A new diagonal storage for efficient implementation of sparse matrix–vector multiplication on graphics processing unit

2021 ◽  
Author(s):  
Guixia He ◽  
Qi Chen ◽  
Jiaquan Gao
Keyword(s):  
Graphics Processing Unit ◽  
Sparse Matrix ◽  
Efficient Implementation ◽  
Processing Unit ◽  
Matrix Vector Multiplication ◽  
Graphics Processing ◽  
Matrix Vector

GPU Accelerated Reconstruction in Compton Scattering Tomography Using Matrix Compression

2014 ◽  
Vol 519-520 ◽  
pp. 102-107
Author(s):  
Yu Fei Yu ◽  
Bin Yan ◽  
Biao Wang ◽  
Lei Li ◽  
Yu Han ◽  
...  
Keyword(s):  
Compton Scattering ◽  
Graphics Processing Unit ◽  
Sparse Matrix ◽  
Reconstruction Algorithm ◽  
Processing Unit ◽  
Matrix Vector Multiplication ◽  
Speedup Ratio ◽  
Parallel Features ◽  
Graphics Processing ◽  
Matrix Vector

An acceleration strategy for TV-ADM reconstruction algorithm in Compton scattering tomography (CST) is proposed. By analyzing the sparse characteristic of CST projection matrixes, firstly, the sparse matrix vector CSR format and ELL format are used to store them, which greatly reduce the memory consumption. Then, a Sparse Matrix Vector multiplication (SpMV) method is utilized to accelerate the projector and back projector process. Finally, based on the parallel features, the TV-ADM is computed with Graphics Processing Unit (GPU). Numerical experiments show that the TV-ADM with the presented acceleration strategy could achieve a 96 times speedup ratio and 224 times memory compression ratio without precision loss.

Parallel computations of the step response of a floor heater with the use of a graphics processing unit. Part 2: results and their evaluation

2013 ◽  
Vol 61 (4) ◽  
pp. 949-954 ◽  
Author(s):  
J. Gołębiowski ◽  
J. Forenc
Keyword(s):  
Graphics Processing Unit ◽  
Sparse Matrix ◽  
Temporal Distribution ◽  
Step Response ◽  
Processing Unit ◽  
Commercial Program ◽  
Speed Up ◽  
Spatio Temporal ◽  
Graphics Processing ◽  
Linear Systems Of Equations

Abstract Using models and algorithms presented in the first part of the article, a spatio-temporal distribution of the step response of a floor heater was determined. The results have been presented in the form of heating curves and temperature profiles of the heater in the selected time moments. The computations results were verified through comparing them with the solution obtained with the use of a commercial program - NISA. Additionally, the distribution of the average time constant of thermal processes occurring in the heater was determined. The analysis of the use of a graphics processing unit in numerical computations based on the conjugate gradient method was done. It was proved that the use of a graphics processing unit is profitable in the case of solving linear systems of equations with dense coefficient matrices. In the case of a sparse matrix, the speed-up depends on the number of its non-zero elements.

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