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  • Are indivisible operations still indivisible on multiprocessor and multicore systems?

    - by Steve314
    As per the title, plus what are the limitations and gotchas. For example, on x86 processors, alignment for most data types is optional - an optimisation rather than a requirement. That means that a pointer may be stored at an unaligned address, which in turn means that pointer might be split over a cache page boundary. Obviously this could be done if you work hard enough on any processor (picking out particular bytes etc), but not in a way where you'd still expect the write operation to be indivisible. I seriously doubt that a multicore processor can ensure that other cores can guarantee a consistent all-before or all-after view of a written pointer in this unaligned-write-crossing-a-page-boundary situation. Am I right? And are there any similar gotchas I haven't thought of?

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  • Python: how to run several scripts (or functions) at the same time under windows 7 multicore processor 64bit

    - by Gianni
    sorry for this question because there are several examples in Stackoverflow. I am writing in order to clarify some of my doubts because I am quite new in Python language. i wrote a function: def clipmyfile(inFile,poly,outFile): ... # doing something with inFile and poly and return outFile Normally I do this: clipmyfile(inFile="File1.txt",poly="poly1.shp",outFile="res1.txt") clipmyfile(inFile="File2.txt",poly="poly2.shp",outFile="res2.txt") clipmyfile(inFile="File3.txt",poly="poly3.shp",outFile="res3.txt") ...... clipmyfile(inFile="File21.txt",poly="poly21.shp",outFile="res21.txt") I had read in this example Run several python programs at the same time and i can use (but probably i wrong) from multiprocessing import Pool p = Pool(21) # like in your example, running 21 separate processes to run the function in the same time and speed my analysis I am really honest to say that I didn't understand the next step. Thanks in advance for help and suggestion Gianni

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  • Optimal Sharing of heavy computation job using Snow and/or multicore

    - by James
    Hi, I have the following problem. First my environment, I have two 24-CPU servers to work with and one big job (resampling a large dataset) to share among them. I've setup multicore and (a socket) Snow cluster on each. As a high-level interface I'm using foreach. What is the optimal sharing of the job? Should I setup a Snow cluster using CPUs from both machines and split the job that way (i.e. use doSNOW for the foreach loop). Or should I use the two servers separately and use multicore on each server (i.e. split the job in two chunks, run them on each server and then stich it back together). Basically what is an easy way to: 1. Keep communication between servers down (since this is probably the slowest bit). 2. Ensure that the random numbers generated in the servers are not highly correlated.

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  • Solr Multicore Admin Problem

    - by Daniel M
    Im trying to add a url based security constraint to solr deployed in websphere 6.1. If I specify the core name in the url of the constraint then the admin url for that core gives a 404. Has anyone had any success with this or any suggestions? Cheers Cross-posted with stackoverflow

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  • Multicore solr on Ubuntu 10.04 working for anyone?

    - by coleifer
    Following instructions from the two sites below, I've installed tomcat6 and solr 1.4 http://gist.github.com/204638 https://wiki.fourkitchens.com/display/TECH/Solr+1.4+on+Ubuntu+9.10+and+CentOS+5 I have successfully got it up and running on a server running 9.04 with multicore support, but on the 10.04 I can't seem to get it to work. I am able to reach localhost:xxxx/solr/ on the 10.04 box and see a single link to the Solr Admin, but following the link takes me to a 404 page with the following output: /solr/admin/ HTTP Status 404 - missing core name in path The requested resource (missing core name in path) is not available I am also unable to access /solr/site1/ as I would except - it similarly returns a 404 <!-- from /var/solr/solr.xml, site dirs exist --> <cores adminPath="/admin/cores"> <core name="site1" instanceDir="site1" /> <core name="site2" instanceDir="site2" /> </cores> <!-- from /etc/tomcat6/Catalina/localhost/solr.xml --> <Context docBase="/var/solr/solr.war" debug="0" privileged="true" allowLinking="true" crossContext="true"> <Environment name="solr/home" type="java.lang.String" value="/var/solr" override="true" /> </Context>

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  • Programming for Multi core Processors

    - by Chathuranga Chandrasekara
    As far as I know, the multi-core architecture in a processor does not effect the program. The actual instruction execution is handled in a lower layer. my question is, Given that you have a multicore environment, Can I use any programming practices to utilize the available resources more effectively? How should I change my code to gain more performance in multicore environments?

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  • Solr Multicore Admin Problem

    - by Daniel M
    Im trying to add a url based security constraint to solr deployed in websphere 6.1. If I specify the core name in the url of the constraint then the admin url for that core gives a 404. Has anyone had any success with this or any suggestions? Cheers

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  • Minimal "Task Queue" with stock Linux tools to leverage Multicore CPU

    - by Manuel
    What is the best/easiest way to build a minimal task queue system for Linux using bash and common tools? I have a file with 9'000 lines, each line has a bash command line, the commands are completely independent. command 1 > Logs/1.log command 2 > Logs/2.log command 3 > Logs/3.log ... My box has more than one core and I want to execute X tasks at the same time. I searched the web for a good way to do this. Apparently, a lot of people have this problem but nobody has a good solution so far. It would be nice if the solution had the following features: can interpret more than one command (e.g. command; command) can interpret stream redirects on the lines (e.g. ls > /tmp/ls.txt) only uses common Linux tools Bonus points if it works on other Unix-clones without too exotic requirements.

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  • SOLR multicore shared configuration

    - by Mark
    I'm using multiple cores in SOLR to enable offline population of indices (and then using SWAP to swap out the active core). I want to use the same solrconfig.xml file for both cores - can someone tell me where I should put this so it can be picked up by SOLR?

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  • Melhoria de Performance no .NET 4.5: Multicore Just-in-Time (JIT).

    - by anobre
    Olá pessoal! Dando uma lida nas melhorias de performance da plataforma .NET 4.5, me deparei com algo extremamente interessante: Multicore Just-in-Time (JIT). A teoria é muito simples: por que não utilizar vários núcleos para a compilação JIT? Além disto, será que seria possível compilar os métodos em uma determinada ordem, onde os primeiros fossem aqueles com maior probabilidade de execução? Isto parece meio loucura mas é o que o Multicore Just-in-Time (JIT) faz. E o melhor de tudo, de uma forma extremamente simples. As aplicações ASP.NET 4.5 já o fazem por default. Em outras ocasiões, basta executar duas linhas de código: uma indicando a pasta onde o arquivo que armazenará o profile ficará, e a outra para iniciar o procedimento. Este profile é o arquivo responsável por armazenar a ordem de compilação dos métodos, para que aqueles com maior chance de serem executados mais cedo sejam compilados antes. Código para este processo: ProfileOptimization.SetProfileRoot(@"C:\ProfileRoot"); ProfileOptimization.StartProfile("profile"); .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } Esta otimização na compilação só será notada após a criação do profile. Portanto, na primeira vez nada será percebido. Ao final do processo, um arquivo com o nome escolhido (no caso profile) será criado, na pasta indicada como root: Fica a dica! Abraços!

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  • Java Parallel Programming

    - by user578524
    Dear All, I need to parallelize a CPU intensive Java application on my multicore desktop but I am not so comfortable with threads programming. I looked at Scala but this would imply learning a new language which is really time consuming. I also looked at Ateji PX Java parallel extensions which seem very easy to use but did not have a chance yet to evaluate it. Would anyone recommend it? Other suggestions welcome. Thanks in advance for your help Bill

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  • Will a database server perform better running on 2 CPUs with 16 cores or 4 CPUs with 8 cores?

    - by AlexOdin
    What I have: an online financial application (ASP.NET, C#) at peak we have 5K+ simultaneous users backend is running on Oracle 11g (active server + stand-by using Active Data Guard). At peak - 4K-5K database sessions Oracle is installed on Linux 5.8 (Oracle's unbreakable version) the database size: 7TB disk storage: NetApp (connected with 10GB network) I would like to replace old servers (IT will purchase HP blades BL685C). Servers will have 256GB of RAM. I need your help to figure out what to do with CPUs and cores. Options: 2 CPUs (2.3 GHz) with 16 cores each 4 CPUs (3.0 GHz) with 8 cores each Question: Which one should I pick? P.S. Next year, we will migrate from Oracle to SQL server. I hope, whatever option you recommend will work for both platforms

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  • NedMalloc / DlMalloc experiences

    - by Suma
    I am currently evaluating a few of scalable memory allocators, namely nedmalloc and ptmalloc (both built on top of dlmalloc), as a replacement for default malloc / new because of significant contention seen in multithreaded environment. Their published performance seems to be good, however I would like to check what are experiences of other people who have really used them. Were your performance goals satisfied? Did you experience any unexpected or hard to solve issues (like heap corruption)? If you have tried both ptmaalloc and nedmalloc, which of the two would you recommend? Why (ease of use, performance)?

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  • How are interrupts handled by dual processor machines?

    - by jeffD
    I have an idea of how interrupts are handled by a dual core CPU. I was wondering about how interrupt handling is implemented on a board with more than one physical processor. Is any of the interrupt responsibility determined by the physical board's configuration? Each processor must be able to handle some types of interrupts, like disk I/O. Unless there is some circuitry to manage and dispatch interrupts to the appropriate processor? My guess is that the scheme must be processor neutral, so that any processor and core can run the interrupt handler. If a core is waiting on a disk read, will that core be the one to run the interrupt handler when the disk is ready?

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  • Multi-part question about multi-threading, locks and multi-core processors (multi ^ 3)

    - by MusiGenesis
    I have a program with two methods. The first method takes two arrays as parameters, and performs an operation in which values from one array are conditionally written into the other, like so: void Blend(int[] dest, int[] src, int offset) { for (int i = 0; i < src.Length; i++) { int rdr = dest[i + offset]; dest[i + offset] = src[i] > rdr? src[i] : rdr; } } The second method creates two separate sets of int arrays and iterates through them such that each array of one set is Blended with each array from the other set, like so: void CrossBlend() { int[][] set1 = new int[150][75000]; // we'll pretend this actually compiles int[][] set2 = new int[25][10000]; // we'll pretend this actually compiles for (int i1 = 0; i1 < set1.Length; i1++) { for (int i2 = 0; i2 < set2.Length; i2++) { Blend(set1[i1], set2[i2], 0); // or any offset, doesn't matter } } } First question: Since this apporoach is an obvious candidate for parallelization, is it intrinsically thread-safe? It seems like no, since I can conceive a scenario (unlikely, I think) where one thread's changes are lost because a different threads ~simultaneous operation. If no, would this: void Blend(int[] dest, int[] src, int offset) { lock (dest) { for (int i = 0; i < src.Length; i++) { int rdr = dest[i + offset]; dest[i + offset] = src[i] > rdr? src[i] : rdr; } } } be an effective fix? Second question: If so, what would be the likely performance cost of using locks like this? I assume that with something like this, if a thread attempts to lock a destination array that is currently locked by another thread, the first thread would block until the lock was released instead of continuing to process something. Also, how much time does it actually take to acquire a lock? Nanosecond scale, or worse than that? Would this be a major issue in something like this? Third question: How would I best approach this problem in a multi-threaded way that would take advantage of multi-core processors (and this is based on the potentially wrong assumption that a multi-threaded solution would not speed up this operation on a single core processor)? I'm guessing that I would want to have one thread running per core, but I don't know if that's true.

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  • In a multithreaded app, would a multi-core or multiprocessor arrangement be better?

    - by Michael
    I've read a lot on this topic already both here (e.g., stackoverflow.com/questions/1713554/threads-processes-vs-multithreading-multi-core-multiprocessor-how-they-are or http://stackoverflow.com/questions/680684/multi-cpu-multi-core-and-hyper-thread) and elsewhere (e.g., ixbtlabs.com/articles2/cpu/rmmt-l2-cache.html or software.intel.com/en-us/articles/multi-core-introduction/), but I still am not sure about a couple things that seem very straightforward. So I thought I'd just ask. (1) Is a multi-core processor in which each core has dedicated cache effectively the same as a multiprocessor system (balanced of course for processor speed, cache size, and so on)? (2) Let's say I have some images to analyze (i.e., computer vision), and I have these images loaded into RAM. My app spawns a thread for each image that needs to be analyzed. Will this app on a shared cache multi-core processor run slower than on a dedicated cache multi-core processor, and would the latter run at the same speed as on an equivalent single-core multiprocessor machine? Thank you for the help!

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