原创 OpenMP and multicore

Dear Readers,

In the last article, we saw about the so called “embrassingly parallel operations” which can easily take advantage of multicore systems. In this article, let us see one more way of getting performance improvements on multicore systems. OpenMP is one of them.

OpenMP specifications was originally defined by industry vendors like Sun, Intel in 1997. It was popular in Symmetric Multiprocessing (SMP) systems. A typical SMP system is a multiprocessor computer hardware where two or more identical processors are connected to a single shared memory and are all processors run same OS instance.

Surprisingly, today's multicore systems are similar to the SMP architecture. Instead of multiple processors, we have multiple cores. All cores access the common shared memory and run same OS instance. That is why, a solution like OpenMP which is from SMP era is suddenly finding a renewed interest in the multicore systems of today.

The OpenMP specification is defined for C/C++/Fortran languages. It consists of three parts: compiler directives, runtime library and environment variables. The code is instrumented with directives and it gets compiled with the openMP supported compiler. The code is linked with the runtime library for generating the executable. There are some runtime environment variables that control the code execution.

An OpenMP program works like this:

1. Start as a single process called the master thread. The master thread executes sequentially like any other normal program, until the first parallel region construct is encountered.
2. The master thread then creates a team of parallel threads
3. The statements in the parallel region construct are then executed in parallel among the various threads created
4. When the individual threads complete the statements in the parallel region construct, they synchronize and terminate, leaving only the master thread

Since the process of creation, starting and joining of threads is done automatically, programmers are relieved of the complexities. The model also allows variables to be locked and shared between the threads and supports fairly advanced features.

Here is an example code from Wikipedia:

int main(int argc, char **argv) {
    const int N = 100000;
    int i, a[N];
 
    #pragma omp parallel for    - Compiler directive
    for (i = 0; i < N; i++)
        a = 2 * i;
 
    return 0;
}