Xabclib:A Fully Auto-tuned Sparse Iterative Solver

In this paper, we propose a general application programming interface named OpenATLib for auto-tuning (AT). OpenATLib is designed to establish the reusability of AT functions. By using OpenATLib, we develop a fully auto-tuned sparse iterative solver named Xabclib. Xabclib has several novel run-time...

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Bibliographic Details
Main Authors Katagiri, Takahiro, Sakurai, Takao, Igai, Mitsuyoshi, Itoh, Shoji, Ohshima, Satoshi, Kuroda, Hisayasu, Naono, Ken, Nakajima, Kengo
Format Journal Article
LanguageEnglish
Published 30.04.2024
Subjects
Computer Science - Distributed, Parallel, and Cluster Computing
Computer Science - Mathematical Software
Computer Science - Performance
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Summary:In this paper, we propose a general application programming interface named OpenATLib for auto-tuning (AT). OpenATLib is designed to establish the reusability of AT functions. By using OpenATLib, we develop a fully auto-tuned sparse iterative solver named Xabclib. Xabclib has several novel run-time AT functions. First, the following new implementations of sparse matrix-vector multiplication (SpMV) for thread processing are implemented:(1) non-zero elements; (2) omission of zero-elements computation for vector reduction; (3) branchless segmented scan (BSS). According to the performance evaluation and the comparison with conventional implementations, the following results are obtained: (1) 14x speedup for non-zero elements and zero-elements computation omission for symmetric SpMV; (2) 4.62x speedup by using BSS. We also develop a "numerical computation policy" that can optimize memory space and computational accuracy. Using the policy, we obtain the following: (1) an averaged 1/45 memory space reduction; (2) avoidance of the "fault convergence" situation, which is a problem of conventional solvers.
DOI:10.48550/arxiv.2405.01599