Writing parallel software effectively for embedded systems is not an easy task. We believe a new approach is needed to maximize the performance speed-up. Therefore we propose a layered top-down model for parallel embe...
详细信息
ISBN:
(纸本)9781479927289
Writing parallel software effectively for embedded systems is not an easy task. We believe a new approach is needed to maximize the performance speed-up. Therefore we propose a layered top-down model for parallel embeddedsoftware, based on Our Pattern Language for High-Performance Computing. Several case studies were developed to demonstrate the strength of the model. First, a Fast Fourier Transformation algorithm was parallelized using the top-down model. A speed-up was achieved close to the theoretical maximum. Next, a telecommunication system was migrated from a naive symmetric multiprocessing setup to an asymmetric multiprocessing set-up. Finally, an algorithm that searches for sequences in a list of arcs and lines was implemented in two different ways. The strengths and weaknesses of both parallel implementations are explained.
multicoreembedded systems introduce new opportunities and challenges. Scaling of computational power is one of the main reasons for transition to a multicore environment. In most cases parallelization of existing alg...
详细信息
ISBN:
(纸本)9780769550947
multicoreembedded systems introduce new opportunities and challenges. Scaling of computational power is one of the main reasons for transition to a multicore environment. In most cases parallelization of existing algorithms is time consuming and error prone, dealing with low-level constructs. Migrating principles of object-oriented design patterns to parallel embeddedsoftware avoids this. We propose a top-down approach for refactoring existing sequential to parallel algorithms in an intuitive way, avoiding the usage of locking mechanisms. We illustrate the approach on the well known Fast Fourier Transformation algorithm. Parallel design patterns, such as Map Reduce, Divide-and-Conquer and Task Parallelism assist to derive a parallel approach for calculating the Fast Fourier Transform. By combining these design patterns, a robust and better performing application is obtained.
暂无评论