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A compact sparse matrix representation using random hash functions

机译:使用随机哈希函数的紧凑型稀疏矩阵表示

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摘要

In this paper, a practical method is presented that allows for the compact representation of sparse matrices. We have employed some random hash functions and applied the rehash technique to the compression of sparse matrices. Using our method, a large-scale sparse matrix can be compressed into some condensed tables. The zero elements of the original matrix can be determined directly by these condensed tables, and the values of nonzero elements can be re- covered in a row major order. Moreover, the space occupied by these condensed tables is small. Though the elements cannot be referenced directly, the compression result can be transmitted progressively. Performance evaluation shows that our method has achieved quite some effective improvement for the compression of randomly distributed sparse matrices.
机译:在本文中,提出了一种实用的方法,该方法允许稀疏矩阵的紧凑表示。我们采用了一些随机哈希函数,并将rehash技术应用于稀疏矩阵的压缩。使用我们的方法,可以将大型稀疏矩阵压缩为一些压缩表。原始矩阵的零元素可以直接由这些精简表确定,非零元素的值可以按行主要顺序重新覆盖。而且,这些浓缩桌子所占的空间很小。尽管不能直接引用这些元素,但是可以逐步传输压缩结果。性能评估表明,我们的方法在压缩随机分布的稀疏矩阵方面取得了相当有效的改进。

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