Multi-GPU implementation and performance optimization for CSR-based sparse matrix-vector multiplication

2017 ◽  
Author(s):  
Ping Guo ◽  
Changjiang Zhang
Keyword(s):  
Performance Optimization ◽  
Sparse Matrix ◽  
Matrix Vector Multiplication ◽  
And Performance ◽  
Matrix Vector ◽  
Gpu Implementation

scholarly journals Optimization and performance evaluation of the IDR iterative Krylov solver on GPUs

2016 ◽  
Vol 32 (2) ◽  
pp. 220-230 ◽  
Author(s):  
Hartwig Anzt ◽  
Moritz Kreutzer ◽  
Eduardo Ponce ◽  
Gregory D Peterson ◽  
Gerhard Wellein ◽  
...  
Keyword(s):  
Performance Evaluation ◽  
Sparse Matrix ◽  
Data Locality ◽  
Performance Model ◽  
Reduction Algorithm ◽  
Comprehensive Performance ◽  
And Performance ◽  
Matrix Vector ◽  
Gpu Implementation ◽  
Optimization And Performance

In this paper, we present an optimized GPU implementation for the induced dimension reduction algorithm. We improve data locality, combine it with an efficient sparse matrix vector kernel, and investigate the potential of overlapping computation with communication as well as the possibility of concurrent kernel execution. A comprehensive performance evaluation is conducted using a suitable performance model. The analysis reveals efficiency of up to 90%, which indicates that the implementation achieves performance close to the theoretically attainable bound.

scholarly journals Sparse Matrix-Vector Multiplication on GPGPUs

2017 ◽  
Vol 43 (4) ◽  
pp. 1-49 ◽  
Author(s):  
Salvatore Filippone ◽  
Valeria Cardellini ◽  
Davide Barbieri ◽  
Alessandro Fanfarillo
Keyword(s):  
Sparse Matrix ◽  
Matrix Vector Multiplication ◽  
Matrix Vector
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