We investigate the execution of the Irregular Wavefront Propagation Pattern (IWPP), a fundamental computing structure used in several image analysis operations, on the Intel® Xeon Phi™ co-processor. An efficient implementation of IWPP on the Xeon Phi is a challenging problem because of IWPP’s irregularity and the use of atomic instructions in the original IWPP algorithm to resolve race conditions. On the Xeon Phi, the use of SIMD and vectorization instructions is critical to attain high performance. However, SIMD atomic instructions are not supported. Therefore, we propose a new IWPP algorithm that can take advantage of the supported SIMD instruction set. We also evaluate an alternate storage container (priority queue) to track active elements in the wavefront in an effort to improve the parallel algorithm efficiency. The new IWPP algorithm is evaluated with Morphological Reconstruction and Imfill operations as use cases. Our results show performance improvements of up to 5.63× on top of the original IWPP due to vectorization. Moreover, the new IWPP achieves speedups of 45.7× and 1.62×, respectively, as compared to efficient CPU and GPU implementations.
Este trabalho apresenta uma implementação do algoritmo Longest Common Subsequence (LCS) para comparação de duas sequências biológicas utilizando linguagem de alto nı́vel High Level Synthesis (HLS) para FPGAs. Foram comparados resultados entre a execução em uma CPU Intel Core i73770 e uma FPGA Xilinx® ADM-PCIE-KU3 que possui uma Xilinx Kintex® UltraScale XCKU060-2. Os resultados mostraram que a implementação em CPU consumiu 6,8x mais energia em relação à FPGA.
Welcome to this special issue, a showcase of some of the most notable papers which were presented at SBAC-PAD 2011 in Vitória, Brazil, in October 2011. SBAC-PAD is an international annual conference, started in 1987, which has continuously presented an overview of new developments, applications, and trends in parallel and distributed computing technologies. SBAC-PAD is open to faculty members, researchers, practitioners, and graduate students around the world. Last year, it was promoted by the Brazilian Computer Society, organized in cooperation with the IEEE Computer
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.