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  • What is the fastest cyclic synchronization in Java (ExecutorService vs. CyclicBarrier vs. X)?

    - by Alex Dunlop
    Which Java synchronization construct is likely to provide the best performance for a concurrent, iterative processing scenario with a fixed number of threads like the one outlined below? After experimenting on my own for a while (using ExecutorService and CyclicBarrier) and being somewhat surprised by the results, I would be grateful for some expert advice and maybe some new ideas. Existing questions here do not seem to focus primarily on performance, hence this new one. Thanks in advance! The core of the app is a simple iterative data processing algorithm, parallelized to the spread the computational load across 8 cores on a Mac Pro, running OS X 10.6 and Java 1.6.0_07. The data to be processed is split into 8 blocks and each block is fed to a Runnable to be executed by one of a fixed number of threads. Parallelizing the algorithm was fairly straightforward, and it functionally works as desired, but its performance is not yet what I think it could be. The app seems to spend a lot of time in system calls synchronizing, so after some profiling I wonder whether I selected the most appropriate synchronization mechanism(s). A key requirement of the algorithm is that it needs to proceed in stages, so the threads need to sync up at the end of each stage. The main thread prepares the work (very low overhead), passes it to the threads, lets them work on it, then proceeds when all threads are done, rearranges the work (again very low overhead) and repeats the cycle. The machine is dedicated to this task, Garbage Collection is minimized by using per-thread pools of pre-allocated items, and the number of threads can be fixed (no incoming requests or the like, just one thread per CPU core). V1 - ExecutorService My first implementation used an ExecutorService with 8 worker threads. The program creates 8 tasks holding the work and then lets them work on it, roughly like this: // create one thread per CPU executorService = Executors.newFixedThreadPool( 8 ); ... // now process data in cycles while( ...) { // package data into 8 work items ... // create one Callable task per work item ... // submit the Callables to the worker threads executorService.invokeAll( taskList ); } This works well functionally (it does what it should), and for very large work items indeed all 8 CPUs become highly loaded, as much as the processing algorithm would be expected to allow (some work items will finish faster than others, then idle). However, as the work items become smaller (and this is not really under the program's control), the user CPU load shrinks dramatically: blocksize | system | user | cycles/sec 256k 1.8% 85% 1.30 64k 2.5% 77% 5.6 16k 4% 64% 22.5 4096 8% 56% 86 1024 13% 38% 227 256 17% 19% 420 64 19% 17% 948 16 19% 13% 1626 Legend: - block size = size of the work item (= computational steps) - system = system load, as shown in OS X Activity Monitor (red bar) - user = user load, as shown in OS X Activity Monitor (green bar) - cycles/sec = iterations through the main while loop, more is better The primary area of concern here is the high percentage of time spent in the system, which appears to be driven by thread synchronization calls. As expected, for smaller work items, ExecutorService.invokeAll() will require relatively more effort to sync up the threads versus the amount of work being performed in each thread. But since ExecutorService is more generic than it would need to be for this use case (it can queue tasks for threads if there are more tasks than cores), I though maybe there would be a leaner synchronization construct. V2 - CyclicBarrier The next implementation used a CyclicBarrier to sync up the threads before receiving work and after completing it, roughly as follows: main() { // create the barrier barrier = new CyclicBarrier( 8 + 1 ); // create Runable for thread, tell it about the barrier Runnable task = new WorkerThreadRunnable( barrier ); // start the threads for( int i = 0; i < 8; i++ ) { // create one thread per core new Thread( task ).start(); } while( ... ) { // tell threads about the work ... // N threads + this will call await(), then system proceeds barrier.await(); // ... now worker threads work on the work... // wait for worker threads to finish barrier.await(); } } class WorkerThreadRunnable implements Runnable { CyclicBarrier barrier; WorkerThreadRunnable( CyclicBarrier barrier ) { this.barrier = barrier; } public void run() { while( true ) { // wait for work barrier.await(); // do the work ... // wait for everyone else to finish barrier.await(); } } } Again, this works well functionally (it does what it should), and for very large work items indeed all 8 CPUs become highly loaded, as before. However, as the work items become smaller, the load still shrinks dramatically: blocksize | system | user | cycles/sec 256k 1.9% 85% 1.30 64k 2.7% 78% 6.1 16k 5.5% 52% 25 4096 9% 29% 64 1024 11% 15% 117 256 12% 8% 169 64 12% 6.5% 285 16 12% 6% 377 For large work items, synchronization is negligible and the performance is identical to V1. But unexpectedly, the results of the (highly specialized) CyclicBarrier seem MUCH WORSE than those for the (generic) ExecutorService: throughput (cycles/sec) is only about 1/4th of V1. A preliminary conclusion would be that even though this seems to be the advertised ideal use case for CyclicBarrier, it performs much worse than the generic ExecutorService. V3 - Wait/Notify + CyclicBarrier It seemed worth a try to replace the first cyclic barrier await() with a simple wait/notify mechanism: main() { // create the barrier // create Runable for thread, tell it about the barrier // start the threads while( ... ) { // tell threads about the work // for each: workerThreadRunnable.setWorkItem( ... ); // ... now worker threads work on the work... // wait for worker threads to finish barrier.await(); } } class WorkerThreadRunnable implements Runnable { CyclicBarrier barrier; @NotNull volatile private Callable<Integer> workItem; WorkerThreadRunnable( CyclicBarrier barrier ) { this.barrier = barrier; this.workItem = NO_WORK; } final protected void setWorkItem( @NotNull final Callable<Integer> callable ) { synchronized( this ) { workItem = callable; notify(); } } public void run() { while( true ) { // wait for work while( true ) { synchronized( this ) { if( workItem != NO_WORK ) break; try { wait(); } catch( InterruptedException e ) { e.printStackTrace(); } } } // do the work ... // wait for everyone else to finish barrier.await(); } } } Again, this works well functionally (it does what it should). blocksize | system | user | cycles/sec 256k 1.9% 85% 1.30 64k 2.4% 80% 6.3 16k 4.6% 60% 30.1 4096 8.6% 41% 98.5 1024 12% 23% 202 256 14% 11.6% 299 64 14% 10.0% 518 16 14.8% 8.7% 679 The throughput for small work items is still much worse than that of the ExecutorService, but about 2x that of the CyclicBarrier. Eliminating one CyclicBarrier eliminates half of the gap. V4 - Busy wait instead of wait/notify Since this app is the primary one running on the system and the cores idle anyway if they're not busy with a work item, why not try a busy wait for work items in each thread, even if that spins the CPU needlessly. The worker thread code changes as follows: class WorkerThreadRunnable implements Runnable { // as before final protected void setWorkItem( @NotNull final Callable<Integer> callable ) { workItem = callable; } public void run() { while( true ) { // busy-wait for work while( true ) { if( workItem != NO_WORK ) break; } // do the work ... // wait for everyone else to finish barrier.await(); } } } Also works well functionally (it does what it should). blocksize | system | user | cycles/sec 256k 1.9% 85% 1.30 64k 2.2% 81% 6.3 16k 4.2% 62% 33 4096 7.5% 40% 107 1024 10.4% 23% 210 256 12.0% 12.0% 310 64 11.9% 10.2% 550 16 12.2% 8.6% 741 For small work items, this increases throughput by a further 10% over the CyclicBarrier + wait/notify variant, which is not insignificant. But it is still much lower-throughput than V1 with the ExecutorService. V5 - ? So what is the best synchronization mechanism for such a (presumably not uncommon) problem? I am weary of writing my own sync mechanism to completely replace ExecutorService (assuming that it is too generic and there has to be something that can still be taken out to make it more efficient). It is not my area of expertise and I'm concerned that I'd spend a lot of time debugging it (since I'm not even sure my wait/notify and busy wait variants are correct) for uncertain gain. Any advice would be greatly appreciated.

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  • Need help receiving ByteArray data

    - by k80sg
    Hi folks, I am trying to receive byte array data from a machine. It sends out 3 different types of data structure each with different number of fields which consist of mostly int and a few floats, and byte sizes, the first being 320 bytes, 420 for the second type and 560 for the third. When the sending program is launched, it fires all 3 types of data simultaneouly with an interval of 1 sec. Example: Sending order: Pack1 - 320 bytes 1 sec later Pack2 - 420 bytes 1 sec later Pack3 - 560 bytes 1 sec later Pack1 - 320 bytes ... .. . How do I check the incoming byte size before passing it to: byte[] handsize = new byte[bytesize]; as the data I receive are all out of order, for instance using the following the read all int: System.out.println("Reading data in int format:" + " " + datainput.readInt()); I get many different sets of values whenever I run my prog although with some valid field data but they are all over the place. I am not too sure how exactly should I do it but I tried the following and apparently my data fields are not receiving in correct sequence: BufferedInputStream bais = new BufferedInputStream(requestSocket.getInputStream()); DataInputStream datainput = new DataInputStream(bais); byte[] handsize = new byte[560]; datainput.readFully(handsize); int n = 0; int intByte[] = new int[140]; for (int i = 0; i < 140 ; i++) { System.out.println("Reading data in int format:" + " " + datainput.readInt()); intByte[n] = datainput.readInt(); n = n + 1; System.out.println("The value in array is:" + intByte[0]); System.out.println("The value in array is:" + intByte[1]); System.out.println("The value in array is:" + intByte[2]); System.out.println("The value in array is:" + intByte[3]); Also from the above code, the order of the values printed out with System.out.println("Reading data in int format:" + " " + datainput.readInt()); and System.out.println("The value in array is:" + intByte[0]); System.out.println("The value in array is:" + intByte[1]); are different. Any help will be appreciated. Thanks

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  • set radio button in jquery dialog

    - by RememberME
    I have the following if/else on another form and it works perfectly. I've now put it on a form which shows as a jquery dialog. Every alert along the way shows the correct assignment, but when the dialog opens, neither button is selected. $("#create-company").click(function() { alert($('#primary_company').val().length); if ($('#primary_company').val().length > 0) { alert("if secondary"); $('#secondary').attr('checked', 'true'); var id = $("input:radio[name='companyType']:checked").attr('id'); alert(id); } else { alert("else primary"); $('#primary').attr('checked', 'true'); $('#sec').hide(); var id = $("input:radio[name='companyType']:checked").attr('id'); alert(id); } var id = $("input:radio[name='companyType']:checked").attr('id'); alert(id); $('#popupCreateCompany').dialog('open'); }); Dialog: $('#popupCreateCompany').dialog( { autoOpen: false, modal: true, buttons: { 'Add': function() { var dialog = $(this); var form = dialog.find('input:text, select'); $.post('/company/post', $(form).serialize(), function(data) { if (data.Result == "success") { var id = $("input:radio[name='companyType']:checked").attr('id'); if (id == "primary") { $('#company').append($('<option></option>').val(data.company_id).html(data.company_name).attr("selected", true)); $('#primary_company').append($('<option></option>').val(data.company_id).html(data.company_name).attr("selected", true)); $('#company_id').append($('<option></option>').val(data.company_id).html(data.company_name).attr("selected", true)); } else { $('#company_id').append($('<option></option>').val(data.company_id).html(data.company_name)); } dialog.dialog('close'); alert("Company " + data.company_name + " successfully added."); } else { alert(data.Result); }; }, "json") }, 'Cancel': function() { $(this).dialog('close'); } } }); Radio buttons: <label>Company Type:</label> <label for="primary"><input onclick="javascript: $('#sec').hide('slow');$('#primary_company').find('option:first').attr('selected','selected');" type="radio" name="companyType" id="primary" />Primary</label> <label for="secondary"><input onclick="javascript: $('#sec').show('slow');" type="radio" name="companyType" id="secondary" />Subsidiary</label> <div id="sec"> <fieldset> <label for="primary_company">Primary Company:</label> <%= Html.DropDownList("primary_company", Model.SelectPrimaryCompanies, "** Select Primary Company **") %> </fieldset> </div>

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  • Better way to fill a Ruby hash?

    - by sardaukar
    Is there a better way to do this? (it looks clunky) form_params = {} form_params['tid'] = tid form_params['qid'] = qid form_params['pri'] = pri form_params['sec'] = sec form_params['to_u'] = to_u form_params['to_d'] = to_d form_params['from'] = from form_params['wl'] = wl

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  • CheerryPy and concurrency

    - by RadiantHex
    Hi folks, I'm using CheeryPy in order to serve a python application through WSGI. I tried benchmarking it, but it seems as if CheeryPy can only handle exactly 10 req/sec. No matter what I do. Built a simple app with a 3 second pause, in order to accurately determine what is going on... and I can confirm that the 10 req/sec has nothing to do with the resources used by the python script. __ Any ideas?

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  • 2 drives, slow software RAID1 (md)

    - by bart613
    Hello, I've got a server from hetzner.de (EQ4) with 2* SAMSUNG HD753LJ drives (750G 32MB cache). OS is CentOS 5 (x86_64). Drives are combined together into two RAID1 partitions: /dev/md0 which is 512MB big and has only /boot partitions /dev/md1 which is over 700GB big and is one big LVM which hosts other partitions Now, I've been running some benchmarks and it seems like even though exactly the same drives, speed differs a bit on each of them. # hdparm -tT /dev/sda /dev/sda: Timing cached reads: 25612 MB in 1.99 seconds = 12860.70 MB/sec Timing buffered disk reads: 352 MB in 3.01 seconds = 116.80 MB/sec # hdparm -tT /dev/sdb /dev/sdb: Timing cached reads: 25524 MB in 1.99 seconds = 12815.99 MB/sec Timing buffered disk reads: 342 MB in 3.01 seconds = 113.64 MB/sec Also, when I run eg. pgbench which is stressing IO quite heavily, I can see following from iostat output: Device: rrqm/s wrqm/s r/s w/s rsec/s wsec/s avgrq-sz avgqu-sz await svctm %util sda 0.00 231.40 0.00 298.00 0.00 9683.20 32.49 0.17 0.58 0.34 10.24 sda1 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 sda2 0.00 231.40 0.00 298.00 0.00 9683.20 32.49 0.17 0.58 0.34 10.24 sdb 0.00 231.40 0.00 301.80 0.00 9740.80 32.28 14.19 51.17 3.10 93.68 sdb1 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 sdb2 0.00 231.40 0.00 301.80 0.00 9740.80 32.28 14.19 51.17 3.10 93.68 md1 0.00 0.00 0.00 529.60 0.00 9692.80 18.30 0.00 0.00 0.00 0.00 md0 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 dm-0 0.00 0.00 0.00 0.60 0.00 4.80 8.00 0.00 0.00 0.00 0.00 dm-1 0.00 0.00 0.00 529.00 0.00 9688.00 18.31 24.51 49.91 1.81 95.92 Device: rrqm/s wrqm/s r/s w/s rsec/s wsec/s avgrq-sz avgqu-sz await svctm %util sda 0.00 152.40 0.00 330.60 0.00 5176.00 15.66 0.19 0.57 0.19 6.24 sda1 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 sda2 0.00 152.40 0.00 330.60 0.00 5176.00 15.66 0.19 0.57 0.19 6.24 sdb 0.00 152.40 0.00 326.20 0.00 5118.40 15.69 19.96 55.36 3.01 98.16 sdb1 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 sdb2 0.00 152.40 0.00 326.20 0.00 5118.40 15.69 19.96 55.36 3.01 98.16 md1 0.00 0.00 0.00 482.80 0.00 5166.40 10.70 0.00 0.00 0.00 0.00 md0 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 dm-0 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 dm-1 0.00 0.00 0.00 482.80 0.00 5166.40 10.70 30.19 56.92 2.05 99.04 Device: rrqm/s wrqm/s r/s w/s rsec/s wsec/s avgrq-sz avgqu-sz await svctm %util sda 0.00 181.64 0.00 324.55 0.00 5445.11 16.78 0.15 0.45 0.21 6.87 sda1 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 sda2 0.00 181.64 0.00 324.55 0.00 5445.11 16.78 0.15 0.45 0.21 6.87 sdb 0.00 181.84 0.00 328.54 0.00 5493.01 16.72 18.34 61.57 3.01 99.00 sdb1 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 sdb2 0.00 181.84 0.00 328.54 0.00 5493.01 16.72 18.34 61.57 3.01 99.00 md1 0.00 0.00 0.00 506.39 0.00 5477.05 10.82 0.00 0.00 0.00 0.00 md0 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 dm-0 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 dm-1 0.00 0.00 0.00 506.39 0.00 5477.05 10.82 28.77 62.15 1.96 99.00 And this is completely getting me confused. How come two exactly the same specced drives have such a difference in write speed (see util%)? I haven't really paid attention to those speeds before, so perhaps that something normal -- if someone could confirm I would be really grateful. Otherwise, if someone have seen such behavior again or knows what is causing such behavior I would really appreciate answer. I'll also add that both "smartctl -a" and "hdparm -I" output are exactly the same and are not indicating any hardware problems. The slower drive was changed already two times (to new ones). Also I asked to change the drives with places, and then sda were slower and sdb quicker (so the slow one was the same drive). SATA cables were changed two times already.

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  • MySQL Memory usage

    - by Rob Stevenson-Leggett
    Our MySQL server seems to be using a lot of memory. I've tried looking for slow queries and queries with no index and have halved the peak CPU usage and Apache memory usage but the MySQL memory stays constantly at 2.2GB (~51% of available memory on the server). Here's the graph from Plesk. Running top in the SSH window shows the same figures. Does anyone have any ideas on why the memory usage is constant like this and not peaks and troughs with usage of the app? Here's the output of the MySQL Tuning Primer script: -- MYSQL PERFORMANCE TUNING PRIMER -- - By: Matthew Montgomery - MySQL Version 5.0.77-log x86_64 Uptime = 1 days 14 hrs 4 min 21 sec Avg. qps = 22 Total Questions = 3059456 Threads Connected = 13 Warning: Server has not been running for at least 48hrs. It may not be safe to use these recommendations To find out more information on how each of these runtime variables effects performance visit: http://dev.mysql.com/doc/refman/5.0/en/server-system-variables.html Visit http://www.mysql.com/products/enterprise/advisors.html for info about MySQL's Enterprise Monitoring and Advisory Service SLOW QUERIES The slow query log is enabled. Current long_query_time = 1 sec. You have 6 out of 3059477 that take longer than 1 sec. to complete Your long_query_time seems to be fine BINARY UPDATE LOG The binary update log is NOT enabled. You will not be able to do point in time recovery See http://dev.mysql.com/doc/refman/5.0/en/point-in-time-recovery.html WORKER THREADS Current thread_cache_size = 0 Current threads_cached = 0 Current threads_per_sec = 2 Historic threads_per_sec = 0 Threads created per/sec are overrunning threads cached You should raise thread_cache_size MAX CONNECTIONS Current max_connections = 100 Current threads_connected = 14 Historic max_used_connections = 20 The number of used connections is 20% of the configured maximum. Your max_connections variable seems to be fine. INNODB STATUS Current InnoDB index space = 6 M Current InnoDB data space = 18 M Current InnoDB buffer pool free = 0 % Current innodb_buffer_pool_size = 8 M Depending on how much space your innodb indexes take up it may be safe to increase this value to up to 2 / 3 of total system memory MEMORY USAGE Max Memory Ever Allocated : 2.07 G Configured Max Per-thread Buffers : 274 M Configured Max Global Buffers : 2.01 G Configured Max Memory Limit : 2.28 G Physical Memory : 3.84 G Max memory limit seem to be within acceptable norms KEY BUFFER Current MyISAM index space = 4 M Current key_buffer_size = 7 M Key cache miss rate is 1 : 40 Key buffer free ratio = 81 % Your key_buffer_size seems to be fine QUERY CACHE Query cache is supported but not enabled Perhaps you should set the query_cache_size SORT OPERATIONS Current sort_buffer_size = 2 M Current read_rnd_buffer_size = 256 K Sort buffer seems to be fine JOINS Current join_buffer_size = 132.00 K You have had 16 queries where a join could not use an index properly You should enable "log-queries-not-using-indexes" Then look for non indexed joins in the slow query log. If you are unable to optimize your queries you may want to increase your join_buffer_size to accommodate larger joins in one pass. Note! This script will still suggest raising the join_buffer_size when ANY joins not using indexes are found. OPEN FILES LIMIT Current open_files_limit = 1024 files The open_files_limit should typically be set to at least 2x-3x that of table_cache if you have heavy MyISAM usage. Your open_files_limit value seems to be fine TABLE CACHE Current table_cache value = 64 tables You have a total of 426 tables You have 64 open tables. Current table_cache hit rate is 1% , while 100% of your table cache is in use You should probably increase your table_cache TEMP TABLES Current max_heap_table_size = 16 M Current tmp_table_size = 32 M Of 15134 temp tables, 9% were created on disk Effective in-memory tmp_table_size is limited to max_heap_table_size. Created disk tmp tables ratio seems fine TABLE SCANS Current read_buffer_size = 128 K Current table scan ratio = 2915 : 1 read_buffer_size seems to be fine TABLE LOCKING Current Lock Wait ratio = 1 : 142213 Your table locking seems to be fine The app is a facebook game with about 50-100 concurrent users. Thanks, Rob

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  • Oracle Expands Sun Blade Portfolio for Cloud and Highly Virtualized Environments

    - by Ferhat Hatay
    Oracle announced the expansion of Sun Blade Portfolio for cloud and highly virtualized environments that deliver powerful performance and simplified management as tightly integrated systems.  Along with the SPARC T3-1B blade server, Oracle VM blade cluster reference configuration and Oracle's optimized solution for Oracle WebLogic Suite, Oracle introduced the dual-node Sun Blade X6275 M2 server module with some impressive benchmark results.   Benchmarks on the Sun Blade X6275 M2 server module demonstrate the outstanding performance characteristics critical for running varied commercial applications used in cloud and highly virtualized environments.  These include best-in-class SPEC CPU2006 results with the Intel Xeon processor 5600 series, six Fluent world records and 1.8 times the price-performance of the IBM Power 755 running NAMD, a prominent bio-informatics workload.   Benchmarks for Sun Blade X6275 M2 server module  SPEC CPU2006  The Sun Blade X6275 M2 server module demonstrated best in class SPECint_rate2006 results for all published results using the Intel Xeon processor 5600 series, with a result of 679.  This result is 97% better than the HP BL460c G7 blade, 80% better than the IBM HS22V blade, and 79% better than the Dell M710 blade.  This result demonstrates the density advantage of the new Oracle's server module for space-constrained data centers.     Sun Blade X6275M2 (2 Nodes, Intel Xeon X5670 2.93GHz) - 679 SPECint_rate2006; HP ProLiant BL460c G7 (2.93 GHz, Intel Xeon X5670) - 347 SPECint_rate2006; IBM BladeCenter HS22V (Intel Xeon X5680)  - 377 SPECint_rate2006; Dell PowerEdge M710 (Intel Xeon X5680, 3.33 GHz) - 380 SPECint_rate2006.  SPEC, SPECint, SPECfp reg tm of Standard Performance Evaluation Corporation. Results from www.spec.org as of 11/24/2010 and this report.    For more specifics about these results, please go to see http://blogs.sun.com/BestPerf   Fluent The Sun Fire X6275 M2 server module produced world-record results on each of the six standard cases in the current "FLUENT 12" benchmark test suite at 8-, 12-, 24-, 32-, 64- and 96-core configurations. These results beat the most recent QLogic score with IBM DX 360 M series platforms and QLogic "Truescale" interconnects.  Results on sedan_4m test case on the Sun Blade X6275 M2 server module are 23% better than the HP C7000 system, and 20% better than the IBM DX 360 M2; Dell has not posted a result for this test case.  Results can be found at the FLUENT website.   ANSYS's FLUENT software solves fluid flow problems, and is based on a numerical technique called computational fluid dynamics (CFD), which is used in the automotive, aerospace, and consumer products industries. The FLUENT 12 benchmark test suite consists of seven models that are well suited for multi-node clustered environments and representative of modern engineering CFD clusters. Vendors benchmark their systems with the principal objective of providing comparative performance information for FLUENT software that, among other things, depends on compilers, optimization, interconnect, and the performance characteristics of the hardware.   FLUENT application performance is representative of other commercial applications that require memory and CPU resources to be available in a scalable cluster-ready format.  FLUENT benchmark has six conventional test cases (eddy_417k, turbo_500k, aircraft_2m, sedan_4m, truck_14m, truck_poly_14m) at various core counts.   All information on the FLUENT website (http://www.fluent.com) is Copyrighted1995-2010 by ANSYS Inc. Results as of November 24, 2010. For more specifics about these results, please go to see http://blogs.sun.com/BestPerf   NAMD Results on the Sun Blade X6275 M2 server module running NAMD (a parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems) show up to a 1.8X better price/performance than IBM's Power 7-based system.  For space-constrained environments, the ultra-dense Sun Blade X6275 M2 server module provides a 1.7X better price/performance per rack unit than IBM's system.     IBM Power 755 4-way Cluster (16U). Total price for cluster: $324,212. See IBM United States Hardware Announcement 110-008, dated February 9, 2010, pp. 4, 21 and 39-46.  Sun Blade X6275 M2 8-Blade Cluster (10U). Total price for cluster:  $193,939. Price/performance and performance/RU comparisons based on f1ATPase molecule test results. Sun Blade X6275 M2 cluster: $3,568/step/sec, 5.435 step/sec/RU. IBM Power 755 cluster: $6,355/step/sec, 3.189 step/sec/U. See http://www-03.ibm.com/systems/power/hardware/reports/system_perf.html. See http://www.ks.uiuc.edu/Research/namd/performance.html for more information, results as of 11/24/10.   For more specifics about these results, please go to see http://blogs.sun.com/BestPerf   Reverse Time Migration The Reverse Time Migration is heavily used in geophysical imaging and modeling for Oil & Gas Exploration.  The Sun Blade X6275 M2 server module showed up to a 40% performance improvement over the previous generation server module with super-linear scalability to 16 nodes for the 9-Point Stencil used in this Reverse Time Migration computational kernel.  The balanced combination of Oracle's Sun Storage 7410 system with the Sun Blade X6275 M2 server module cluster showed linear scalability for the total application throughput, including the I/O and MPI communication, to produce a final 3-D seismic depth imaged cube for interpretation. The final image write time from the Sun Blade X6275 M2 server module nodes to Oracle's Sun Storage 7410 system achieved 10GbE line speed of 1.25 GBytes/second or better performance. Between subsequent runs, the effects of I/O buffer caching on the Sun Blade X6275 M2 server module nodes and write optimized caching on the Sun Storage 7410 system gave up to 1.8 GBytes/second effective write performance. The performance results and characterization of this Reverse Time Migration benchmark could serve as a useful measure for many other I/O intensive commercial applications. 3D VTI Reverse Time Migration Seismic Depth Imaging, see http://blogs.sun.com/BestPerf/entry/3d_vti_reverse_time_migration for more information, results as of 11/14/2010.                            

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  • SQLAuthority News – Guest Post – Performance Counters Gathering using Powershell

    - by pinaldave
    Laerte Junior Laerte Junior has previously helped me personally to resolve the issue with Powershell installation on my computer. He did awesome job to help. He has send this another wonderful article regarding performance counter for readers of this blog. I really liked it and I expect all of you who are Powershell geeks, you will like the same as well. As a good DBA, you know that our social life is restricted to a few movies over the year and, when possible, a pizza in a restaurant next to your company’s place, of course. So what we have to do is to create methods through which we can facilitate our daily processes to go home early, and eventually have a nice time with our family (and not sleeping on the couch). As a consultant or fixed employee, one of our daily tasks is to monitor performance counters using Perfmom. To be honest, IDE is getting more complicated. To deal with this, I thought a solution using Powershell. Yes, with some lines of Powershell, you can configure which counters to use. And with one more line, you can already start collecting data. Let’s see one scenario: You are a consultant who has several clients and has just closed another project in troubleshooting an SQL Server environment. You are to use Perfmom to collect data from the server and you already have its XML configuration files made with the counters that you will be using- a file for memory bottleneck f, one for CPU, etc. With one Powershell command line for each XML file, you start collecting. The output of such a TXT file collection is set to up in an SQL Server. With two lines of command for each XML, you make the whole process of data collection. Creating an XML configuration File to Memory Counters: Get-PerfCounterCategory -CategoryName "Memory" | Get-PerfCounterInstance  | Get-PerfCounterCounters |Save-ConfigPerfCounter -PathConfigFile "c:\temp\ConfigfileMemory.xml" -newfile Creating an XML Configuration File to Buffer Manager, counters Page lookups/sec, Page reads/sec, Page writes/sec, Page life expectancy: Get-PerfCounterCategory -CategoryName "SQLServer:Buffer Manager" | Get-PerfCounterInstance | Get-PerfCounterCounters -CounterName "Page*" | Save-ConfigPerfCounter -PathConfigFile "c:\temp\BufferManager.xml" –NewFile Then you start the collection: Set-CollectPerfCounter -DateTimeStart "05/24/2010 08:00:00" -DateTimeEnd "05/24/2010 22:00:00" -Interval 10 -PathConfigFile c:\temp\ConfigfileMemory.xml -PathOutputFile c:\temp\ConfigfileMemory.txt To let the Buffer Manager collect, you need one more counters, including the Buffer cache hit ratio. Just add a new counter to BufferManager.xml, omitting the new file parameter Get-PerfCounterCategory -CategoryName "SQLServer:Buffer Manager" | Get-PerfCounterInstance | Get-PerfCounterCounters -CounterName "Buffer cache hit ratio" | Save-ConfigPerfCounter -PathConfigFile "c:\temp\BufferManager.xml" And start the collection: Set-CollectPerfCounter -DateTimeStart "05/24/2010 08:00:00" -DateTimeEnd "05/24/2010 22:00:00" -Interval 10 -PathConfigFile c:\temp\BufferManager.xml -PathOutputFile c:\temp\BufferManager.txt You do not know which counters are in the Category Buffer Manager? Simple! Get-PerfCounterCategory -CategoryName "SQLServer:Buffer Manager" | Get-PerfCounterInstance | Get-PerfCounterCounters Let’s see one output file as shown below. It is ready to bulk insert into the SQL Server. As you can see, Powershell makes this process incredibly easy and fast. Do you want to see more examples? Visit my blog at Shell Your Experience You can find more about Laerte Junior over here: www.laertejuniordba.spaces.live.com www.simple-talk.com/author/laerte-junior www.twitter.com/laertejuniordba SQL Server Powershell Extension Team: http://sqlpsx.codeplex.com/ Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: SQL, SQL Add-On, SQL Authority, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, SQL Utility, T SQL, Technology Tagged: Powershell

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  • Tuning Red Gate: #3 of Lots

    - by Grant Fritchey
    I'm drilling down into the metrics about SQL Server itself available to me in the Analysis tab of SQL Monitor to see what's up with our two problematic servers. In the previous post I'd noticed that rg-sql01 had quite a few CPU spikes. So one of the first things I want to check there is how much CPU is getting used by SQL Server itself. It's possible we're looking at some other process using up all the CPU Nope, It's SQL Server. I compared this to the rg-sql02 server: You can see that there is a more, consistently low set of CPU counters there. I clearly need to look at rg-sql01 and capture more specific data around the queries running on it to identify which ones are causing these CPU spikes. I always like to look at the Batch Requests/sec on a server, not because it's an indication of a problem, but because it gives you some idea of the load. Just how much is this server getting hit? Here are rg-sql01 and rg-sql02: Of the two, clearly rg-sql01 has a lot of activity. Remember though, that's all this is a measure of, activity. It doesn't suggest anything other than what it says, the number of requests coming in. But it's the kind of thing you want to know in order to understand how the system is used. Are you seeing a correlation between the number of requests and the CPU usage, or a reverse correlation, the number of requests drops as the CPU spikes? See, it's useful. Some of the details you can look at are Compilations/sec, Compilations/Batch and Recompilations/sec. These give you some idea of how the cache is getting used within the system. None of these showed anything interesting on either server. One metric that I like (even though I know it can be controversial) is the Page Life Expectancy. On the average server I expect see a series of mountains as the PLE climbs then drops due to a data load or something along those lines. That's not the case here: Those spikes back in January suggest that the servers weren't really being used much. The PLE on the rg-sql01 seems to be somewhat consistent growing to 3 hours or so then dropping, but the rg-sql02 PLE looks like it might be all over the map. Instead of continuing to look at this high level gathering data view, I'm going to drill down on rg-sql02 and see what it's done for the last week: And now we begin to see where we might have an issue. Memory on this system is getting flushed every 1/2 hour or so. I'm going to check another metric, scans: Whoa! I'm going back to the system real quick to look at some disk information again for rg-sql02. Here is the average disk queue length on the server: and the transfers Right, I think I have a guess as to what's up here. We're seeing memory get flushed constantly and we're seeing lots of scans. The disks are queuing, especially that F drive, and there are lots of requests that correspond to the scans and the memory flushes. In short, we've got queries that are scanning the data, a lot, so we either have bad queries or bad indexes. I'm going back to the server overview for rg-sql02 and check the Top 10 expensive queries. I'm modifying it to show me the last 3 days and the totals, so I'm not looking at some maintenance routine that ran 10 minutes ago and is skewing the results: OK. I need to look into these queries that are getting executed this much. They're generating a lot of reads, but which queries are generating the most reads: Ow, all still going against the same database. This is where I'm going to temporarily leave SQL Monitor. What I want to do is connect up to the server, validate that the Warehouse database is using the F:\ drive (which I'll put money down it is) and then start seeing what's up with these queries. Part 1 of the Series Part 2 of the Series

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  • How do I break down an NSTimeInterval into year, months, days, hours, minutes and seconds on iPhone?

    - by willc2
    I have a time interval that spans years and I want all the time components from year down to seconds. My first thought is to integer divide the time interval by seconds in a year, subtract that from a running total of seconds, divide that by seconds in a month, subtract that from the running total and so on. That just seems convoluted and I've read that whenever you are doing something that looks convoluted, there is probably a built-in method. Is there? I integrated Alex's 2nd method into my code. It's in a method called by a UIDatePicker in my interface. NSDate *now = [NSDate date]; NSDate *then = self.datePicker.date; NSTimeInterval howLong = [now timeIntervalSinceDate:then]; NSDate *date = [NSDate dateWithTimeIntervalSince1970:howLong]; NSString *dateStr = [date description]; const char *dateStrPtr = [dateStr UTF8String]; int year, month, day, hour, minute, sec; sscanf(dateStrPtr, "%d-%d-%d %d:%d:%d", &year, &month, &day, &hour, &minute, &sec); year -= 1970; NSLog(@"%d years\n%d months\n%d days\n%d hours\n%d minutes\n%d seconds", year, month, day, hour, minute, sec); When I set the date picker to a date 1 year and 1 day in the past, I get: 1 years 1 months 1 days 16 hours 0 minutes 20 seconds which is 1 month and 16 hours off. If I set the date picker to 1 day in the past, I am off by the same amount. Update: I have an app that calculates your age in years, given your birthday (set from a UIDatePicker), yet it was often off. This proves there was an inaccuracy, but I can't figure out where it comes from, can you?

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  • How would i down-sample a .wav file then reconstruct it using nyquist? - in matlab [closed]

    - by martin
    Possible Duplicate: How would i down-sample a .wav file then reconstruct it using nyquist? - in matlab This is all done in MatLab 2010 My objective is to show the results of: undersampling, nyquist rate/ oversampling First i need to downsample the .wav file to get an incomplete/ or impartial data stream that i can then reconstuct. Heres the flow chart of what im going to be doing So the flow is analog signal - sampling analog filter - ADC - resample down - resample up - DAC - reconstruction analog filter what needs to be achieved: F= Frequency F(Hz=1/s) E.x. 100Hz = 1000 (Cyc/sec) F(s)= 1/(2f) Example problem: 1000 hz = Highest frequency 1/2(1000hz) = 1/2000 = 5x10(-3) sec/cyc or a sampling rate of 5ms This is my first signal processing project using matlab. what i have so far. % Fs = frequency sampled (44100hz or the sampling frequency of a cd) [test,fs]=wavread('test.wav'); % loads the .wav file left=test(:,1); % Plot of the .wav signal time vs. strength time=(1/44100)*length(left); t=linspace(0,time,length(left)); plot(t,left) xlabel('time (sec)'); ylabel('relative signal strength') **%this is were i would need to sample it at the different frequecys (both above and below and at) nyquist frequency.*I think.*** soundsc(left,fs) % shows the resaultant audio file , which is the same as original ( only at or above nyquist frequency however) Can anyone tell me how to make it better, and how to do the various sampling at different frequencies?

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  • .NET assembly cache / ngen / jit image warm-up and cool-down behavior

    - by Mike Jiang
    Hi, I have an Input Method (IME) program built with C#.NET 2.0 DLL through C++/CLI. Since an IME is always attaching to another application, the C#.NET DLL seems not able to avoid image address rebasing. Although I have applied ngen to create a native image of that C#.NET 2.0 DLL and installed it into Global Assembly Cache, it didn't improved much, approximately 12 sec. down to 9 sec. on a slow PIII level PC. Therefore I uses a small application, which loads all the components referenced by the C#.NET DLL at the boot up time, to "warm up" the native image of that DLL. It works fine to speed up the loading time to 0.5 sec. However, it only worked for a while. About 30 min. later, it seems to "cool down" again. Is there any way to control the behavior of GAC or native image to be always "hot"? Is this exactly a image address rebasing problem? Thank you for your precious time. Sincerely, Mike

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  • Blackberry stopwatch implementation

    - by Michaela
    I'm trying to write a blackberry app that is basically a stopwatch, and displays lap times. First, I'm not sure I'm implementing the stopwatch functionality in the most optimal way. I have a LabelField (_myLabel) that displays the 'clock' - starting at 00:00. Then you hit the start button and every second the _myLabel field gets updated with how many seconds have past since the last update (should only ever increment by 1, but sometimes there is a delay and it will skip a number). I just can't think of a different way to do it - and I am new to GUI development and threads so I guess that's why. EDIT: Here is what calls the stopwatch: _timer = new Timer(); _timer.schedule(new MyTimerTask(), 250, 250); And here is the TimerTask: class MyTimerTask extends TimerTask { long currentTime; long startTime = System.currentTimeMillis(); public void run() { synchronized (Application.getEventLock()) { currentTime = System.currentTimeMillis(); long diff = currentTime - startTime; long min = diff / 60000; long sec = (diff % 60000) / 1000; String minStr = new Long(min).toString(); String secStr = new Long(sec).toString(); if (min < 10) minStr = "0" + minStr; if (sec < 10) secStr = "0" + secStr; _myLabel.setText(minStr + ":" + secStr); timerDisplay.deleteAll(); timerDisplay.add(_timerLabel); } } } Anyway when you stop the stopwatch it updates a historical table of lap time data. When this list gets long, the timer starts to degrade. If you try to scroll, then it gets really bad. Is there a better way to implement my stopwatch?

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  • Loading through Ajax request and bookmarked URL

    - by Varun
    I am working on a ticket system, having the following requirement: The home page is divided into two sections: Sec-1. Some filter options are shown here.(like closed-tickets, open-tickets, all-tickets, tickets-assigned-to-me etc.). You can select one or more of these filters. sec-2. List of tickets satisfying above filters will be displayed here. Now this is what I want: As I change the filters -- the change should be reflected in the URL, so that one is able to bookmark it. -- an ajax request will go and list of tickets satisfying the selected filters will be updated in sec-2. I want the same code to be used to load the tickets in both ways- (a) by selecting that set of filters and (b) by using the bookmark to reload the page. I have little idea on how to do it: The URL will contain the selected filters.(appended after #) changing filters on the page will modify the hash part of URL and call a function (say ajaxHandler()) to parse the URL to get the filters and then make an ajax request to get the list of tickets to be displayed in section2. and I will call the same function ajaxHandler() in window.onload. Is this the way? Any suggestions?

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  • Gmail like URL scheme

    - by Varun
    I am working on a ticket system, having the following requirement: The home page is divided into two sections: Sec-1. Some filter options are shown here.(like closed-tickets, open-tickets, all-tickets, tickets-assigned-to-me etc.). You can select one or more of these filters. sec-2. List of tickets satisfying above filters will be displayed here. Now this is what I want: As I change the filters -- the change should be reflected in the URL, so that one is able to bookmark it. -- an ajax request will go and list of tickets satisfying the selected filters will be updated in sec-2. I want the same code to be used to load the tickets in both ways- (a) by selecting that set of filters and (b) by using the bookmark to reload the page. I have little idea on how to do it: The URL will contain the selected filters.(appended after #) changing filters on the page will modify the hash part of URL and call a function (say ajaxHandler()) to parse the URL to get the filters and then make an ajax request to get the list of tickets to be displayed in section2. and I will call the same function ajaxHandler() in window.onload. I feel this is what Yahoo maps does. What's the best way to implement such URL scheme? Am I headed in the right direction?

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  • Getting percentage of "Count(*)" to the number of all items in "GROUP BY"

    - by celalo
    Let's say I need to have the ratio of "number of items available from certain category" to "the the number of all items". Please consider a MySQL table like this: /* mysql> select * from Item; +----+------------+----------+ | ID | Department | Category | +----+------------+----------+ | 1 | Popular | Rock | | 2 | Classical | Opera | | 3 | Popular | Jazz | | 4 | Classical | Dance | | 5 | Classical | General | | 6 | Classical | Vocal | | 7 | Popular | Blues | | 8 | Popular | Jazz | | 9 | Popular | Country | | 10 | Popular | New Age | | 11 | Popular | New Age | | 12 | Classical | General | | 13 | Classical | Dance | | 14 | Classical | Opera | | 15 | Popular | Blues | | 16 | Popular | Blues | +----+------------+----------+ 16 rows in set (0.03 sec) mysql> SELECT Category, COUNT(*) AS Total -> FROM Item -> WHERE Department='Popular' -> GROUP BY Category; +----------+-------+ | Category | Total | +----------+-------+ | Blues | 3 | | Country | 1 | | Jazz | 2 | | New Age | 2 | | Rock | 1 | +----------+-------+ 5 rows in set (0.02 sec) */ What I need is basically a result set resembles this one: /* +----------+-------+-----------------------------+ | Category | Total | percentage to the all items | (Note that number of all available items is "9") +----------+-------+-----------------------------+ | Blues | 3 | 33 | (3/9)*100 | Country | 1 | 11 | (1/9)*100 | Jazz | 2 | 22 | (2/9)*100 | New Age | 2 | 22 | (2/9)*100 | Rock | 1 | 11 | (1/9)*100 +----------+-------+-----------------------------+ 5 rows in set (0.02 sec) */ How can I achieve such a result set in a single query? Thanks in advance.

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  • Object not declared in scope

    - by jay
    I'm using Xcode for C++ on my computer while using Visual Studio at school. The following code worked just fine in Visual Studio, but I'm having this problem when using Xcode. clock c1(2, 3, 30); Everything works just fine, but it keeps giving me this error that says "Expected ';' before 'c1'" Fine, I put the ';' .. but then, it gives me this error: "'c1' was not declared in this scope" Here's the whole header code: #include <iostream> using namespace std; class clock { private: int h; int m; int s; public: clock(int hr, int mn, int sec); }; clock::clock(int hr, int mn, int sec) { h = hr; m = mn; s = sec; } Here's the whole .cpp code: #include "clock.h" int main() { clock c1(2, 3, 30); return 0; } I stripped everything down to where I had the problem. Everything else, as far as I know, is irrelevant since the problem remains the same with just the mentioned above. Thanks in advance!

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  • JQuery idleTimeout plugin: How to display the dialog after the session is timedout on ASP.NET MVC Pa

    - by Rita
    Hi I am working on migrating the ASP.NET apllication to MVC Framework. I have implemented session timeout for InActiveUser using JQuery idleTimeout plugin. I have set idletime for 30 min as below in my Master Page. So that After the user session is timedout of 30 Min, an Auto Logout dialog shows for couple of seconds and says that "You are about to be signed out due to Inactivity" Now after this once the user is logged out and redirected to Home Page. Here i again want to show a Dialog and should stay there saying "You are Logged out" until the user clicks on it. Here is my code in Master page: $(document).ready(function() { var SEC = 1000; var MIN = 60 * SEC; // http://philpalmieri.com/2009/09/jquery-session-auto-timeout-with-prompt/ <% if(HttpContext.Current.User.Identity.IsAuthenticated) {%> $(document).idleTimeout({ inactivity: 30 * MIN, noconfirm : 30 * SEC, redirect_url: '/Account/Logout', sessionAlive: 0, // 30000, //10 Minutes click_reset: true, alive_url: '', logout_url: '' }); <%} %> } Logout() Method in Account Controller: public virtual ActionResult Logout() { FormsAuthentication.SignOut(); return RedirectToAction(MVC.Home.Default()); } Appreciate your responses.

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  • what webserver / mod / technique should I use to serve everything from memory?

    - by reinier
    I've lots of lookuptables from which I'll generate my webresponse. I think IIS with Asp.net enables me to keep static lookuptables in memory which I can use to serve up my responses very fast. Are there however also non .net solutions which can do the same? I've looked at fastcgi, but I think this starts X processes, of which anyone can handle Y requests. But the processes are by definition shielded from eachother. I could configure fastcgi to use just 1 process, but does this have scalability implications? anything using PHP or any other interpreted language won't fly because it is also cgi or fastcgi bound right? I understand memcache could be an option, though this would require another (local) socket connection which I'd rather avoid since everything in memory would be much faster. The solution can work under WIndows or Unix... it doesn't matter too much. The only thing which matters is that there will be a lot of requests (100/sec now and growing to 500/sec in a year), and I want to reduce the amount of webservers needed to process it. The current solution is done using PHP and memcache (and the occasional hit to the SQL server backend). Although it is fast (for php anyway), Apache has real problems when the 50/sec is passed. I've put a bounty on this question since I've not seen enough responses to make a wise choice. At the moment I'm considering either Asp.net or fastcgi with C(++).

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  • Debug NAudio MP3 reading difference?

    - by Conrad Albrecht
    My code using NAudio to read one particular MP3 gets different results than several other commercial apps. Specifically: My NAudio-based code finds ~1.4 sec of silence at the beginning of this MP3 before "audible audio" (a drum pickup) starts, whereas other apps (Windows Media Player, RealPlayer, WavePad) show ~2.5 sec of silence before that same drum pickup. The particular MP3 is "Like A Rolling Stone" downloaded from Amazon.com. Tested several other MP3s and none show any similar difference between my code and other apps. Most MP3s don't start with such a long silence so I suspect that's the source of the difference. Debugging problems: I can't actually find a way to even prove that the other apps are right and NAudio/me is wrong, i.e. to compare block-by-block my code's results to a "known good reference implementation"; therefore I can't even precisely define the "error" I need to debug. Since my code reads thousands of samples during those 1.4 sec with no obvious errors, I can't think how to narrow down where/when in the input stream to look for a bug. The heart of the NAudio code is a P/Invoke call to acmStreamConvert(), which is a Windows "black box" call which I can't think how to error-check. Can anyone think of any tricks/techniques to debug this?

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  • Improve Application Performace

    - by Gtest
    Hello, Want To Improvide Performace Of C#.Net Applicaiton.. In My Application I am using Third Party Interop/Dll To Process .doc Files. It's a Simple Operation, Which Pass Input/Output FilePath to Interop dll ...& dll will execute text form input file. To Improve Performace I have Tried, Execute 2 therad to process 32 files.(each Thread process 16 files) Execute application code by creating 2 new AppDomains(each AppDomain Code process 16 files) Execute Code Using TPL(Task Parellel Library) But all options take around same time (32 sec) to process 32 files.Manually process tooks same 32 sec to process 32 files. Just tried one thing ..when i have created sample exe to process 16 files as input & output for refrence PAth given in TextBox. ..I open 2 exe instance to process. 1 exe has differnt 16 input files & output Created with input file path 2 exe has differnt 16 input files & output Created with input file path When i click on start button of both exe ..it use 100% cpu & Utilize both core significantly & Process Completed within 16 sec for 32 files. Can we provide this kind of explicit prallism to Improve my applicaiton Peformace? Thanks.

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