Systematic Fusion of CUDA Kernels for Iterative Sparse Linear System Solvers

被引：11
作者：
Aliaga, Jose I. [1 ]
Perez, Joaquin [1 ]
Quintana-Orti, Enrique S. [1 ]
机构：
[1] Univ Jaume 1, Dept Ingn & Ciencia Comp, Castellon de La Plana 12071, Spain
来源：
EURO-PAR 2015: PARALLEL PROCESSING | 2015年 / 9233卷
关键词：
Graphics processors; CUDA; Sparse linear systems; Iterative solvers;
D O I：
10.1007/978-3-662-48096-0_52
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
We introduce a systematic analysis in order to fuse CUDA kernels arising in efficient iterative methods for the solution of sparse linear systems. Our procedure characterizes the input and output vectors of these methods, combining this information together with a dependency analysis, in order to decide which kernels to merge. The experiments on a recent NVIDIA "Kepler" GPU report significant gains, especially in energy consumption, for the fused implementations derived from the application of the methodology to three of the most popular Krylov subspace solvers with/without preconditioning.
引用
收藏
页码：675 / 686
页数：12
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