cpu-cores

I'm using Django with Celery 3.0.17 and now trying to figure out how many celery workers are run by default. From this link I understand that (not having modified this config) the number of workers must be currently equal to the number of CPU cores. And that's why I need the former. I wasn't able to find an official answer by googling or searching heroku's dev center . I think it's 4 cores as I'm seeing 4 concurrent connections to my AMQP server, but I wanted to confirm that. Thanks, J The number of CPUs is not published and is subject to change, but you can find out at runtime by running grep

All is entirely theoretical, the question just came to mind and I wasn't entirely sure whats the answer: Assume you have an application that calculates 4 independent calculations. (Totally independent, doesn't matter what order you do them and you don't need one to calculate another). Also assume those calculations are long (minutes) and CPU-bound (not waiting for any kind of IO) 1) Now, if you have a 1-processor computer, a single thread application will logically be faster than (or the same as) a multithreaded application. As the computer not able to do more then one thing at a time with one

I am running a spark cluster over C++ code wrapped in python. I am currently testing different configurations of multi-threading options (at Python level or Spark level). I am using spark with standalone binaries, over a HDFS 2.5.4 cluster. The cluster is currently made of 10 slaves, with 4 cores each. From what I can see, by default, Spark launches 4 slaves per node (I have 4 python working on a slave node at a time). How can I limit this number ? I can see that I have a --total-executor-cores option for "spark-submit", but there is little documentation on how it impacts the distribution of

I need a reliable way to detect how many CPU cores are on a computer. I am creating a numerically intense simulation C# application and want to create the maximum number of running threads as cores. I have tried many of the methods suggested around the internet like Environment.ProcessorCount, using WMI, this code: http://blogs.adamsoftware.net/Engine/DeterminingthenumberofphysicalCPUsonWindows.aspx None of them seem to think a AMD X2 has two cores. Any ideas? Edit: it appears that Environment.ProcessorCount is returning the correct number. It's on a intel CPU with hyperthreading that is

In some purpose it is needed to make JVM think about it runs on machine with N cores on board instead of real number of cores (e.g. 4 cores instead of 16 ). JVM runs under some Linux build, based on Mandriva/Red Hat Linux core. This question is borderline case because I expect various solutions of this problem. This is not pure linux-administration question, and it isn't pure programmer's question. So... any ideas? The following Java program prints the number of processors as seen by the Java VM: public class AvailableProcessors { public static void main(String... args) { System.out.println

I'm writing a program in C on windows that needs to run as many threads as available cores. But I dont know how to get the number of cores. Any ideas? You can call the GetSystemInfo WinAPI function; it returns a SYSTEM_INFO struct, which has the number of processors (which is the number of cores on a system with multiple core CPUs). You can read NUMBER_OF_PROCESSORS environment variable. James Black Even though the question deals with .NET and yours with C, the basic responses should help: Detecting the number of processors Type "cmd" on windows startup and open "cmd.exe". Now type in the

I am developing an Android application that shows the CPU load per core and memory consumption. For CPU load I am reading /proc/stat and for memory -> /proc/meminfo. However I see that the number of CPU cores in /proc/stat is changing during subsequent reading of the file. cpu 230599 10622 84595 1892023 8236 16 285 0 0 0 cpu0 138005 7992 58080 1738918 6407 16 278 0 0 0 intr 9136791 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9601 0 0 0 0 0 0 ....... ctxt 16904510 btime 1394641996 processes 16919 procs_running 2 procs_blocked 0 softirq 1688530 407 706934 422 1558 407 407 92978 324500 1267 559650 and after

I have a shared machine with 64 cores on which I have a big pipeline of Keras functions that I want to run. The thing is that it seems that Keras automatically uses all the cores available and I can't do that. I use Python and I want to run 67 neural networks in a for loop. I would like to use half of the available cores. I can't find any way of limiting the number of cores in Keras... Do you have any clue? As @Yu-Yang suggested, I used this line before each fit I do : from keras import backend as K K.set_session(K.tf.Session(config=K.tf.ConfigProto(intra_op_‌​parallelism_threads=‌​32, inter