I am using msync in my application on Linux 2.6 to ensure consistency in the event of a crash. I need to thoroughly test my usage of msync but the implementation seems to be flushing all the relevant
I am writing a script that processes some mmaps concurrently with multiprocessing.Process and updates a result list stored in an mmap and locked with a mutex.
I need to read in and process a bunch of ~40mb gzipped text files, and I need it done f开发者_高级运维ast and with minimal i/o overhead (as the volumes are used by others as well). The fastest way I\'
why doesn\'t following pseudo-code work (O_DIRECT results in EFAULT) in_fd = open(\"/dev/mem\"); in_mmap = mmap(in_fd);
In the original vmsplice() implementation, it was suggested that if you had a user-land buffer 2x the maximum number of pages that could fit in a pipe, a successful vmsplice() on the second half of th
I can\'t find any documentation on how numpy handles unmapping of previously memory mapped regions: munmap for num开发者_运维百科py.memmap() and numpy.load(mmap_mode).
I have a really large file I\'m trying to open with mmap and its giving me permission denied.I\'ve tried different flags and modes to the os.open but its just not working for me.
I wanna share a pointer of map during 2 processes. So I tried mmap. I tested mmap in a single process. Here is my code:
Overview I have aprogram bounded significantly by IO and am trying to speed it up. Using mmap seemed to be a good idea, but it actually degrades the performance relative to just using a series of fge
Given a numpy.memmap object created with mode=\'r\' (i.e. read-only), is there a way to force it to purge all loaded pages out of physical RAM, without deleting the object itself?
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