multiprocess

I have a python code that uses the subprocess package to run in shell: subprocess.call(mycode.py, shell=inshell) When I execute the top command I see that I am only using ~30% or less of CPU. I realize some commands may be using disk and not cpu therefore I was timing the speed. The speed running this on a linux system seems slower than a mac 2 core system. How do I parallelize this with threading or multiprocessing package so that I can use multiple CPU cores on said linux system? To parallelize the work done in mycode.py , you need to organize the code so that it fits into this basic pattern

I am looking for the best way to effectively share chunks of data between two (or more) processes in a writer-biased reader/writer model. My current tests are with boost::interprocess . I have created some managed_shared_memory and am attempting to lock access to the data chunk by using an interprocess mutex stored in the shared memory. However, even when using sharable_lock on the reader and upgradable_lock on the writer, the client will read fragmented values during write operations instead of blocking . While doing a similar reader/writer setup between threads in a single process, I used

I developed a program in C++ for research purpose. It takes several days to complete. Now i executing it on our lab 8core server machine to get results quickly, but i see machine assigns only one processor to my program and it remains at 13% processor usage(even i set process priority at high level and affinity for 8 cores). (It is a simple object oriented program without any parallelism or multi threading) How i can get true benefit from the powerful server machine? Thanks in advance. Ira Baxter Partition your code into chunks you can execute in parallel. You need to go read about data

I set up a process that read a queue for incoming urls to download but when urllib2 open a connection the system hangs. import urllib2, multiprocessing from threading import Thread from Queue import Queue from multiprocessing import Queue as ProcessQueue, Process def download(url): """Download a page from an url. url [str]: url to get. return [unicode]: page downloaded. """ if settings.DEBUG: print u'Downloading %s' % url request = urllib2.Request(url) response = urllib2.urlopen(request) encoding = response.headers['content-type'].split('charset=')[-1] content = unicode(response.read(),

I am currently trying to log to a single file from multiple processes but I am having a lot of trouble with it. I have spend countless hours looking online -- stackoverflow and Google, but have come up with nothing concrete. I have read: How should I log while using multiprocessing in Python? I've been trying to use zzzeek's code but it does not write to the file for me. I don't have a specific way I'm doing it -- I've just been trying every way I can. Have any of you got it to work and have sample code, or do you have an alternative way of doing it. I need to log multiple processes to the