用Python分割图片 (PIL)

Python GIL的一个实验

kitt posted @ 2015年11月16日 00:46 in 技术类 Tech , 1880 阅读

 

看了这篇介绍GIL的文章,写的真好,GIL = Global Interpreter Lock, 全局解释器锁,在解释器解释执行任何Python代码时,都需要先获得这把锁才行,也就是一个Python解释器在任意时候都只能跑一个线程,在我的Macbook Pro上跑个实验试试,这些是我本本的参数:

 

CPU: 2.8 GHz Intel Core i7

➜  Desktop  sysctl -a | grep cpu

➜  sysctl -a | grep cpu

hw.ncpu: 4  # 系统使用的cpu数目是4个

hw.activecpu: 4

hw.physicalcpu: 2  # 物理cpu数目是2个

hw.physicalcpu_max: 2

hw.logicalcpu: 4

hw.logicalcpu_max: 4

...

machdep.cpu.brand_string: Intel(R) Core(TM) i7-4558U CPU @ 2.80GHz

...

machdep.cpu.logical_per_package: 16

machdep.cpu.cores_per_package: 8  # 这个不太清楚是啥

...

machdep.cpu.core_count: 2  # 双核

machdep.cpu.thread_count: 4  # 可以跑4线程,即4个Python解释器都跑死循环就能把CPU占到100%

 

实验很简单了,就是写死循环占cpu,先开一个terminal,运行命令top,查看进程和cpu使用情况,然后不断地开terminal,进python,跑死循环:

 

➜  python

Python 2.7.10 (default, Oct 17 2015, 01:15:29) 

[GCC 4.2.1 Compatible Apple LLVM 6.1.0 (clang-602.0.53)] on darwin

Type "help", "copyright", "credits" or "license" for more information.

>>> while True: pass

...

 

开1个的时候, top命令显示的CPU usage在25%左右

2个,50%左右

3个,70%左右(好奇为啥没到75%)

4个,98%左右(最大的数看到了99.3%)

5个,98%左右

6个,98%左右

 

所以在我的机器上一个python解释器只能获得1/4的cpu资源,虐一下自己的机器挺爽的,听到风扇声一下子就起来了,哈哈~ 最后再安利一下Python大法好,写个死循环都只需要一行~

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tt 说:
2016年8月04日 10:51

我试了一下,并不能占到四分之一, python3.5

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kitt 说:
2016年9月02日 01:49

我的是2.7, 系统也要占点资源吧,不能都分给Python吧@tt:

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