Article,
Code Parallelization for Multi-Core Software Defined Radio Platforms with OpenMP
(2011)
Abstract
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 process-
ing power of a multi-core GPP and hence to avoid
system inefficiency, this work provides an approach
to parallelize C/C
++
code using OpenMP. This ap-
plication 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 al-
M.
