A graph-based approach to map matrix algorithms onto local-access processor arrays

J. Moreno, T. Lang
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引用次数: 3

Abstract

The authors describe the application of the multi-mesh graph (MMG) method to the mapping of large matrix algorithms onto class-specific local-access processor arrays. These arrays consist of cells with large local memory (i.e., memory size proportional to the size of the problems) and low cell bandwidth (much smaller than the cell computation rate). The results given indicate that the MMG method allows the analysis of such issues as allocation operations to cells, load balancing, scheduling, synchronization, and overhead in computations and data transfers. These aspects are illustrated by mapping the LU-decomposition algorithm onto a linear memory-linked array. Performance estimates indicate that mapping with the MMG method produces 94% utilization of cells in the target structure used. Therefore, the MMG is a suitable tool for mapping matrix algorithms onto pre-existing arrays.<>
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将矩阵算法映射到本地访问处理器阵列的基于图的方法
作者描述了多网格图(MMG)方法在将大型矩阵算法映射到特定类的本地访问处理器阵列中的应用。这些数组由具有大本地内存(即,内存大小与问题大小成正比)和低单元带宽(远小于单元计算速率)的单元组成。给出的结果表明,MMG方法允许分析诸如向单元分配操作、负载平衡、调度、同步以及计算和数据传输中的开销等问题。通过将lu分解算法映射到线性内存链接数组来说明这些方面。性能估计表明,使用MMG方法的映射在所使用的目标结构中产生94%的单元利用率。因此,MMG是将矩阵算法映射到已有数组的合适工具
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