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Efficient Data Compression Methods for Multidimensional Sparse Array Operations Based on the EKMR Scheme

机译:基于EKMR方案的多维稀疏数组运算的高效数据压缩方法。

摘要

[[abstract]]In our previous work, we have proposed the extended Karnaugh map representation (EKMR) scheme for multidimensional array representation. In this paper, we propose two data compression schemes, EKMR Compressed Row/Column Storage (ECRS/ECCS), for multidimensional sparse arrays based on the EKMR scheme. To evaluate the proposed schemes, we compare them to the CRS/CCS schemes. Both theoretical analysis and experimental tests were conducted. In the theoretical analysis, we analyze the CRS/CCS and the ECRS/ECCS schemes in terms of the time complexity, the space complexity, and the range of their usability for practical applications. In experimental tests, we compare the compressing time of sparse arrays and the execution time of matrix-matrix addition and matrix-matrix multiplication based on the CRS/CCS and the ECRS/ ECCS schemes. The theoretical analysis and experimental results show that the ECRS/ECCS schemes are superior to the CRS/CCS schemes for all the evaluated criteria, except the space complexity in some cases.
机译:[[摘要]]在我们先前的工作中,我们提出了用于多维数组表示的扩展卡诺地图表示(EKMR)方案。在本文中,我们针对基于EKMR方案的多维稀疏阵列提出了两种数据压缩方案EKMR压缩行/列存储(ECRS / ECCS)。为了评估提议的方案,我们将它们与CRS / CCS方案进行比较。进行了理论分析和实验测试。在理论分析中,我们从时间复杂度,空间复杂度以及它们在实际应用中的可用性范围方面分析了CRS / CCS和ECRS / ECCS方案。在实验测试中,我们比较了基于CRS / CCS和ECRS / ECCS方案的稀疏数组的压缩时间以及矩阵-矩阵加法和矩阵-矩阵乘法的执行时间。理论分析和实验结果表明,除了某些情况下的空间复杂度以外,对于所有评估标准,ECRS / ECCS方案均优于CRS / CCS方案。

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