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The Compression Storage Research for Uniform Block Diagonal Matrix

机译:均匀块对角线矩阵的压缩存储研究

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摘要

Matrix is a mathematical object. We are not interested in data itself in the data structure, but how to store the elements in the matrix, so that various operations can be performed effectively. We often use a two-dimensional array to store the elements in the matrix sequentially. If adopt this method of storage, when there is large number of zero elements and have regular distribution a particular element will consume large amounts of storage unit. For high order matrix, the storage method is not only waste storage unit, but also takes a lot of time for invalid computation, it is obviously not desirable. In order to save the storage space, we need to compress storage for such matrix. The main purpose of the compressed storage is to make more of the same nonzero elements share the same storage unit according to the distribution of matrix element, while the zero elements don't allocate storage space. In this paper, we studied the single vector compressed storage and the multi vectors compressed storage of the uniform block diagonal matrix, and obtained the corresponding storage address mapping function, so as to help the scientific research worker.
机译:矩阵是一个数学对象。我们对数据结构中的数据本身不感兴趣,但如何存储矩阵中的元素,从而可以有效地执行各种操作。我们经常使用二维阵列顺序地存储矩阵中的元素。如果采用这种存储方法,当有大量的零元素并且具有常规分布时,特定元素将消耗大量的存储单元。对于高阶矩阵,存储方法不仅是浪费存储单元,而且需要花费大量的计算,但显然是不可取的。为了保存存储空间,我们需要压缩此类矩阵的存储。压缩存储的主要目的是使更多相同的非零元素共享相同的存储单元,根据矩阵元素的分布,而零元素不分配存储空间。在本文中,我们研究了单载压缩存储和均匀块对角线矩阵的多向量压缩存储,并获得了相应的存储地址映射功能,从而帮助科学研究员。

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