非结构化网格计算的内存访问优化

Antal Hiba, Zoltán Nagy, Miklos Ruszinko
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引用次数: 1

摘要

处理器阵列的许多实际应用都受到内存带宽限制的影响。在许多情况下,给出了一个非结构化网格(传感器数据的计算,物理系统的模拟- PDEs),其中顶点表示由边缘表示的依赖关系的计算。在这些计算过程中,处理单元(PEs)的利用率主要取决于网格的节点索引。如果相邻节点在主存中存储得很近,可以显著减少节点数据的重载。对于FPGA,存储器的访问完全可以由设计者决定。网格及其节点的排序定义了图带宽,它决定了片上存储器的最小大小,以避免从片外存储器重新加载节点。如果所需的片上内存大小高于可用资源,则必须将网格划分为多个部分。本文提出了一种新的基于几何的方法,该方法从给定的非结构化网格中构造重新排序的部分,其中每个部分满足预定义的图带宽约束。
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Memory access optimization for computations on unstructured meshes
Many real-life applications of processor-arrays suffer from memory bandwidth limitations. In many cases an unstructured mesh is given (computation on sensor data, simulations of physical systems - PDEs), where the vertices represent computations with dependencies represented by the edges. Utilization of processing elements (PEs) during these computations is mainly depends on the node indexing of the mesh. If the adjacent nodes are stored close to each other in main memory, the reloading of node data can be significantly decreased. In case of FPGA the memory accesses can be fully determined by the designer. The mesh and an ordering of its nodes, define the graph bandwidth, which determines the minimum size of on-chip memory to avoid reloading of the nodes from the off-chip memory. If the required on-chip memory size is higher than the available resources, the mesh must be divided into parts. In this paper a novel geometry-based method is presented, which constructs reordered parts from a given unstructured mesh, where each part meets some predefined constraints on graph bandwidth.
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