Space Efficient Formats for Structure of Sparse Matrices Based on Tree Structures

I. Šimeček, D. Langr, P. Tvrdík
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引用次数: 6

Abstract

Very large sparse matrices are often processed on massively parallel computer systems with distributed memory architectures consisting of tens or hundreds of thousands of processor cores. The problem occurs when we want or need to load/store these matrices from/to a distributed file system. This paper deals with the design of new formats for storing very large sparse matrices suitable for parallel I/O systems. The first one is based on arithmetic coding and the second one is based on binary tree format. We compare the space complexity of common storage formats and our new formats and prove that the latter are considerably more space efficient.
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基于树结构的稀疏矩阵结构的空间高效格式
非常大的稀疏矩阵通常在具有数万或数十万处理器内核组成的分布式内存体系结构的大规模并行计算机系统上处理。当我们想要或需要从分布式文件系统加载/存储这些矩阵时,问题就出现了。本文研究了适合于并行I/O系统的超大稀疏矩阵存储新格式的设计。第一种是基于算术编码,第二种是基于二叉树格式。我们比较了常用的存储格式和我们的新格式的空间复杂度,证明后者的空间效率要高得多。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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