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  • 10 Windows Tweaking Myths Debunked

    - by Chris Hoffman
    Windows is big, complicated, and misunderstood. You’ll still stumble across bad advice from time to time when browsing the web. These Windows tweaking, performance, and system maintenance tips are mostly just useless, but some are actively harmful. Luckily, most of these myths have been stomped out on mainstream sites and forums. However, if you start searching the web, you’ll still find websites that recommend you do these things. Erase Cache Files Regularly to Speed Things Up You can free up disk space by running an application like CCleaner, another temporary-file-cleaning utility, or even the Windows Disk Cleanup tool. In some cases, you may even see an old computer speed up when you erase a large amount of useless files. However, running CCleaner or similar utilities every day to erase your browser’s cache won’t actually speed things up. It will slow down your web browsing as your web browser is forced to redownload the files all over again, and reconstruct the cache you regularly delete. If you’ve installed CCleaner or a similar program and run it every day with the default settings, you’re actually slowing down your web browsing. Consider at least preventing the program from wiping out your web browser cache. Enable ReadyBoost to Speed Up Modern PCs Windows still prompts you to enable ReadyBoost when you insert a USB stick or memory card. On modern computers, this is completely pointless — ReadyBoost won’t actually speed up your computer if you have at least 1 GB of RAM. If you have a very old computer with a tiny amount of RAM — think 512 MB — ReadyBoost may help a bit. Otherwise, don’t bother. Open the Disk Defragmenter and Manually Defragment On Windows 98, users had to manually open the defragmentation tool and run it, ensuring no other applications were using the hard drive while it did its work. Modern versions of Windows are capable of defragmenting your file system while other programs are using it, and they automatically defragment your disks for you. If you’re still opening the Disk Defragmenter every week and clicking the Defragment button, you don’t need to do this — Windows is doing it for you unless you’ve told it not to run on a schedule. Modern computers with solid-state drives don’t have to be defragmented at all. Disable Your Pagefile to Increase Performance When Windows runs out of empty space in RAM, it swaps out data from memory to a pagefile on your hard disk. If a computer doesn’t have much memory and it’s running slow, it’s probably moving data to the pagefile or reading data from it. Some Windows geeks seem to think that the pagefile is bad for system performance and disable it completely. The argument seems to be that Windows can’t be trusted to manage a pagefile and won’t use it intelligently, so the pagefile needs to be removed. As long as you have enough RAM, it’s true that you can get by without a pagefile. However, if you do have enough RAM, Windows will only use the pagefile rarely anyway. Tests have found that disabling the pagefile offers no performance benefit. Enable CPU Cores in MSConfig Some websites claim that Windows may not be using all of your CPU cores or that you can speed up your boot time by increasing the amount of cores used during boot. They direct you to the MSConfig application, where you can indeed select an option that appears to increase the amount of cores used. In reality, Windows always uses the maximum amount of processor cores your CPU has. (Technically, only one core is used at the beginning of the boot process, but the additional cores are quickly activated.) Leave this option unchecked. It’s just a debugging option that allows you to set a maximum number of cores, so it would be useful if you wanted to force Windows to only use a single core on a multi-core system — but all it can do is restrict the amount of cores used. Clean Your Prefetch To Increase Startup Speed Windows watches the programs you run and creates .pf files in its Prefetch folder for them. The Prefetch feature works as a sort of cache — when you open an application, Windows checks the Prefetch folder, looks at the application’s .pf file (if it exists), and uses that as a guide to start preloading data that the application will use. This helps your applications start faster. Some Windows geeks have misunderstood this feature. They believe that Windows loads these files at boot, so your boot time will slow down due to Windows preloading the data specified in the .pf files. They also argue you’ll build up useless files as you uninstall programs and .pf files will be left over. In reality, Windows only loads the data in these .pf files when you launch the associated application and only stores .pf files for the 128 most recently launched programs. If you were to regularly clean out the Prefetch folder, not only would programs take longer to open because they won’t be preloaded, Windows will have to waste time recreating all the .pf files. You could also modify the PrefetchParameters setting to disable Prefetch, but there’s no reason to do that. Let Windows manage Prefetch on its own. Disable QoS To Increase Network Bandwidth Quality of Service (QoS) is a feature that allows your computer to prioritize its traffic. For example, a time-critical application like Skype could choose to use QoS and prioritize its traffic over a file-downloading program so your voice conversation would work smoothly, even while you were downloading files. Some people incorrectly believe that QoS always reserves a certain amount of bandwidth and this bandwidth is unused until you disable it. This is untrue. In reality, 100% of bandwidth is normally available to all applications unless a program chooses to use QoS. Even if a program does choose to use QoS, the reserved space will be available to other programs unless the program is actively using it. No bandwidth is ever set aside and left empty. Set DisablePagingExecutive to Make Windows Faster The DisablePagingExecutive registry setting is set to 0 by default, which allows drivers and system code to be paged to the disk. When set to 1, drivers and system code will be forced to stay resident in memory. Once again, some people believe that Windows isn’t smart enough to manage the pagefile on its own and believe that changing this option will force Windows to keep important files in memory rather than stupidly paging them out. If you have more than enough memory, changing this won’t really do anything. If you have little memory, changing this setting may force Windows to push programs you’re using to the page file rather than push unused system files there — this would slow things down. This is an option that may be helpful for debugging in some situations, not a setting to change for more performance. Process Idle Tasks to Free Memory Windows does things, such as creating scheduled system restore points, when you step away from your computer. It waits until your computer is “idle” so it won’t slow your computer and waste your time while you’re using it. Running the “Rundll32.exe advapi32.dll,ProcessIdleTasks” command forces Windows to perform all of these tasks while you’re using the computer. This is completely pointless and won’t help free memory or anything like that — all you’re doing is forcing Windows to slow your computer down while you’re using it. This command only exists so benchmarking programs can force idle tasks to run before performing benchmarks, ensuring idle tasks don’t start running and interfere with the benchmark. Delay or Disable Windows Services There’s no real reason to disable Windows services anymore. There was a time when Windows was particularly heavy and computers had little memory — think Windows Vista and those “Vista Capable” PCs Microsoft was sued over. Modern versions of Windows like Windows 7 and 8 are lighter than Windows Vista and computers have more than enough memory, so you won’t see any improvements from disabling system services included with Windows. Some people argue for not disabling services, however — they recommend setting services from “Automatic” to “Automatic (Delayed Start)”. By default, the Delayed Start option just starts services two minutes after the last “Automatic” service starts. Setting services to Delayed Start won’t really speed up your boot time, as the services will still need to start — in fact, it may lengthen the time it takes to get a usable desktop as services will still be loading two minutes after booting. Most services can load in parallel, and loading the services as early as possible will result in a better experience. The “Delayed Start” feature is primarily useful for system administrators who need to ensure a specific service starts later than another service. If you ever find a guide that recommends you set a little-known registry setting to improve performance, take a closer look — the change is probably useless. Want to actually speed up your PC? Try disabling useless startup programs that run on boot, increasing your boot time and consuming memory in the background. This is a much better tip than doing any of the above, especially considering most Windows PCs come packed to the brim with bloatware.     

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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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  • Improve your Application Performance with .NET Framework 4.0

    Nice Article on CodeGuru. This processors we use today are quite different from those of just a few years ago, as most processors today provide multiple cores and/or multiple threads. With multiple cores and/or threads we need to change how we tackle problems in code. Yes we can still continue to write code to perform an action in a top down fashion to complete a task. This apprach will continue to work; however, you are not taking advantage of the extra processing power available. The best way to take advantage of the extra cores prior to .NET Framework 4.0 was to create threads and/or utilize the ThreadPool. For many developers utilizing Threads or the ThreadPool can be a little daunting. The .NET 4.0 Framework drastically simplified the process of utilizing the extra processing power through the Task Parallel Library (TPL). This article talks following topics “Data Parallelism”, “Parallel LINQ (PLINQ)” and “Task Parallelism”. span.fullpost {display:none;}

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  • C or assembly code to find current cpu core speed

    - by honestann
    How can my application efficiently determine the following information peroidically while it executes: 1: current speed of each of the 8 CPU cores. 2: which core the code is currently executing on. My application is C and assembly-language, so any solution in either C or assembly-language is fine. This code needs to execute quickly, so creating, reading and processing a file generated by "cat /proc/cpuinfo" is much too slow. The cores slow-down and speed-up automatically, probably to keep CPU temperature under control. Therefore, a one-time measure is not sufficient for my purposes. My application already reads and subtracts the cpu cycle counter in assembly language to determine number of clock cycles, but my program cannot compute elapsed time in nanoseconds unless it knows the current clock frequency of the cpu cores (and which core the code is executing on). Thanks!

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  • Improve your Application Performance with .NET Framework 4.0

    Nice Article on CodeGuru. This processors we use today are quite different from those of just a few years ago, as most processors today provide multiple cores and/or multiple threads. With multiple cores and/or threads we need to change how we tackle problems in code. Yes we can still continue to write code to perform an action in a top down fashion to complete a task. This apprach will continue to work; however, you are not taking advantage of the extra processing power available. The best way to take advantage of the extra cores prior to .NET Framework 4.0 was to create threads and/or utilize the ThreadPool. For many developers utilizing Threads or the ThreadPool can be a little daunting. The .NET 4.0 Framework drastically simplified the process of utilizing the extra processing power through the Task Parallel Library (TPL). This article talks following topics “Data Parallelism”, “Parallel LINQ (PLINQ)” and “Task Parallelism”. span.fullpost {display:none;}

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  • PASS Summit 2011 &ndash; Part III

    - by Tara Kizer
    Well we’re about a month past PASS Summit 2011, and yet I haven’t finished blogging my notes! Between work and home life, I haven’t been able to come up for air in a bit.  Now on to my notes… On Thursday of the PASS Summit 2011, I attended Klaus Aschenbrenner’s (blog|twitter) “Advanced SQL Server 2008 Troubleshooting”, Joe Webb’s (blog|twitter) “SQL Server Locking & Blocking Made Simple”, Kalen Delaney’s (blog|twitter) “What Happened? Exploring the Plan Cache”, and Paul Randal’s (blog|twitter) “More DBA Mythbusters”.  I think my head grew two times in size from the Thursday sessions.  Just WOW! I took a ton of notes in Klaus' session.  He took a deep dive into how to troubleshoot performance problems.  Here is how he goes about solving a performance problem: Start by checking the wait stats DMV System health Memory issues I/O issues I normally start with blocking and then hit the wait stats.  Here’s the wait stat query (Paul Randal’s) that I use when working on a performance problem.  He highlighted a few waits to be aware of such as WRITELOG (indicates IO subsystem problem), SOS_SCHEDULER_YIELD (indicates CPU problem), and PAGEIOLATCH_XX (indicates an IO subsystem problem or a buffer pool problem).  Regarding memory issues, Klaus recommended that as a bare minimum, one should set the “max server memory (MB)” in sp_configure to 2GB or 10% reserved for the OS (whichever comes first).  This is just a starting point though! Regarding I/O issues, Klaus talked about disk partition alignment, which can improve SQL I/O performance by up to 100%.  You should use 64kb for NTFS cluster, and it’s automatic in Windows 2008 R2. Joe’s locking and blocking presentation was a good session to really clear up the fog in my mind about locking.  One takeaway that I had no idea could be done was that you can set a timeout in T-SQL code view LOCK_TIMEOUT.  If you do this via the application, you should trap error 1222. Kalen’s session went into execution plans.  The minimum size of a plan is 24k.  This adds up fast especially if you have a lot of plans that don’t get reused much.  You can use sys.dm_exec_cached_plans to check how often a plan is being reused by checking the usecounts column.  She said that we can use DBCC FLUSHPROCINDB to clear out the stored procedure cache for a specific database.  I didn’t know we had this available, so this was great to hear.  This will be less intrusive when an emergency comes up where I’ve needed to run DBCC FREEPROCCACHE. Kalen said one should enable “optimize for ad hoc workloads” if you have an adhoc loc.  This stores only a 300-byte stub of the first plan, and if it gets run again, it’ll store the whole thing.  This helps with plan cache bloat.  I have a lot of systems that use prepared statements, and Kalen says we simulate those calls by using sp_executesql.  Cool! Paul did a series of posts last year to debunk various myths and misconceptions around SQL Server.  He continues to debunk things via “DBA Mythbusters”.  You can get a PDF of a bunch of these here.  One of the myths he went over is the number of tempdb data files that you should have.  Back in 2000, the recommendation was to have as many tempdb data files as there are CPU cores on your server.  This no longer holds true due to the numerous cores we have on our servers.  Paul says you should start out with 1/4 to 1/2 the number of cores and work your way up from there.  BUT!  Paul likes what Bob Ward (twitter) says on this topic: 8 or less cores –> set number of files equal to the number of cores Greater than 8 cores –> start with 8 files and increase in blocks of 4 One common myth out there is to set your MAXDOP to 1 for an OLTP workload with high CXPACKET waits.  Instead of that, dig deeper first.  Look for missing indexes, out-of-date statistics, increase the “cost threshold for parallelism” setting, and perhaps set MAXDOP at the query level.  Paul stressed that you should not plan a backup strategy but instead plan a restore strategy.  What are your recoverability requirements?  Once you know that, now plan out your backups. As Paul always does, he talked about DBCC CHECKDB.  He said how fabulous it is.  I didn’t want to interrupt the presentation, so after his session had ended, I asked Paul about the need to run DBCC CHECKDB on your mirror systems.  You could have data corruption occur at the mirror and not at the principal server.  If you aren’t checking for data corruption on your mirror systems, you could be failing over to a corrupt database in the case of a disaster or even a planned failover.  You can’t run DBCC CHECKDB against the mirrored database, but you can run it against a snapshot off the mirrored database.

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  • Parallelism implies concurrency but not the other way round right?

    - by Cedric Martin
    I often read that parallelism and concurrency are different things. Very often the answerers/commenters go as far as writing that they're two entirely different things. Yet in my view they're related but I'd like some clarification on that. For example if I'm on a multi-core CPU and manage to divide the computation into x smaller computation (say using fork/join) each running in its own thread, I'll have a program that is both doing parallel computation (because supposedly at any point in time several threads are going to run on several cores) and being concurrent right? While if I'm simply using, say, Java and dealing with UI events and repaints on the Event Dispatch Thread plus running the only thread I created myself, I'll have a program that is concurrent (EDT + GC thread + my main thread etc.) but not parallel. I'd like to know if I'm getting this right and if parallelism (on a "single but multi-cores" system) always implies concurrency or not? Also, are multi-threaded programs running on multi-cores CPU but where the different threads are doing totally different computation considered to be using "parallelism"?

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  • How do I create a solr core with the data from an existing one?

    - by steve_d
    Solr 1.4 Enterprise Search Server recommends doing large updates on a copy of the core, and then swapping it in for the main core. I am following these steps: Create prep core: http://localhost:8983/solr/admin/cores?action=CREATE&name=prep&instanceDir=main Perform index update, then commit/optimize on prep core. Swap main and prep core: http://localhost:8983/solr/admin/cores?action=SWAP&core=main&other=prep Unload prep core: http://localhost:8983/solr/admin/cores?action=UNLOAD&core=prep The problem I am having is, the core created in step 1 doesn't have any data in it. If I am going to do a full index of everything and the kitchen sink, that would be fine, but if I just want to update a (large) subset of the documents - that's obviously not going to work. (I could merge the cores, but part of what I'm trying to do is get rid of any deleted documents without trying to make a list of them.) Is there some flag to the CREATE action that I'm missing? The Solr Wiki page for CoreAdmin is a little sparse on details.

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  • How can I use my multiple cored dedicated server to run my java application?

    - by Delta
    I have a game built in a java environment and I use JVM. I have 4 cores @ 2.4Ghz and my server is only using one of those cores... I've tried and searched and I still have no guides to setup multiple cores to run the game like, say 1 core for running the character saving + loading, and 1 core for the server itself, and 1 core for a helper to help other cores that need more power. I don't even know if this is possible but this is all in java the operating machine is windows server 2003 and I've tried so hard I just don't know what to do. May someone please help me! Thank you so much!

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  • What hash algorithms are paralellizable? Optimizing the hashing of large files utilizing on mult-co

    - by DanO
    I'm interested in optimizing the hashing of some large files (optimizing wall clock time). The I/O has been optimized well enough already and the I/O device (local SSD) is only tapped at about 25% of capacity, while one of the CPU cores is completely maxed-out. I have more cores available, and in the future will likely have even more cores. So far I've only been able to tap into more cores if I happen to need multiple hashes of the same file, say an MD5 AND a SHA256 at the same time. I can use the same I/O stream to feed two or more hash algorithms, and I get the faster algorithms done for free (as far as wall clock time). As I understand most hash algorithms, each new bit changes the entire result, and it is inherently challenging/impossible to do in parallel. Are any of the mainstream hash algorithms parallelizable? Are there any non-mainstream hashes that are parallelizable (and that have at least a sample implementation available)? As future CPUs will trend toward more cores and a leveling off in clock speed, is there any way to improve the performance of file hashing? (other than liquid nitrogen cooled overclocking?) or is it inherently non-parallelizable?

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  • Determining the load on a particular core in a multicore processor

    - by S.Man
    In a multicore processor, there are ways to tell the particular application to run in either single core or 2 cores or 3 cores. During such scenarios, how will a scheduler be able to determine the load(number of threads) on a particular core in a multicore processor and accordingly distribute(balance) the load(allocate threads) across the various cores ?

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  • What hash algorithms are parallelizable? Optimizing the hashing of large files utilizing on multi-co

    - by DanO
    I'm interested in optimizing the hashing of some large files (optimizing wall clock time). The I/O has been optimized well enough already and the I/O device (local SSD) is only tapped at about 25% of capacity, while one of the CPU cores is completely maxed-out. I have more cores available, and in the future will likely have even more cores. So far I've only been able to tap into more cores if I happen to need multiple hashes of the same file, say an MD5 AND a SHA256 at the same time. I can use the same I/O stream to feed two or more hash algorithms, and I get the faster algorithms done for free (as far as wall clock time). As I understand most hash algorithms, each new bit changes the entire result, and it is inherently challenging/impossible to do in parallel. Are any of the mainstream hash algorithms parallelizable? Are there any non-mainstream hashes that are parallelizable (and that have at least a sample implementation available)? As future CPUs will trend toward more cores and a leveling off in clock speed, is there any way to improve the performance of file hashing? (other than liquid nitrogen cooled overclocking?) or is it inherently non-parallelizable?

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  • Intel Xeon 5600 (Westmere-EP) and 7500 (Nehalem-EX)

    - by jchang
    Intel Xeon 5600 (Westmere-EP) and 7500 (Nehalem-EX) Performance Intel launched the Xeon 5600 series (Westmere-EP, 32nm) six-core processors on 16 March 2010 without any TPC benchmark results. In the performance world, no results almost always mean bad or not good results. Yet there is every reason to believe that the Xeon 5600 series with six-cores (X models only) will performance exactly as expected for a 50% increase in the number of cores at the same frequency (as the 5500) with no system level...(read more)

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  • The winning combination: Oracle VM Server for x86 + Oracle Sun Fire HW

    - by Karim Berrah
    You might be wondering why OVM Server for x86 (OVM/x86 here and below) should be seriously considered as a nice (business point of view) alternative to standard Hypervisors, if you are virtualizing Oracle Software, especially if you are planning to move to Oracle x86 Hardware (rackmount or blades). Well, let see some "not well known" facts that might interest you and help you in saving more money for your entire company (and not only the Virtulization team). Fact 1: OVM/x86 is considered as a hard partitionning technology (check page 2 of Oracle Server Partitionning Licencing Policies), so if you are buying new servers based on the latest INTEL Xeon E7 CPUs (10 cores per Socket) and have some licencing issues in deploying further Oracle SW, because you are using a hypervisor not recognized as a hard partitionning technology (like VMware), then you need to check here how to do it with OVM . This might help you to continue to deploy your Oracle DB instances on new x86 HW (12 cores, 40 cores, 64 cores servers) in a reasonable way, without having to pay licences for 12 CPU, 40 CPUs or 64 CPUs. You might also consider migrating your legacy Oracle DB DBs to a virtualized environment like OVM/x86 an recover some CPU licences, that can be reused somewhere else in production. Fact 2: OVM/x86 is free to use, without any extra licence for any specific feature (LiveMigration, High Availability, Embedded Management Console). If you want to use it on non Oracle HW, there is a support fee per  system and per year, that is much below VMware support (Oracle VM Premier Limited Support for systems up to 2 CPUs, and Oracle VM Premier Support for any bigger system, independently on the number of populated sockets). Fact 3: support is included with your Oracle x86 HW support (OPS for systems)  and you can re-install on you system Oracle Linux, Oracle Solaris or Oracle VM server for x86, without beeing charged, an keeping the same support level. Fact 4: it is less expensive to virtualize Oracle Linux or Oracle Solaris on OVM/x86 with Oracle HW that any other similar solution with VMware, because all the VMs are then supported and licenced when you buy Oracle HW with OPS. Fact 5: Oracle VM Templates bring you many Virtual Machines already installed, patched and optimized for various Oracle applications. And to be more specific, those templates are fully supported by Oracle, which is not really true when it comes to another hypervisor. By optimized VM Kernel, I mean PV drivers, OVM-ready kernels in the VM, single source clock for all the VMS, better memory management of the VM ... Fact 6: there is no extra costs for a management console. OVM comes with a free OVM Manager package for Linux.  More infos: Latest announcement of OVM/x86 update 2.2.2 A short flash demo of OVM server for x86 A short flash demo on OVM Templates and Virtual Assembly Builder Oracle Linux Support and Oracle VM Support Global Price List  ISVs: Benefits for Independant Sofwtare Vendors (ISVs) in using OVM/x86 Consultant Services: Advanced Customer Services for OVM/x86  Technical Features Best practices and Guideline for OVM with Oracle Blades Reduce TCO and get more Value from your x86 Infrastructure

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  • Core Parking in Ubuntu?

    - by Xxx Xxx
    Core parking is a new feature that introduced in Windows 7 to get better Battery performance . Depending on the resource use of the operating system it may park one or multiple cores of a multi-core cpu to reduce the computer’s power consumption and thermal emissions. Once operations require more processing power, the parked cores are activated again to assist in the tasks So my question is that is there any way i can do it on Ubuntu 12.04 " Core Parking " ?

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  • Intel Xeon E5 (Sandy Bridge-EP) and SQL Server 2012 Benchmarks

    - by jchang
    Intel officially announced the Xeon E5 2600 series processor based on Sandy Bridge-EP variant with upto 8 cores and 20MB LLC per socket. Only one TPC benchmark accompanied product launch, summary below. Processors Cores per Frequency Memory SQL Vendor TPC-E 2 x Xeon E5-2690 8 2.9GHz 512GB (16x32GB) 2012 IBM 1,863.23 2 x Xeon E7-2870 10 2.4GHz 512GB (32x16GB) 2008R2 IBM 1,560.70 2 x Xeon X5690 6 3.46GHz 192GB (12x16GB) 2008R2 HP 1,284.14 Note: the HP report lists SQL Server 2008 R2 Enterprise Edition...(read more)

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  • Impact of the L3 cache on performance - worth a dual-processor system?

    - by Dan Nissenbaum
    I will be purchasing a new high-end system, and I would like to have a better sense of whether a dual-processor Xeon system (I am looking at the new, high-end Xeon E5-2687W) might, realistically, provide a noticeable performance improvement due to the doubling of the L3 cache (20 MB per CPU). (This is in addition to the occasional added advantage due to the doubling of cores and RAM.) My usage scenario is, roughly, that I have many background applications running at any time - 3 or 4 data compression/backup applications, a low-impact web server, one or two virtual machines at any given time (usually fairly idle), and perhaps 20 utility programs that utilize a noticeable (but small) portion of the CPU cores. In total, when I am not actively using the computer, about 25% of the total CPU power is utilized in my current i7-970 6-core (12 thread) system. When I am doing routine work, the CPU utilization often exceeds 50%, and occasionally hits 75%-80%. The Xeon E5-2687W is not only a second-generation i7 (so should improve performance for that reason), but also has 8 cores (16 threads), rather than 6 cores. For this reason, I expect to run into the 75% CPU range even less frequently. Nonetheless, the ability to double the cores and the RAM is a consideration. However, in the end, I believe this decision comes down to whether the doubling of the L3 cache will provide a noticeable improvement. There are many benchmarks, and a lot of discussion, regarding CPU power. However, I find very little discussion of L3 cache utilization, and how increases in the L3 cache (such as doubling it with dual processors) affect performance. For example: If there are only two processes running, but each benefits from a large L3 cache (such as might be the case for background processes that frequently scan the file system), perhaps the overall system performance might noticeably improve with dual CPU's - even if only a single core is active on each CPU - due to each process having double the effective L3 cache. I am hoping that someone has a sense of the benefits of increasing (or doubling) the L3 cache size. Note: the CPU I am considering (the Xeon E5-2687W) has 20 MB L3 cache, so a system with dual CPU's would have 40 MB L3 cache.

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  • A new number one

    - by nospam(at)example.com (Joerg Moellenkamp)
    The Top500 supercomputer list has a new number one: The K Computer, built by Fujitsu, currently combines 68544 SPARC64 VIIIfx CPUs, each with eight cores, for a total of 548,352 cores?almost twice as many as any other system in the TOP500. The K Computer is also more powerful than the next five systems on the list combined.Interestingly this system runs under Linux. And it uses tofu as its interconnect

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  • Redhat 5.5: Multi-thread process only uses 1 CPU of the available 8

    - by Tonny
    Weird situation: Redhat Enterprise 5.5 (stock install, no updates, x64) on a HP z800 workstation. (Dual Xeon 2,2 Ghz. 8 cores, 16 if you count Hyper-threading. RH sees 16 cores.) We have an application that can utilize 1, 2 or 4 threads for heavy calculations. Somehow all these threads run on the same core at 100% load (the other 15 cores are nearly idle) so there is absolutely no benefit from the extra threads. In fact there is a slight slowdown as the threads get in each others way on the single core. How do I get them to run on separate cores (if possible)? Application is 64 bit. Can't change anything about the software except changing the threads setting. Is there some obscure Linux setting I can try to change? (I'm a True64 and Aix guy. I use Linux, but have no in depth knowledge of the process scheduling on Linux.)

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  • IBM "per core" comparisons for SPECjEnterprise2010

    - by jhenning
    I recently stumbled upon a blog entry from Roman Kharkovski (an IBM employee) comparing some SPECjEnterprise2010 results for IBM vs. Oracle. Mr. Kharkovski's blog claims that SPARC delivers half the transactions per core vs. POWER7. Prior to any argument, I should say that my predisposition is to like Mr. Kharkovski, because he says that his blog is intended to be factual; that the intent is to try to avoid marketing hype and FUD tactic; and mostly because he features a picture of himself wearing a bike helmet (me too). Therefore, in a spirit of technical argument, rather than FUD fight, there are a few areas in his comparison that should be discussed. Scaling is not free For any benchmark, if a small system scores 13k using quantity R1 of some resource, and a big system scores 57k using quantity R2 of that resource, then, sure, it's tempting to divide: is  13k/R1 > 57k/R2 ? It is tempting, but not necessarily educational. The problem is that scaling is not free. Building big systems is harder than building small systems. Scoring  13k/R1  on a little system provides no guarantee whatsoever that one can sustain that ratio when attempting to handle more than 4 times as many users. Choosing the denominator radically changes the picture When ratios are used, one can vastly manipulate appearances by the choice of denominator. In this case, lots of choices are available for the resource to be compared (R1 and R2 above). IBM chooses to put cores in the denominator. Mr. Kharkovski provides some reasons for that choice in his blog entry. And yet, it should be noted that the very concept of a core is: arbitrary: not necessarily comparable across vendors; fluid: modern chips shift chip resources in response to load; and invisible: unless you have a microscope, you can't see it. By contrast, one can actually see processor chips with the naked eye, and they are a bit easier to count. If we put chips in the denominator instead of cores, we get: 13161.07 EjOPS / 4 chips = 3290 EjOPS per chip for IBM vs 57422.17 EjOPS / 16 chips = 3588 EjOPS per chip for Oracle The choice of denominator makes all the difference in the appearance. Speaking for myself, dividing by chips just seems to make more sense, because: I can see chips and count them; and I can accurately compare the number of chips in my system to the count in some other vendor's system; and Tthe probability of being able to continue to accurately count them over the next 10 years of microprocessor development seems higher than the probability of being able to accurately and comparably count "cores". SPEC Fair use requirements Speaking as an individual, not speaking for SPEC and not speaking for my employer, I wonder whether Mr. Kharkovski's blog article, taken as a whole, meets the requirements of the SPEC Fair Use rule www.spec.org/fairuse.html section I.D.2. For example, Mr. Kharkovski's footnote (1) begins Results from http://www.spec.org as of 04/04/2013 Oracle SUN SPARC T5-8 449 EjOPS/core SPECjEnterprise2010 (Oracle's WLS best SPECjEnterprise2010 EjOPS/core result on SPARC). IBM Power730 823 EjOPS/core (World Record SPECjEnterprise2010 EJOPS/core result) The questionable tactic, from a Fair Use point of view, is that there is no such metric at the designated location. At www.spec.org, You can find the SPEC metric 57422.17 SPECjEnterprise2010 EjOPS for Oracle and You can also find the SPEC metric 13161.07 SPECjEnterprise2010 EjOPS for IBM. Despite the implication of the footnote, you will not find any mention of 449 nor anything that says 823. SPEC says that you can, under its fair use rule, derive your own values; but it emphasizes: "The context must not give the appearance that SPEC has created or endorsed the derived value." Substantiation and transparency Although SPEC disclaims responsibility for non-SPEC information (section I.E), it says that non-SPEC data and methods should be accurate, should be explained, should be substantiated. Unfortunately, it is difficult or impossible for the reader to independently verify the pricing: Were like units compared to like (e.g. list price to list price)? Were all components (hw, sw, support) included? Were all fees included? Note that when tpc.org shows IBM pricing, there are often items such as "PROCESSOR ACTIVATION" and "MEMORY ACTIVATION". Without the transparency of a detailed breakdown, the pricing claims are questionable. T5 claim for "Fastest Processor" Mr. Kharkovski several times questions Oracle's claim for fastest processor, writing You see, when you publish industry benchmarks, people may actually compare your results to other vendor's results. Well, as we performance people always say, "it depends". If you believe in performance-per-core as the primary way of looking at the world, then yes, the POWER7+ is impressive, spending its chip resources to support up to 32 threads (8 cores x 4 threads). Or, it just might be useful to consider performance-per-chip. Each SPARC T5 chip allows 128 hardware threads to be simultaneously executing (16 cores x 8 threads). The Industry Standard Benchmark that focuses specifically on processor chip performance is SPEC CPU2006. For this very well known and popular benchmark, SPARC T5: provides better performance than both POWER7 and POWER7+, for 1 chip vs. 1 chip, for 8 chip vs. 8 chip, for integer (SPECint_rate2006) and floating point (SPECfp_rate2006), for Peak tuning and for Base tuning. For example, at the 8-chip level, integer throughput (SPECint_rate2006) is: 3750 for SPARC 2170 for POWER7+. You can find the details at the March 2013 BestPerf CPU2006 page SPEC is a trademark of the Standard Performance Evaluation Corporation, www.spec.org. The two specific results quoted for SPECjEnterprise2010 are posted at the URLs linked from the discussion. Results for SPEC CPU2006 were verified at spec.org 1 July 2013, and can be rechecked here.

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  • CPU's on Hyper-V host system is just idling, even though VM's are at full throttle

    - 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 These three machines are running very sluggishly, they are at 100% cpu even though the host system is barely using any cpu at all, typically below 10% total. Could anyone please give some tips as to the best setup for CPU allocating? Should I have set each server to have two cores, or should I increase this number above the total number of cores on the host? What is a good number to set on the Virtual Machine Reserve and Virtual Machine Limit? Is 8 gigs of physical RAM insufficient for 3 VM's? Thanks for reading. :)

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  • How can I judge the suitability of modern processors for systems with specific CPU requirements?

    - by Iszi
    Inspired by this question: How do I calculate clock speed in multi-core processors? The answers in the above question do a fair job of explaining why a lower-speed multi-core processor won't necessarily perform at the same level as a higher-speed single-core processor. Example: 4*2=8, but a quad-core 2 GHz processor isn't necessarily as fast as a single-core 8 GHz processor. However, I'm having a hard time putting the information in those answers to practical use in my mind. Particularly, I want to know how it should be used to judge whether a given CPU is appropriate for an application with specific requirements. Example scenarios: An application has a minimum CPU requirement of 2.4 GHz dual-core. Another application has a minimum CPU requirement of 1.8 GHz single-core. For either of the above scenarios: Would a higher-speed processor with fewer cores, or a lower-speed processor with more cores, be equally sufficient? If so, how can we determine the appropriate processor speeds required for a given number of cores?

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