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This series of two articles discusses how data and memory layout affect performance and suggests specific steps to improve software performance. The basic steps shown in these two articles can yield significant performance gains. These two articles are designed at an intermediate level. It is assumed the reader desires to optimize software performance using common C, C++ and Fortran* programming...
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In this pair of articles on performance and memory covers basic concepts to provide guidance to developers seeking to improve software performance. This paper expands on concepts discussed in Part 1, to consider parallelism, both vectorization (single instruction multiple data SIMD) as well as shared memory parallelism (threading), and distributed memory computing.
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