Can I measure the speedup from parallelization in matlab?

Question

If I assume that a problem is a candidate for parallization e.g. matrix multiplication or some other problem and I use an Intel i7 haswell dualcore, is there some way I can compare a parallel execution to a sequential version of the same program or will matlab optimize a program to my architecture (dualcore, quadcore..)? I would like to know the speedup from adding more processors from a good benchmark parallell program.

Answer 1

Unfortunately there is no such thing as a benchmark parallel program. If you measure a speedup for a benchmark algorithm that does not mean that all the algorithms will benefit from parallelization

Since your target architecture has only 2 cores you might be better off avoiding parallelization at all and let Matlab and the operative system to optimize the execution. Anyway, here are the steps I followed.

• Determine if your problem is apt for parallelization by calculating the theoretical speedup. Some problems like matrix multiplication or Gauss elimination are well studied. Since I assume your problem is more complicated than that, try to decompose your algorithm into simple blocks and determine, block-wise, the advantages of parallelization.
• If you find that several parts of your algorithms could profit from parallelization, study those part separately.
• Obtain statistical information of the runtime of your sequential algorithm. That is, run your program X number of times under similar conditions (and similar inputs) and average the running time.
• Obtain statistical information of the runtime of your parallel algorithm.
• Measure with the profiler. Many people recommends to use function like tic or toc. The profiler will give you a more accurate picture of your running times, as well as detailed information per function. See the documentation for detailed information on how to use the profiler.
• Don't make the mistake of not taking into account the time Matlab takes to open the pool of workers (I assume you are working with the Parallel Computing Toolbox). Depending on your number of workers, the pool takes more/less time and in some occasions it could be up to 1 minute (2011b)!

Answer 2

You can try "Run and time" feature on MATLAB.

Or simply put some tic and toc to the first and end of your code, respectively.

Answer 3

Matlab provides a number of timing functions to help you assess the performance of your code: go read the documentation here and select the function that you deem most appropriate in your case! In particular, be aware of the difference between tic toc and the cputime function.