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Computer-implemented systems and methods for efficient sparse matrix representation and processing

机译:高效稀疏矩阵表示和处理的计算机实现的系统和方法

摘要

Speed with which sparse matrices are processed can be increased by using improved compressed representations of the matrices. Structured compressed representations reduce the number of cache misses experienced during matrix processing by decreasing the number of times the cache has to be accessed randomly. Further, representations of the matrix that divide and regroup rows and columns of the matrix based on their number of non-zero entries allows to assign the most appropriate kernel function for processing of these portions of a matrix, overcoming the limitations of the GPU-based hardware. As a result, the speed of processing can be increased without disturbing the original structure of the matrix.
机译:通过使用改进的矩阵压缩表示,可以提高处理稀疏矩阵的速度。结构化的压缩表示形式通过减少必须随机访问高速缓存的次数来减少矩阵处理期间遇到的高速缓存未命中的次数。此外,基于矩阵的行和列的非零条目数对其进行划分和重新组合的矩阵表示形式,可以分配最合适的内核函数来处理矩阵的这些部分,从而克服了基于GPU的局限性硬件。结果,可以提高处理速度,而不会干扰矩阵的原始结构。

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