I used MPI to write a distribution layer. Let say we have n of data sources and k of data consumers. In my approach each of n MPI processes reads data, then distributes it to one (or ma开发者_StackOve
Is there an equivalent to Haskell Control.Parallel.Strategies o开发者_Python百科r a way to achieve the same thing?
I\'m trying to use GNU parallel to post a lot of files to a web server. In my directory, I have some files:
I have create a pthread_create inside a pthread_create, I have used socket programming, 开发者_如何学运维where I receive a packet and then create a thread which does the writing to the file. When I se
for example, i wish I can see 1% ~ 100%, how could I do that? Parallel.For<Dictionary<int, long>>(0, r1, () => new Dictionary<int, long>(), (j, loop, tmpWi开发者_开发技巧nRange)
In the chapter \"Programming Multicore CPUs\" of the Programming Erlang book, Joe Armstrong gives a nice example of parallelization of a map function:
Googling didn’t help much, has anyone used AMP? In the code snippet below the cast from integer to double (double v = idx.x) leads to a “Failed to create shader” run time error.
What\'s the faster way to effectively fill an array of bytes where each byte represents a pixel (black or white: < 125 = black, > 125 = white) from a Bitmap class?
Consider the following snipped of code, which calculates the size of all paths given. def pathSizes = []
I\'m using parallel.for to launch in many threads a external program. But despite the fact that these are separate threads I need implement sth like delay. E.开发者_JS百科g. 2 threads want to launch t
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