Sparse matrix-vector multiplication on network-on-chip

Author:

Sun C.-C.,Götze J.,Jheng H.-Y.,Ruan S.-J.

Abstract

Abstract. In this paper, we present an idea for performing matrix-vector multiplication by using Network-on-Chip (NoC) architecture. In traditional IC design on-chip communications have been designed with dedicated point-to-point interconnections. Therefore, regular local data transfer is the major concept of many parallel implementations. However, when dealing with the parallel implementation of sparse matrix-vector multiplication (SMVM), which is the main step of all iterative algorithms for solving systems of linear equation, the required data transfers depend on the sparsity structure of the matrix and can be extremely irregular. Using the NoC architecture makes it possible to deal with arbitrary structure of the data transfers; i.e. with the irregular structure of the sparse matrices. So far, we have already implemented the proposed SMVM-NoC architecture with the size 4×4 and 5×5 in IEEE 754 single float point precision using FPGA.

Publisher

Copernicus GmbH

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Sparse Matrix-Vector Multiplication: A Data Mapping-Based Architecture;2014 15th International Conference on Parallel and Distributed Computing, Applications and Technologies;2014-12

2. Inexact Sparse Matrix Vector Multiplication in Krylov Subspace Methods: An Application-Oriented Reduction Method;Parallel Processing and Applied Mathematics;2014

3. Utilizing Robustness of Krylov Subspace Methods in Reducing the Effort of Sparse Matrix Vector Multiplication;Procedia Computer Science;2013

4. Sparse Matrix-Vector Multiplication Based on Network-on-Chip: On Data Mapping;2012 Fifth International Symposium on Parallel Architectures, Algorithms and Programming;2012-12

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