Citation
Abstract
Solving linear system with a magnitude of thousand to ten thousand of unknowns takes a very long time in serial fashion. Furthermore, linear system that is discretised from Partial Dif erentiation Equations (PDE) is also typically solved by a class of iterative method. Therefore, by parallelising Jacobi Iterative Method using OpenACC, we are able to review and compare OpenACC’s capabilities in accelerating Jacobi Iterative Method using compiler directives approach as opposed to CUDA’s approach. Moreover, we implemented OpenACC in two distinctive domains, where the first domain is on manycore environment with a testbed hardware of Nvidia GeForce GTX 980 and the second domain is on multicore environment where 4 CPU(s) of AMD Opteron 6272 chips are clustered on a single machine with a total of 64 cores. This research project has shown great potentials of the implemented Jacobi Iterative Method using OpenACC as we managed to obtain verily rewarding results. Where, the highest speedup gain is up to 82x faster on GPU with Unified Memory (UM) enabled and 55x times faster on CPU where all 64 cores are fully utilized, and this is when the number of unknowns to be solved is 25,000 and 2,500 respectively.
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Additional Metadata
Item Type: | Article |
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Divisions: | Faculty of Computer Science and Information Technology |
DOI Number: | https://doi.org/10.34218/IJARET.11.12.2020.120 |
Publisher: | IAEME Publication |
Keywords: | OpenACC; Jacobi; Iterative method; GPU programming; Linear System Solver |
Depositing User: | Ms. Zaimah Saiful Yazan |
Date Deposited: | 12 Jun 2024 08:26 |
Last Modified: | 12 Jun 2024 08:26 |
Altmetrics: | http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.34218/IJARET.11.12.2020.120 |
URI: | http://psasir.upm.edu.my/id/eprint/87113 |
Statistic Details: | View Download Statistic |
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