Using OpenMP: Portable Shared Memory Parallel Programming (Scientific and Engineering Computation)
Using OpenMP: Portable Shared Memory Parallel Programming (Scientific and Engineering Computation)
OpenMP: Eine Einfhrung in die parallele Programmierung mit C/C++ (Informatik im Fokus)
OpenMP: Eine Einfhrung in die parallele Programmierung mit C/C++ (Informatik im Fokus)
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Since the number of processing cores in a General Purpose Processor (GPP) increases steadily, parallelization of algorithms is a well known topic in computer science. Algorithms have to be adapted to this new processor architecture to fully exploit the available processing power. This development equally affects the Software Defined Radio (SDR) technology because the GPP has become an important processor for SDR platforms. To make use of the entire processing power of a multi-core GPP and hence to avoid system inefficiency, this work provides an approach to parallelize C/C+驴+ code using OpenMP. This application programming interface provides a rapid way to parallelize code using compiler directives inserted at appropriate positions in the code. The processing load can be shared between all available cores. We use Matlab Simulink as a framework for a model-based design and evaluate the processing gain of embedded handwritten C-code blocks with OpenMP support.We will show that with OpenMP the core utilization is increased. Compared to a single-core GPP, we will present the increase of the processing speed depending on the number of cores. We will also highlight the limitations of code parallelization. In our results, we will show that a straightforward implementation of algorithms without multi-core consideration will cause an underutilized system.