![]() Our own code to compute this might look like code/small/prefixsum.m In MATLAB this is called the cumsum function. It is important to reiterate that not all MATLAB for loops can be converted to parfor.įor example, the prefix sum problem computes the sums of elements up to a particular location in a vector, for every location in the vector. What speedup did you obtain? Limits of parfor Once the pool is started, run your parallel code. So let’s avoid skewing the timing results in our small example and exclude timing the parallel pool startup. However, our pi calculation doesn’t take very long unlike a full-scale problem where the parallel pool startup time would not be significant. MATLAB is usually configured to automatically start a parallel pool when needed. You may do so using the parpool command you saw previously, or using MATLAB’s parallel pool menu in the bottom left corner. Now let’s see whether it goes any faster. Go ahead and rename the for statement to a parfor statement. The code even has tic/toc commands already, so we are all set to convert this to a parallel loop. So each iteration of the loop is in indeed independent. ![]() ![]() The only shared variable is incircle, which satisfies classification as a reduction variable, and the loop variable counts consecutive integers. Each iteration of the loop has its own temporary x, y values. How could we improve the performance of this code?Ĭan this code be parallelized? We only have one loop that could be a candidate for parfor. This code is similar, except it generates many more points, and for speed it no longer displays a visual image. Let’s now move on to code/montecarlo/montecarlo.m. The montecarlo_illustration.m code only shows a few points. So as the random selection of points grows, we can approximate the value of pi. The ratio of points inside vs outside the circle is proportional to pi. Random points are selected and determined to be inside or outside the circle. Let us look at a typical example of a Monte Carlo process - computing the value of pi.įirst, to understand what this example does let’s run code/montecarlo/montecarlo_illustration.m. It is easier to learn how to program by working through real examples. ![]() Illustrate differences between code that does and does not parallelize well.Įxample MATLAB parfor Monte Carlo Illustration ![]()
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