cpu-cores

问题 This question already has answers here : Getting processor information in Python (10 answers) Closed 5 years ago . I'm trying to find out where this value is stored in both windows and osx , in order to do some calculations to make a better task distribution. Core speed in Hz Thanks in advance. Using the platform.process() command only returns the name not the speed I only managed to get it trough this: import subprocess info=subprocess.check_output(["wmic","cpu","get", "name"]) print info

问题 I ran below simple Python program - to do 4 processes separately. I expect the program completes execution in 4 seconds (as you can see in the code), but it takes 10 seconds - meaning it does not do parallel processing. I have more than 1 core in my CPU, but the program seems using just one. Please guide me how can I achieve parallel processing here? Thanks. import multiprocessing import time from datetime import datetime def foo(i): print(datetime.now()) time.sleep(i) print(datetime.now())

问题 I thought the point of a multi-core computer is that it could run multiple threads simultaneously. In that case, if you have a quad-core machine, what's the point of having more than 4 threads running at a time? Wouldn't they just be stealing time from each other? 回答1: The answer revolves around the purpose of threads, which is parallelism: to run several separate lines of execution at once. In an 'ideal' system, you would have one thread executing per core: no interruption. In reality this

问题 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? 回答1: The following Java program prints the number of processors as seen by the

问题 How can I use all cpu cores in my server(has 4 cores) linux Debian over OpenVZ to gzipping faster one big file ? I am trying to use these commands but I can not put the pieces together get number of cores CORES=$(grep -c '^processor' /proc/cpuinfo) this for split big file in more split -b100 file.big this for use gzip command with multiple core find /source -type f -print0 | xargs -0 -n 1 -P $CORES gzip --best I don't know if this is the best way for optimize gzip process of big files.. 回答1:

问题 Is it possible to print the current CPU usage for each core in the system? This is what I have so far using powershell: Get-WmiObject -Query "select Name, PercentProcessorTime from Win32_PerfFormattedData_PerfOS_Processor" 回答1: It can be be done using the following powershell command: (Get-WmiObject -Query "select Name, PercentProcessorTime from Win32_PerfFormattedData_PerfOS_Processor") | foreach-object { write-host "$($_.Name): $($_.PercentProcessorTime)" }; Also you could create a file

问题 I'm looking for a library that will provide this type of information: RAM Swap space Number of CPUs speed (CPU MHz) Number of cores Chip type Ultimately I'll be calling into it from Java, but a C library would be fine, which I can wrap with JNI. Platforms of interest include, but not limited to, AIX, HP-UX, Solaris, Windows. Thanks! 回答1: Like you I was looking for a cross platform system info library and found this: http://code.google.com/p/geekinfo/ I didn't test it yet but it might suit

问题 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

问题 I have a Apache Spark 1.6.1 standalone cluster set on a single machine with the following specifications: CPU: Core i7-4790 (# of cores: 4, # of threads: 8) RAM: 16GB I set nothing so Spark can take the default values, which for cores is "all the available cores", based on that, the question is: Why is Spark detecting 8 cores, when I only have 4? 回答1: I assume that setting all available cores means that Spark is also using Virtual cores And since your CPU does support Hyperthreading it has 8

问题 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 回答1: