Title :
OpenMP-MCA: Leveraging Multiprocessor Embedded Systems Using Industry Standards
Author :
Peng Sun;Sunita Chandrasekaran;Barbara Chapman
Author_Institution :
Dept. of Comput. Sci., Univ. of Houston, Houston, TX, USA
fDate :
5/1/2015 12:00:00 AM
Abstract :
Multicore embedded systems are rapidly emerging. Hardware designers are packing more and more features into their design. Introducing heterogeneity in these systems, i.e. Adding cores of varying types does provide opportunities to solve problems in different aspects. However, this presents several challenges to embedded system programmers since software is still not mature enough to efficiently exploit the capabilities of the emerging hardware rich with cores of varying types. Programmers still rely on understanding and using low-level hardware-specific API. This approach is not only very time-consuming but also tedious and error-prone. Moreover, the solutions developed are very closely tied to a particular hardware raising significant concerns with software portability. What we need is an industry standard that will enable better programming practices for both current and future embedded systems. To that end, in our project, we have explored the possibility of using existing standards such as OpenMP that provides portable high-level programming constructs along with another industry-driven standard for multicore systems, MCA. For our work, we have considered the GNU compiler since it is the compiler that mostly used in the embedded system domain facilitating open source development. We target a platform consisting of twelve PowerPC e6500 64-bit dual-threaded cores. We create a portable software solution by studying the GNU Open MP runtime library and extending it to incorporate MCA libraries. The solution abstracts the low-level details of the target platform and the results show that the additional MCA layer does not incur any overhead. The results are competitive when compared with a proprietary toolchain.
Keywords :
"Embedded systems","Hardware","Programming","Multicore processing","Instruction sets","Synchronization"
Conference_Titel :
Parallel and Distributed Processing Symposium Workshop (IPDPSW), 2015 IEEE International
DOI :
10.1109/IPDPSW.2015.13