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Parallelism and Scalability in an Image Processing Application

机译:图像处理应用程序中的并行性和可伸缩性

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The recent trends in processor architecture show that parallel processing is moving into new areas of computing in the form of many-core desktop processors and multi-processor system-on-chip. This means that parallel processing is required in application areas that traditionally have not used parallel programs. This paper investigates parallelism and scalability of an embedded image processing application. The major challenges faced when parallelizing the application were to extract enough parallelism from the application and to reduce load imbalance. The application has limited immediately available parallelism. It is difficult to further extract parallelism since the application has small data sets and parallelization overhead is relatively high. There is also a fair amount of load imbalance which is made worse by a non-uniform memory latency. Even so, we show that with some tuning relative speedups in excess of 9 on a 16 CPU system can be reached.
机译:处理器体系结构的最新趋势表明,并行处理正以多核台式机处理器和多处理器片上系统的形式进入新的计算领域。这意味着在传统上没有使用并行程序的应用程序区域中需要并行处理。本文研究嵌入式图像处理应用程序的并行性和可伸缩性。并行化应用程序时面临的主要挑战是从应用程序中提取足够的并行度并减少负载不平衡。该应用程序限制了立即可用的并行性。由于应用程序的数据集较小且并行化开销相对较高,因此很难进一步提取并行性。还有相当数量的负载不平衡,这会因不均匀的内存延迟而变得更糟。即使如此,我们仍然表明,通过一些调整,在16 CPU系统上可以达到超过9的相对加速比。

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