting of our performance test app the Runs value not to one million but to 1. Serializer Time in ms N objects protobuf-net 85 1 DataContract 24 1 The code-gen overhead is significant and can take up to 200ms for more complex types. The break even point where the code-gen cost is amortized by its faster serialization performance is (assuming small objects) somewhere between 20.000-40.000 serialized objects. As it turned out my specific scenario involved about 100 types and 1000 serializations in total. That explains why the good old DataContractSerializer is not so easy to take out of business. The final approach I ended up was to reduce the number of types and to serialize primitive types via BinaryWriter directly which turned out to be a pretty good alternative. It sounded good until I measured again and found that my optimizations so far do not help much. After looking more deeper at the profiling data I did found that one of the 1000 calls did take 50% of the time. So how do I find out which call it was? Normal profilers do fail short at this discipline. A (totally undeserved) relatively unknown profiler is SpeedTrace which does unlike normal profilers create traces of your applications by instrumenting your IL code at runtime. This way you can look at the full call stack of the one slow serializer call to find out if this stack was something special. Unfortunately the call stack showed nothing special. But luckily I have my own tracing as well and I could see that the slow serializer call did happen during the serialization of a bool value. When you encounter after much analysis something unreasonable you cannot explain it then the chances are good that your thread was suspended by the garbage collector. If there is a problem with excessive GCs remains to be investigated but so far the serialization performance seems to be mostly ok.  When you do profile a complex system with many interconnected processes you can never be sure that the timings you just did measure are accurate at all. Some process might be hitting the disc slowing things down for all other processes for some seconds as well. There is a big difference between warm and cold startup. If you restart all processes you can basically forget the first run because of the OS disc cache, JIT and GCs make the measured timings very flexible. When you are in need of a random number generator you should measure cold startup times of a sufficiently complex system. After the first run you can try again getting different and much lower numbers. Now try again at least two times to get some feeling how stable the numbers are. Oh and try to do the same thing the next day. It might be that the bottleneck you found yesterday is gone today. Thanks to GC and other random stuff it can become pretty hard to find stuff worth optimizing if no big bottlenecks except bloatloads of code are left anymore. When I have found a spot worth optimizing I do make the code changes and do measure again to check if something has changed. If it has got slower and I am certain that my change should have made it faster I can blame the GC again. The thing is that if you optimize stuff and you allocate less objects the GC times will shift to some other location. If you are unlucky it will make your faster working code slower because you see now GCs at times where none were before. This is where the stuff does get really tricky. A safe escape hatch is to create a repro of the slow code in an isolated application so you can change things fast in a reliable manner. Then the normal profilers do also start working again. As Vance Morrison does point out it is much more complex to profile a system against the wall clock compared to optimize for CPU time. The reason is that for wall clock time analysis you need to understand how your system does work and which threads (if you have not one but perhaps 20) are causing a visible delay to the end user and which threads can wait a long time without affecting the user experience at all. Next time: Commercial profiler shootout.

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• LVM2 vs MDADM performance

  - by archer

  I've used MDADM + LVM2 on many boxes for quite a while. MDADM was serving for both RAID0 and RAID1 arrays, while LVM2 where used for logical volumes on top of MDADM. Recently I've found that LVM2 could be used w/o MDADM (thus minus one layer, as the result - less overhead) for both mirroring and stripping. However, some guys claims that READ PERFORMANCE on LVM2 for mirrored array is not that fast as for LVM2 (linear) on top of MDADM (RAID1) as LVM2 does not read from 2+ devices at a time, but use 2nd and higher devices in case of 1st device failure. MDADM reads from 2 devices at a time (even in mirrored mode). Who could confirm that?

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• Tweaking Firefox for Performance

  - by Simon Sheehan

  As an avid Firefox user since it began, I've been looking to make some under the hood changes to it, in order to optimize it for speed and performance. I'd also like to limit my RAM usage with it. Are there any settings that can help this? What can be changed in about:config that affects this? I'd also like to know if themes or anything really boost RAM usage, as they are generally very small files to download. Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:7.0a1) Gecko/20110630 Firefox/7.0a1

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• How to monitor CPU usage and performance on a Hyper-V server with several VM's

  - by Bjørn

  Hello, I have a server that is running Windows 2008 64 bit Hyper-V, with 8 gigs of RAM and Intel Xeon X3440 @ 2.53 Ghz, which gives me 8 logical cores in the performance monitor on the host system. I have set up three Virtual Machines, all running Windows 2008 32 bit. Build server, running Team City Staging server SQL Server, running SQL Server 2005 I have some troubles with the setup in that the host monitor remains responsive at all times, even though the VM's are seemingly working at 100% cpu and are very sluggish and unresponsive. (I have asked a separate question about that.) So the question here is: What is the best way to monitor how the physical CPU's are actually utilized? The reason I am asking is that I am being told that i cannot reliably use the task manager to monitor CPU usage in a VM.

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• performance counter

  - by Abruzzo Forte e Gentile

  Hi All I created a performance counter for my C# application. Its type is NumberOfItems32. I don't know why but the Performance Monitor is displaying me on the y-axis only as maximum value only 100 when my counter is much more bigger than this for sure. Do you know if this is the correct behavior or am I doing something wrong? Thanks all AFG

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• CPU & Memory Usage Log & Performance

  - by wittythotha

  I want to have an idea of the amount of CPU and memory that is being used. I have a website hosted using IIS, and have clients connecting to it. I want to find out the amount of load that the CPU, RAM and the network has when multiple clients connect. I tried out using tools like Fiddler, the inbuilt Resource Manager, and also some other applications I found on the internet. I just want to keep track of all these data in a file, so I can plot out a graph and find out how the CPU, etc. is performing. I read a few other posts, but didn't find anything that solves the problem. Is there good CPU / Memory Logging tool available, just to plot a graph of the usage, etc.? EDIT : I want to know of some tool that can save the performance details in a log file, so that I can use it to plot a graph, etc.

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• POI performance

  - by The Machine

  I am using POI in my J2EE web application to generate a workbook. However, i find that POI takes around 3 mins to create a workbook with 25K rows(with around 15 columns each). Is this a POI performance issue , or is it justified to take that much of time? Are there other APIs known for better performance ?

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• performance of vmware-machine on different computers

  - by bxshi

  I'm working on a filesystem improving project, and found a paper says the cheating on benchmark, and it gives a solution that use VMs could help others to reproduce our result. And the question is, if I have made a specific vmware virtual machine, will it runs the same at different computer and platform? For example, I have a virtual machine which is 1G RAM, 4G HD and 2G one-core CPU. Will that runs the same at a qual-core 3G CPU and a 2.4G P4? What if the computer have 4G RAM? Will vmware use some buffer mechanism to improve performance? If that's true, does it means the VM runs on a 2G RAM host will slower than on a 4G host? Hope you can help me on that, or just told me where could I find the answer.

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• NFS performance troubleshooting

  - by aix

  I am troubleshooting NFS performance issues on Linux, and I'm looking at the following nfsiostat output: host:/path mounted on /path: op/s rpc bklog 96.75 0.01 read: ops/s kB/s kB/op retrans avg RTT (ms) avg exe (ms) 86.561 1408.294 16.269 0 (0.0%) 34.595 89.688 write: ops/s kB/s kB/op retrans avg RTT (ms) avg exe (ms) 10.113 326.282 32.265 0 (0.0%) 19.688 72446.246 What exactly is the meaning of avg RTT (ms) and avg exe (ms)? avg exe for writes is 72 seconds(!) -- would you say this is abnormal and, if so, how do I go about troubleshooting this further? I'm using NFS over TCP. Both the client and the server are on the same GigE LAN.

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• Strategies for very fast delivery of webpages.

  - by Cherian

  I run a website Cucumbertown with an initial pay load of nearly 9KB zipped. All my js is delayed loaded with requirejs and modernizer is the only exception. Now all my webpages are Nginx cached and only 10-15% hits go to the backend proxy. And the cache is invalidated by logged in users as proxy_cache_bypass. So for an anonymous user its nearly always a cache hit. I have some basic OS tuning with default via ip dev eth0 initcwnd 15 net.ipv4.tcp_slow_start_after_idle 0 Despite an all cache & large initcwnd my pages still take 2.5 – 3 seconds. I have a yslow score of And page speed at Are there strategies that can help deliver webpages even faster than this? Deliver pages at 1+ second time for 10KB payload? Notes: My servers run of a fairly good data center from Linode at Fremont.

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• Slow Network Performance with Windows Server 2008 SP1

  - by Axeva

  I recently installed Service Pack 1 for Windows Server 2008. Since that time, network performance has been awful. Both Windows 7 and Mac Snow Leopard clients have seen miserable speeds when trying to read or write to the server. This is the exact update: Windows Server 2008 R2 Service Pack 1 x64 Edition (KB976932) It's a very simple file server setup. No Domain or Active Directory. Essentially just shared folders. It's Windows Web Server that I'm running. Are there any settings I can tweak? Should I roll back the update (doesn't seem wise)? Update: I've turned off the Power Management for the Network Adapter. That may help. If it doesn't have to be powered on at the start of a request, it should speed things up. Or so I would assume.

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• Max Files for a Directory in Linux File System, Best Performance

  - by ngkong

  how many files in a diretory will be decrease server performance? I have a website that contain hundreds thousand of images ( a million in separated directory). I wonder if it will effect the performance. server detail: centos, apache, php 5

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• MySQL Linked Server and SQL Server 2008 Express Performance

  - by Jeffrey

  Hi All, I am currently trying to setup a MySQL Linked Server via SQL Server 2008 Express. I have tried two methods, creating a DSN using the mySQL 5.1 ODBC driver, and using Cherry Software OLE DB Driver as well. The method that I prefer would be using the ODBC driver, but both run horrendously slow (doing one simple join takes about 5 min). Is there any way I can get better performance? We are trying to cross query between multiple mySQL databases on different servers, and this seems to be method we think would work well. Any comments, suggestions, etc... would be greatly appreciated. Regards, Jeffrey

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• Performance required to improve Windows Experience Index?

  - by Ian Boyd

  Is there a guide on the metrics required to obtain a certain Windows Experience Index? A Microsoft guy said in January 2009: On the matter of transparency, it is indeed our plan to disclose in great detail how the scores are calculated, what the tests attempt to measure, why, and how they map to realistic scenarios and usage patterns. Has that amount of transparency happened? Is there a technet article somewhere? If my score was limited by my Memory subscore of 5.9. A nieve person would suggest: Buy a faster RAM Which is wrong of course. From the Windows help: If your computer has a 64-bit central processing unit (CPU) and 4 gigabytes (GB) or less random access memory (RAM), then the Memory (RAM) subscore for your computer will have a maximum of 5.9. You can buy the fastest, overclocked, liquid-cooled, DDR5 RAM on the planet; you'll still have a maximum Memory subscore of 5.9. So in general the knee-jerk advice "buy better stuff" is not helpful. What i am looking for is attributes required to achieve a certain score, or move beyond a current limitation. The information i've been able to compile so far, chiefly from 3 Windows blog entries, and an article: Memory subscore Score Conditions ======= ================================ 1.0 < 256 MB 2.0 < 500 MB 2.9 <= 512 MB 3.5 < 704 MB 3.9 < 944 MB 4.5 <= 1.5 GB 5.9 < 4.0GB-64MB on a 64-bit OS Windows Vista highest score 7.9 Windows 7 highest score Graphics Subscore Score Conditions ======= ====================== 1.0 doesn't support DX9 1.9 doesn't support WDDM 4.9 does not support Pixel Shader 3.0 5.9 doesn't support DX10 or WDDM1.1 Windows Vista highest score 7.9 Windows 7 highest score Gaming graphics subscore Score Result ======= ============================= 1.0 doesn't support D3D 2.0 supports D3D9, DX9 and WDDM 5.9 doesn't support DX10 or WDDM1.1 Windows Vista highest score 6.0-6.9 good framerates (e.g. 40-50fps) at normal resoltuions (e.g. 1280x1024) 7.0-7.9 even higher framerates at even higher resolutions 7.9 Windows 7 highest score Processor subscore Score Conditions ======= ========================================================================== 5.9 Windows Vista highest score 6.0-6.9 many quad core processors will be able to score in the high 6 low 7 ranges 7.0+ many quad core processors will be able to score in the high 6 low 7 ranges 7.9 8-core systems will be able to approach 8.9 Windows 7 highest score Primary hard disk subscore (note) Score Conditions ======= ======================================== 1.9 Limit for pathological drives that stop responding when pending writes 2.0 Limit for pathological drives that stop responding when pending writes 2.9 Limit for pathological drives that stop responding when pending writes 3.0 Limit for pathological drives that stop responding when pending writes 5.9 highest you're likely to see without SSD Windows Vista highest score 7.9 Windows 7 highest score Bonus Chatter You can find your WEI detailed test results in: C:\Windows\Performance\WinSAT\DataStore e.g. 2011-11-06 01.00.19.482 Disk.Assessment (Recent).WinSAT.xml <WinSAT> <WinSPR> <DiskScore>5.9</DiskScore> </WinSPR> <Metrics> <DiskMetrics> <AvgThroughput units="MB/s" score="6.4" ioSize="65536" kind="Sequential Read">89.95188</AvgThroughput> <AvgThroughput units="MB/s" score="4.0" ioSize="16384" kind="Random Read">1.58000</AvgThroughput> <Responsiveness Reason="UnableToAssess" Kind="Cap">TRUE</Responsiveness> </DiskMetrics> </Metrics> </WinSAT> Pre-emptive snarky comment: "WEI is useless, it has no relation to reality" Fine, how do i increase my hard-drive's random I/O throughput? Update - Amount of memory limits rating Some people don't believe Microsoft's statement that having less than 4GB of RAM on a 64-bit edition of Windows doesn't limit the rating to 5.9: And from xxx.Formal.Assessment (Recent).WinSAT.xml: <WinSPR> <LimitsApplied> <MemoryScore> <LimitApplied Friendly="Physical memory available to the OS is less than 4.0GB-64MB on a 64-bit OS : limit mem score to 5.9" Relation="LT">4227858432</LimitApplied> </MemoryScore> </LimitsApplied> </WinSPR> References Windows Vista Team Blog: Windows Experience Index: An In-Depth Look Understand and improve your computer's performance in Windows Vista Engineering Windows 7 Blog: Engineering the Windows 7 “Windows Experience Index”

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• Why better isolation level means better performance in MS SQL Server

  - by Oleg Zhylin

  When measuring performance on my query I came up with a dependency between isolation level and elapsed time that was surprising to me READUNCOMMITTED - 409024 READCOMMITTED - 368021 REPEATABLEREAD - 358019 SERIALIZABLE - 348019 Left column is table hint, and the right column is elapsed time in microseconds (sys.dm_exec_query_stats.total_elapsed_time). Why better isolation level gives better performance? This is a development machine and no concurrency whatsoever happens. I would expect READUNCOMMITTED to be the fasted due to less locking overhead.

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• Performance considerations when mixing C++ and Objective-C in same file

  - by user333984

  I have some high-performance C++ that I need to interface with Objective-C, is there any performance penalty to just dumping this code into a .mm file that contains my Objective-C code vs. leaving this code in a separate .cpp file and extern-ing all the functions I need to call from the .mm file?

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• proxy.pac file performance optimization

  - by Tuinslak

  I reroute certain websites through a proxy with a proxy.pac file. It basically looks like this: if (shExpMatch(host, "www.youtube.com")) { return "PROXY proxy.domain.tld:8080; DIRECT" } if (shExpMatch(host, "youtube.com")) { return "PROXY proxy.domain.tld:8080; DIRECT" } At the moment about 125 sites are rerouted using this method. However, I plan on adding quite a few more domains to it, and I'm guessing it will eventually be a list of 500-1000 domains. It's important to not reroute all traffic through the proxy. What's the best way to keep this file optimized, performance-wise ? Thanks

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• Very slow disk performance on Dell PowerEdge 2950 w/ PERC 6/i running RAID 10

  - by vocoder

  I recently set up a server running Ubuntu 10.04 LTS on a Dell PowerEdge 2950 server - it has 6 500 gb 7200RPM SATA drives setup in a RAID 10 config. I am seeing extremely poor disk performance - the RAID array reports all disks are normal and using MegaCLI, it looks like the BBU is fine. hdparm -tT /dev/sda reports: Timing cached reads: 90 MB in 2.05 seconds = 43.96 MB/sec Timing buffered disk reads: 24 MB in 3.11 seconds = 7.72 MB/sec So as you can see, it takes forever to something as simple as an apt-get upgrade and even logging into the server. How do I go about troubleshooting what is causing this? I upgraded the firmware on the PERC 6i RAID controller to the latest, but didn't see any improvements.

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• SQLAuthority News – Microsoft Whitepaper – AlwaysOn Solution Guide: Offloading Read-Only Workloads to Secondary Replicas

  - by pinaldave

  SQL Server 2012 has many interesting features but the most talked feature is AlwaysOn. Performance tuning is always a hot topic. I see lots of need of the same and lots of business around it. However, many times when people talk about performance tuning they think of it as a either query tuning, performance tuning, or server tuning. All are valid points, but performance tuning expert usually understands the business workload and business logic before making suggestions. For example, if performance tuning expert analysis workload and realize that there are plenty of reports as well read only queries on the server they can for sure consider alternate options for the same. If read only data is not required real time or it can accept the data which is delayed a bit it makes sense to divide the workload. A secondary replica of the original data which can serve all the read only queries and report is a good idea in most of the cases where there is plenty of workload which is not dependent on the real time data. SQL Server 2012 has introduced the feature of AlwaysOn which can very well fit in this scenario and provide a solution in Read-Only Workloads. Microsoft has recently announced a white paper which is based on absolutely the same subject. I recommend it to read for every SQL Enthusiast who is are going to implement a solution to offload read-only workloads to secondary replicas. Download white paper AlwaysOn Solution Guide: Offloading Read-Only Workloads to Secondary Replicas Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Backup and Restore, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: AlwaysOn

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• Puppet performance compared to cfengine

  - by Andy

  I'm considering using Puppet or cfengine. Key factors are performance, and research on the internet suggests cfengine uses less memory and CPU cycles compared to puppet. However, puppet seems easier to use. I need to manage several web servers, as well as handheld tablets and machines that will only connect to some central control servers periodically. All are Linux machines. Would I be able to use either puppet or cfengine for this? And if so, does puppet still make poor use of resources? I'd like to use puppet because it seems simpler, but a lot of the articles I've found refer to cfengine 2 - is cfengine 3 easier to configure? Thanks

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• Better performance with memcached cluster or local memcaches?

  - by Nicholas Tolley Cottrell

  I have a small cluster of servers balancing a Java web app. Currently I have 3 memcached servers caching data and all web apps shares all 3 memcached instances. I often get strange slowdowns and timeouts to some of the memcacheds and I wondering if there is a good way of analyzing the performance. I am wondering whether my iptables rules (or some other system limitation) are blocking/slowing connections. I am considering reconfiguring the web apps so that they only query the memcached process on their own localhost.

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• What's the relationship between meta-circular interpreters, virtual machines and increased performance?

  - by Gomi

  I've read about meta-circular interpreters on the web (including SICP) and I've looked into the code of some implementations (such as PyPy and Narcissus). I've read quite a bit about two languages which made great use of metacircular evaluation, Lisp and Smalltalk. As far as I understood Lisp was the first self-hosting compiler and Smalltalk had the first "true" JIT implementation. One thing I've not fully understood is how can those interpreters/compilers achieve so good performance or, in other words, why is PyPy faster than CPython? Is it because of reflection? And also, my Smalltalk research led me to believe that there's a relationship between JIT, virtual machines and reflection. Virtual Machines such as the JVM and CLR allow a great deal of type introspection and I believe they make great use it in Just-in-Time (and AOT, I suppose?) compilation. But as far as I know, Virtual Machines are kind of like CPUs, in that they have a basic instruction set. Are Virtual Machines efficient because they include type and reference information, which would allow language-agnostic reflection? I ask this because many both interpreted and compiled languages are now using bytecode as a target (LLVM, Parrot, YARV, CPython) and traditional VMs like JVM and CLR have gained incredible boosts in performance. I've been told that it's about JIT, but as far as I know JIT is nothing new since Smalltalk and Sun's own Self have been doing it before Java. I don't remember VMs performing particularly well in the past, there weren't many non-academic ones outside of JVM and .NET and their performance was definitely not as good as it is now (I wish I could source this claim but I speak from personal experience). Then all of a sudden, in the late 2000s something changed and a lot of VMs started to pop up even for established languages, and with very good performance. Was something discovered about the JIT implementation that allowed pretty much every modern VM to skyrocket in performance? A paper or a book maybe?

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