Search Results

Search found 13151 results on 527 pages for 'performance counters'.

Page 160/527 | < Previous Page | 156 157 158 159 160 161 162 163 164 165 166 167  | Next Page >

  • Speed up math code in C# by writing a C dll?

    - by Projectile Fish
    I have a very large nested for loop in which some multiplications and additions are performed on floating point numbers. for (int i = 0; i < length1; i++) { s = GetS(i); c = GetC(i); for(int j = 0; j < length2; j++) { double oldU = u[j]; u[j] = c * oldU + s * omega[i][j]; omega[i][j] = c * omega[i][j] - s * oldU; } } This loop is taking up the majority of my processing time and is a bottleneck. Would I be likely to see any speed improvements if I rewrite this loop in C and interface to it from C#?

    Read the article

  • one two-directed tcp socket OR two one-directed? (linux, high volume, low latency)

    - by osgx
    Hello I need to send (interchange) a high volume of data periodically with the lowest possible latency between 2 machines. The network is rather fast (e.g. 1Gbit or even 2G+). Os is linux. Is it be faster with using 1 tcp socket (for send and recv) or with using 2 uni-directed tcp sockets? The test for this task is very like NetPIPE network benchmark - measure latency and bandwidth for sizes from 2^1 up to 2^13 bytes, each size sent and received 3 times at least (in teal task the number of sends is greater. both processes will be sending and receiving, like ping-pong maybe). The benefit of 2 uni-directed connections come from linux: http://lxr.linux.no/linux+v2.6.18/net/ipv4/tcp_input.c#L3847 3847/* 3848 * TCP receive function for the ESTABLISHED state. 3849 * 3850 * It is split into a fast path and a slow path. The fast path is 3851 * disabled when: ... 3859 * - Data is sent in both directions. Fast path only supports pure senders 3860 * or pure receivers (this means either the sequence number or the ack 3861 * value must stay constant) ... 3863 * 3864 * When these conditions are not satisfied it drops into a standard 3865 * receive procedure patterned after RFC793 to handle all cases. 3866 * The first three cases are guaranteed by proper pred_flags setting, 3867 * the rest is checked inline. Fast processing is turned on in 3868 * tcp_data_queue when everything is OK. All other conditions for disabling fast path is false. And only not-unidirected socket stops kernel from fastpath in receive

    Read the article

  • How do I make this nested for loop, testing sums of cubes, more efficient?

    - by Brian J. Fink
    I'm trying to iterate through all the combinations of pairs of positive long integers in Java and testing the sum of their cubes to discover if it's a Fibonacci number. I'm currently doing this by using the value of the outer loop variable as the inner loop's upper limit, with the effect being that the outer loop runs a little slower each time. Initially it appeared to run very quickly--I was up to 10 digits within minutes. But now after 2 full days of continuous execution, I'm only somewhere in the middle range of 15 digits. At this rate it may end up taking a whole year just to finish running this program. The code for the program is below: import java.lang.*; import java.math.*; public class FindFib { public static void main(String args[]) { long uLimit=9223372036854775807L; //long maximum value BigDecimal PHI=new BigDecimal(1D+Math.sqrt(5D)/2D); //Golden Ratio for(long a=1;a<=uLimit;a++) //Outer Loop, 1 to maximum for(long b=1;b<=a;b++) //Inner Loop, 1 to current outer { //Cube the numbers and add BigDecimal c=BigDecimal.valueOf(a).pow(3).add(BigDecimal.valueOf(b).pow(3)); System.out.print(c+" "); //Output result //Upper and lower limits of interval for Mobius test: [c*PHI-1/c,c*PHI+1/c] BigDecimal d=c.multiply(PHI).subtract(BigDecimal.ONE.divide(c,BigDecimal.ROUND_HALF_UP)), e=c.multiply(PHI).add(BigDecimal.ONE.divide(c,BigDecimal.ROUND_HALF_UP)); //Mobius test: if integer in interval (floor values unequal) Fibonacci number! if (d.toBigInteger().compareTo(e.toBigInteger())!=0) System.out.println(); //Line feed else System.out.print("\r"); //Carriage return instead } //Display final message System.out.println("\rDone. "); } } Now the use of BigDecimal and BigInteger was delibrate; I need them to get the necessary precision. Is there anything other than my variable types that I could change to gain better efficiency?

    Read the article

  • Jmeter- HTTP Cache Manager, Unable to cache everything what it is being cached by Browser

    - by chinmay brahma
    I used HTTP Chache Manager to Cache files which are being cached in browser. I am successful of doing it for some of the pages. Number of files being cached in Jmeter is equal to Number of files being cached by browser. But in some cases : I found number files being cached is lesser than the files being cached by browser. Using Jmeter I found only 5 files are being cached but in real browser 12 files are getting cached. Thanks in advance

    Read the article

  • Measuring debug vs release of ASP.NET applications

    - by Alex Angas
    A question at work came up about building ASP.NET applications in release vs debug mode. When researching further (particularly on SO), general advice is that setting <compilation debug="true"> in web.config has a much bigger impact. Has anyone done any testing to get some actual numbers about this? Here's the sort of information I'm looking for (which may give away my experience with testing such things): Execution time | Debug build | Release build -------------------+---------------+--------------- Debug web.config | average 1 | average 2 Retail web.config | average 3 | average 4 Max memory usage | Debug build | Release build -------------------+---------------+--------------- Debug web.config | average 1 | average 2 Retail web.config | average 3 | average 4 Output file size | Debug build | Release build -------------------+---------------+--------------- | size 1 | size 2

    Read the article

  • Preventing a heavy process from sinking in the swap file

    - by eran
    Our service tends to fall asleep during the nights on our client's server, and then have a hard time waking up. What seems to happen is that the process heap, which is sometimes several hundreds of MB, is moved to the swap file. This happens at night, when our service is not used, and others are scheduled to run (DB backups, AV scans etc). When this happens, after a few hours of inactivity the first call to the service takes up to a few minutes (consequent calls take seconds). I'm quite certain it's an issue of virtual memory management, and I really hate the idea of forcing the OS to keep our service in the physical memory. I know doing that will hurt other processes on the server, and decrease the overall server throughput. Having that said, our clients just want our app to be responsive. They don't care if nightly jobs take longer. I vaguely remember there's a way to force Windows to keep pages on the physical memory, but I really hate that idea. I'm leaning more towards some internal or external watchdog that will initiate higher-level functionalities (there is already some internal scheduler that does very little, and makes no difference). If there were a 3rd party tool that provided that kind of service is would have been just as good. I'd love to hear any comments, recommendations and common solutions to this kind of problem. The service is written in VC2005 and runs on Windows servers.

    Read the article

  • What limits scaling in this simple OpenMP program?

    - by Douglas B. Staple
    I'm trying to understand limits to parallelization on a 48-core system (4xAMD Opteron 6348, 2.8 Ghz, 12 cores per CPU). I wrote this tiny OpenMP code to test the speedup in what I thought would be the best possible situation (the task is embarrassingly parallel): // Compile with: gcc scaling.c -std=c99 -fopenmp -O3 #include <stdio.h> #include <stdint.h> int main(){ const uint64_t umin=1; const uint64_t umax=10000000000LL; double sum=0.; #pragma omp parallel for reduction(+:sum) for(uint64_t u=umin; u<umax; u++) sum+=1./u/u; printf("%e\n", sum); } I was surprised to find that the scaling is highly nonlinear. It takes about 2.9s for the code to run with 48 threads, 3.1s with 36 threads, 3.7s with 24 threads, 4.9s with 12 threads, and 57s for the code to run with 1 thread. Unfortunately I have to say that there is one process running on the computer using 100% of one core, so that might be affecting it. It's not my process, so I can't end it to test the difference, but somehow I doubt that's making the difference between a 19~20x speedup and the ideal 48x speedup. To make sure it wasn't an OpenMP issue, I ran two copies of the program at the same time with 24 threads each (one with umin=1, umax=5000000000, and the other with umin=5000000000, umax=10000000000). In that case both copies of the program finish after 2.9s, so it's exactly the same as running 48 threads with a single instance of the program. What's preventing linear scaling with this simple program?

    Read the article

  • Fastest XML parser for small, simple documents in Java

    - by Varkhan
    I have to objectify very simple and small XML documents (less than 1k, and it's almost SGML: no namespaces, plain UTF-8, you name it...), read from a stream, in Java. I am using JAXP to process the data from my stream into a Document object. I have tried Xerces, it's way too big and slow... I am using Dom4j, but I am still spending way too much time in org.dom4j.io.SAXReader. Does anybody out there have any suggestion on a faster, more efficient implementation, keeping in mind I have very tough CPU and memory constraints? [Edit 1] Keep in mind that my documents are very small, so the overhead of staring the parser can be important. For instance I am spending as much time in org.xml.sax.helpers.XMLReaderFactory.createXMLReader as in org.dom4j.io.SAXReader.read [Edit 2] The result has to be in Dom format, as I pass the document to decision tools that do arbitrary processing on it, like switching code based on the value of arbitrary XPaths, but also extracting lists of values packed as children of a predefined node. [Edit 3] In any case I eventually need to load/parse the complete document, since all the information it contains is going to be used at some point. (This question is related to, but different from, http://stackoverflow.com/questions/373833/best-xml-parser-for-java )

    Read the article

  • Are closures in javascript recompiled

    - by Discodancer
    Let's say we have this code (forget about prototypes for a moment): function A(){ var foo = 1; this.method = function(){ return foo; } } var a = new A(); is the inner function recompiled each time the function A is run? Or is it better (and why) to do it like this: function method = function(){ return this.foo; } function A(){ this.foo = 1; this.method = method; } var a = new A(); Or are the javascript engines smart enough not to create a new 'method' function every time? Specifically Google's v8 and node.js. Also, any general recommendations on when to use which technique are welcome. In my specific example, it really suits me to use the first example, but I know thath the outer function will be instantiated many times.

    Read the article

  • Database structure for ecommerce site

    - by imanc
    Hey Guys, I have been tasked with designing an ecommerce solution. The aspect that is causing me the most problems is the database. Currently the site consists of 10+ country based shops each with their own database (all residing on the same mysql instance). For the new site I'd rather all these shop databases be merged into one database so that all tables (products, orders, customers etc.) have a shop_id field. From a programming perspective this seems to make the most sense as we won't have to manage data across multiple databases. Currently the entire site generates about 120k orders a year, but is experiencing fairly heavy growth and we need to design a solution that will scale. In 5 years there may be more than a million orders per year and a database that contains 5 years order history (archiving maybe a solution here). The question is - do we use a single database, or do we keep the database-per-shop structure? I am currently trying to find supporting evidence for either avenue. The company I am designing the solution for prefer the per-shop database structure because they believe it will allow the sites to scale. But my argument is that the shop's database probably won't get that busy over the next few years that they exceed the capacity of a mysql database and a "no expenses spared" hardware set-up. I am wondering if anyone has any advice either way? Does anyone have experience with websites / ecommerce sites that have tables containing millions of records? I know there is probably not a clear answer here, but at what stage do we have too many records or too large table files to have a fast loading site? Also, if anyone has any advice on sources of information - books, websites, etc. where I can do further research, it would be highly appreciated! Cheers, imanc

    Read the article

  • oprofile unable to produce call graph

    - by aaa
    hello I am trying to use oprofile to generate call graph. Compiler is g++, platform is linux x86-64, linker is gfortran C++ code is compiled with -fno- omit-frame-pointer. oprofile is started with --callgraph=25. report I run with --callgraph. the call graph is produced but it's only includes self time, which is not much use what am I missing?

    Read the article

  • one two-directed tcp socket of two one-directed? (linux, high volume, low latency)

    - by osgx
    Hello I need to send (interchange) a high volume of data periodically with the lowest possible latency between 2 machines. The network is rather fast (e.g. 1Gbit or even 2G+). Os is linux. Is it be faster with using 1 tcp socket (for send and recv) or with using 2 uni-directed tcp sockets? The test for this task is very like NetPIPE network benchmark - measure latency and bandwidth for sizes from 2^1 up to 2^13 bytes, each size sent and received 3 times at least (in teal task the number of sends is greater. both processes will be sending and receiving, like ping-pong maybe). The benefit of 2 uni-directed connections come from linux: http://lxr.linux.no/linux+v2.6.18/net/ipv4/tcp_input.c#L3847 3847/* 3848 * TCP receive function for the ESTABLISHED state. 3849 * 3850 * It is split into a fast path and a slow path. The fast path is 3851 * disabled when: ... 3859 * - Data is sent in both directions. Fast path only supports pure senders 3860 * or pure receivers (this means either the sequence number or the ack 3861 * value must stay constant) ... 3863 * 3864 * When these conditions are not satisfied it drops into a standard 3865 * receive procedure patterned after RFC793 to handle all cases. 3866 * The first three cases are guaranteed by proper pred_flags setting, 3867 * the rest is checked inline. Fast processing is turned on in 3868 * tcp_data_queue when everything is OK. All other conditions for disabling fast path is false. And only not-unidirected socket stops kernel from fastpath in receive

    Read the article

  • How to get the size of a binary tree ?

    - by Andrei Ciobanu
    I have a very simple binary tree structure, something like: struct nmbintree_s { unsigned int size; int (*cmp)(const void *e1, const void *e2); void (*destructor)(void *data); nmbintree_node *root; }; struct nmbintree_node_s { void *data; struct nmbintree_node_s *right; struct nmbintree_node_s *left; }; Sometimes i need to extract a 'tree' from another and i need to get the size to the 'extracted tree' in order to update the size of the initial 'tree' . I was thinking on two approaches: 1) Using a recursive function, something like: unsigned int nmbintree_size(struct nmbintree_node* node) { if (node==NULL) { return(0); } return( nmbintree_size(node->left) + nmbintree_size(node->right) + 1 ); } 2) A preorder / inorder / postorder traversal done in an iterative way (using stack / queue) + counting the nodes. What approach do you think is more 'memory failure proof' / performant ? Any other suggestions / tips ? NOTE: I am probably going to use this implementation in the future for small projects of mine. So I don't want to unexpectedly fail :).

    Read the article

  • Effecient data structure design

    - by Sway
    Hi there, I need to match a series of user inputed words against a large dictionary of words (to ensure the entered value exists). So if the user entered: "orange" it should match an entry "orange' in the dictionary. Now the catch is that the user can also enter a wildcard or series of wildcard characters like say "or__ge" which would also match "orange" The key requirements are: * this should be as fast as possible. * use the smallest amount of memory to achieve it. If the size of the word list was small I could use a string containing all the words and use regular expressions. however given that the word list could contain potentially hundreds of thousands of enteries I'm assuming this wouldn't work. So is some sort of 'tree' be the way to go for this...? Any thoughts or suggestions on this would be totally appreciated! Thanks in advance, Matt

    Read the article

  • How to not over-use jQuery?

    - by Fedyashev Nikita
    Typical jQuery over-use: $('button').click(function() { alert('Button clicked: ' + $(this).attr('id')); }); Which can be simplified to: $('button').click(function() { alert('Button clicked: ' + this.id); }); Which is way faster. Can you give me any more examples of similar jQuery over-use?

    Read the article

  • integer division in php

    - by oezi
    hi guys, i'm looking for the fastest way to do an integer division in php. for example, 5 / 2 schould be 4 | 6 / 2 should be 3 and so on. if i simply do this, php will return 2.5 in the first case, the only solution i could find was using intval($my_number/2) - wich isn't as fast as i want it to be (but gives the expected results). can anyone help me out with this?

    Read the article

  • Creating C++ client app for some abstract windows server - how to manage TCP connection to server speed?

    - by Kabumbus
    So we have some server with some address port and ip. we are developing that server so we can implement on it what ever we need for help. What are standard/best practices for data transfer speed management between C++ windows client app and server (C++)? My main point is in how to get how much data can be uploaded/downloaded from/to client via his low speed network to my relatively super fast server. (I need it for set up of his live stream Audio/Video bit rate) My try on explaining number 3. We do not care how fast is our server. It is always faster than needed. We care about client tyring to stream out to our server his media. he streams encoded (via ffmpeg) live video data to our server. But he has say ADSL with 500kb/s of outgoing traffic. Also he uses some ICQ or what so ever so he has less than 500 kb/s per second. And he wants to stream live video! So we need to set up our ffmpeg to encode video with respect to the bit rate user can provide. We develop server side and client side. We need a way of finding out how much user can upload per second currently (so value can change dynamically over time)

    Read the article

  • Tracking down slow managed DLL loading

    - by Alex K
    I am faced with the following issue and at this point I feel like I'm severely lacking some sort of tool, I just don't know what that tool is, or what exactly it should be doing. Here is the setup: I have a 3rd party DLL that has to be registered in GAC. This all works fine and good on pretty much every machine our software was deployed on before. But now we got 2 machines, seemingly identical to the ones we know work (they are cloned from the same image and stuffed with the same hardware, so pretty much the only difference is software settings, over which I went over and over, and they seem fine). Now the problem, the DLL in GAC takes a very long time to load. At least I believe this is the issue, what I can say definitively is that instantiating a single class from that DLL is the slow part. Once it is loaded, thing fly as they always have. But while on known-good machines the DLL loads so fast that a timestamp in the log doesn't even change, on these 2 machines it take over 1min to load. Knowns: I have no access to the source, so I can't debug through the DLL. Our app is the only one that uses it (so shouldn't be simultaneous access issues). There is only one version of this DLL in existance, so it shouldn't be a matter of version conflict. The GAC reference is being used (if I uninstall the DLL from GAC, an exception will be thrown about the missing GAC reference). Could someone with a greater skill in debug-fu suggest what I can do to track down the root cause of this issue?

    Read the article

  • Reasonably faster way to traverse a directory tree in Python?

    - by Sridhar Ratnakumar
    Assuming that the given directory tree is of reasonable size: say an open source project like Twisted or Python, what is the fastest way to traverse and iterate over the absolute path of all files/directories inside that directory? I want to do this from within Python (subprocess is allowed). os.path.walk is slow. So I tried ls -lR and tree -fi. For a project with about 8337 files (including tmp, pyc, test, .svn files): $ time tree -fi > /dev/null real 0m0.170s user 0m0.044s sys 0m0.123s $ time ls -lR > /dev/null real 0m0.292s user 0m0.138s sys 0m0.152s $ time find . > /dev/null real 0m0.074s user 0m0.017s sys 0m0.056s $ tree appears to be faster than ls -lR (though ls -R is faster than tree, but it does not give full paths). find is the fastest. Can anyone think of a faster and/or better approach? On Windows, I may simply ship a 32-bit binary tree.exe or ls.exe if necessary. Update 1: Added find

    Read the article

  • What's the good of IDE's auto generated @override annotation ?

    - by Tony
    I am using eclipse , when I use shortcut to generate override implementations , there is an override annotation up there , I am using JDK 6 , this is all right , but under JDK 5 this annotation will cause an error, so I want to ask , if this annotation is completely useless ? Will compiler do some kind of optimization using this annotation ?

    Read the article

  • SQL Server uncorrelated subquery very slow

    - by brianberns
    I have a simple, uncorrelated subquery that performs very poorly on SQL Server. I'm not very experienced at reading execution plans, but it looks like the inner query is being executed once for every row in the outer query, even though the results are the same each time. What can I do to tell SQL Server to execute the inner query only once? The query looks like this: select * from Record record0_ where record0_.RecordTypeFK='c2a0ffa5-d23b-11db-9ea3-000e7f30d6a2' and ( record0_.EntityFK in ( select record1_.EntityFK from Record record1_ join RecordTextValue textvalues2_ on record1_.PK=textvalues2_.RecordFK and textvalues2_.FieldFK = '0d323c22-0ec2-11e0-a148-0018f3dde540' and (textvalues2_.Value like 'O%' escape '~') ) )

    Read the article

  • Best practice for handling memory leaks in large Java projects?

    - by knorv
    In almost all larger Java projects I've been involved with I've noticed that the quality of service of the application degrades with the uptime of the container. This is most probably due to memory leaks in the code. The correct way to solve this problem is obviously to trace back to the root cause of the problem and fix the leaks in the code. The quick and dirty way of solving the problem is simply restarting Tomcat (or whichever servlet container you're using). These are my three questions: Assume that you choose to solve the problem by tracing the root cause of the problem (the memory leaks), how would you collect data to zoom in on the problem? Assume that you choose the quick and dirty way of speeding things up by simply restarting the container, how would you collect data to choose the optimal restart cycle? Have you been able to deploy and run projects over an extended period of time without ever restarting the servlet container to regain snappiness? Or is an occasional servlet restart something that one has to simply accept?

    Read the article

< Previous Page | 156 157 158 159 160 161 162 163 164 165 166 167  | Next Page >