For my application, I need it to be fast so I plan to change it to 0.01 second timeout for the statementĭatum = self._comms_queue.get(timeout=0. Hello everyone I wrote the classic example of the sum of two vectors with the kernel function, using the id of the thread and of the blocks. I am wondering whether there is any specific reason to use 1 second timeout. The functions use a timeout of 1 seconds as in version 1.6 which causes unnecessary long delay when executing trivial jobs. It is called both in the main loop processing jobs as well as after the main loop. Using the partitioner there is a performance gain (it's faster than the sequential loop). Using only parallel it would cost me more time than using a sequential loop. After reading the code, I found that this is caused by the JobQueue._fill_results() trying to retrieve additional results from the _comms_queue. When the time to calculate 1 item is very low, it's better to use the partitioner, to process the list in small portions per thread. But, that extra work can be worth the effort, because when done right. BenVoigt Or better yet, just use a math library thats already spent an enormous amount of time writing as optimized of an implementation as possible for. Those coordination challenges are part of what make writing parallel programs harder than simple sequential programs. Also, sieves tend to be embarassingly parallel. The only thing I see that is really wrong is that you use. It looks like you're calculating the location of the diagonal element correctly, but it wouldn't hurt to print out residual norms: they should be the same between sequential and parallel. I didn't find anything in the documentation to configure to speed up the process and I didn't find anyone having similar issues on the Internet. Algorithm improvements will pay off many times faster than naive Parallel.For. Next: parallelizing a numerical method may change the mathematics. I encounter a strange problem when using fabric in parallel mode: for trivial jobs like getting hostname, sequential execution on multiple hosts are much faster than parallel mode. When run in parallel on four processors, with each image requiring 14 14 seconds, the program takes 18 18 seconds to run. I've coded this two version in one file(.First of all I would like to thank you for developing this great tool, it really makes my life much easier. Our example cat detection program takes 60 60 seconds to run sequentially. Many applications today require more computing power than a traditional sequential computer can offer. the work function is faster for large inputs, it is not faster than the sequential. Programming on a multiprocessor system using the divide-and-conquer technique is called parallel programming. Contents Previous Next Index 15 Parallel Programming Computers with. the outcome(Elapsed time) is totally reversed, the program not using thread is much faster than thread program. Sometimes sequential processing is faster than parallel where the latter requires gathering all the data in one place. It seems challenging to find out the reason I will greatly appreciate your contribution in this problem.
Sequential program faster than parallel code#
The parallel code is much slower than the sequential code.
Sequential program faster than parallel serial#
The cpu time (s) cost by the parallel code is 3.85937500000000. Where parallel processing can complete multiple tasks using two or more processors, serial processing (also called sequential processing) will only complete one. Using pthread library, I've had written some code for matrix multiplication.ĪFAIK, the program using thread would be much faster than program without using thread. The results are: The cpu time (s) by the sequential code is 1.98437500000000.
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