论文标题
用于优化SPTRSV的图形转换策略
A Graph Transformation Strategy for Optimizing SpTRSV
论文作者
论文摘要
稀疏三角溶液（SPTRSV）是经过广泛研究的计算内核。并行SPTRSV实现的一个重要障碍是，在稀疏矩阵的某些部分中，计算是串行的。通过转换依赖图，可以增加缺乏部分的部分的并行性。在这项工作中，我们提出了一种方法，以提高稀疏基质的并行度度，讨论其局限性和可能的改进，并将其与以前的手动方法进行比较。结果提供了有关如何制定策略来改变依赖图的一些提示。
Sparse triangular solve (SpTRSV) is an extensively studied computational kernel. An important obstacle in parallel SpTRSV implementations is that in some parts of a sparse matrix the computation is serial. By transforming the dependency graph, it is possible to increase the parallelism of the parts that lack it. In this work, we present an approach to increase the parallelism degree of a sparse matrix, discuss its limitations and possible improvements, and we compare it to a previous manual approach. The results provide several hints on how to craft a collection of strategies to transform a dependency graph.
