Today, we'll have a quick look at OpenMP. OpenMP is a set of programming APIs, and compiler pragmas that support multi-platform, shared memory multiprocessing programming in C/C++ and Fortran. The interesting thing about OpenMP, is that it is a very nice simple way to split loops (for, do) into tasks for multi-threading. Our program has a number of "for" loops in it, so that is the obvious avenue to explore for our particular program.
Anyone can get a quick overview of OpenMP
In the previous article about multi-threading, I mentioned that there are 2 options for breaking up the work that needs to be done. Option 1 was to have each thread work on a subset of the portfolio, but do all the experiments. Option 2 was to have each thread work on a subset of the experiments, and to work on all of the portfolio.
Today, we'll look at option 2, and I'll try to explain what was needed in the program to accomplish this task. Option 1 and option 2 programs will look
One of the questions I hear a lot is: Is multi-threaded programming difficult?
The answer to that question is: It depends. Not really an answer, but it does depend on a number of factors. The multi-threaded api is fairly simple, so coding a multi-threaded application is easy. What’s difficult depends on your application, what it does, and how the data is used and structured. If your application uses a lot of shared data, which you need to control access to, with semaphores and mutexes,
One of the topics I want to cover here, is HPC programming. That includes many things, so I want to look at such things as threading, toolkits such as openMP, graphics processor (GPU) toolkits, and cluster kits, such as MPI, as well as others that crop up from time to time. Learning how to use these toolkits can range from simple to complex. Getting the most out of each toolkit is an exercise for the reader. I will cover some basics about using each one, and run some performance tests to compare
High Performance programs, typically do the same thing multiple times with different data, or with different parameters, such as a simulation. Real World applications, such as a program that monitors a port, gets data, processes the data, returns a result, may need to operate on multiple cores as well, but I typically call this type of multi-threading, "concurrency", where your program is doing different things concurrently. This may not be everyone's definition, but I tend to look at
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