High performance computing systems for many-core processors
Computer simulations can be used in different research fields. One of them is to perform real world obstacle detection and avoidance for unmanned vehicles. In addition, very little research has been done on simulating several obstacle detection and avoidance for autonomous aircrafts. The objective o...
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sg-ntu-dr.10356-592012023-03-03T20:29:53Z High performance computing systems for many-core processors Soh, Alexius Matthias Sheng En School of Computer Engineering He Bingsheng DRNTU::Engineering::Computer science and engineering::Computing methodologies::Simulation and modeling Computer simulations can be used in different research fields. One of them is to perform real world obstacle detection and avoidance for unmanned vehicles. In addition, very little research has been done on simulating several obstacle detection and avoidance for autonomous aircrafts. The objective of this research is to determine if it is better to perform simulations on the GPU than on the CPU when there are multiple simulations to be performed at any one time. Four to ten unique obstacle layouts were used for the experiment. The simulations were executed sequentially, in multi-threaded approach and using the GPU. The experiment reveals that executing the simulations on the GPU proves to be time efficient as compared to the CPU while allowing more simulations to run in parallel. The result of this study shows that implementing the simulations to run the GPU in comparison to the CPU does allow for greater time efficiency. Bachelor of Engineering (Computer Engineering) 2014-04-25T04:54:15Z 2014-04-25T04:54:15Z 2014 2014 Final Year Project (FYP) http://hdl.handle.net/10356/59201 en Nanyang Technological University 22 p. application/pdf |
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DRNTU::Engineering::Computer science and engineering::Computing methodologies::Simulation and modeling Soh, Alexius Matthias Sheng En High performance computing systems for many-core processors |
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Computer simulations can be used in different research fields. One of them is to perform real world obstacle detection and avoidance for unmanned vehicles. In addition, very little research has been done on simulating several obstacle detection and avoidance for autonomous aircrafts. The objective of this research is to determine if it is better to perform simulations on the GPU than on the CPU when there are multiple simulations to be performed at any one time. Four to ten unique obstacle layouts were used for the experiment. The simulations were executed sequentially, in multi-threaded approach and using the GPU. The experiment reveals that executing the simulations on the GPU proves to be time efficient as compared to the CPU while allowing more simulations to run in parallel. The result of this study shows that implementing the simulations to run the GPU in comparison to the CPU does allow for greater time efficiency. |
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School of Computer Engineering |
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School of Computer Engineering Soh, Alexius Matthias Sheng En |
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Final Year Project |
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Soh, Alexius Matthias Sheng En |
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Soh, Alexius Matthias Sheng En |
title |
High performance computing systems for many-core processors |
title_short |
High performance computing systems for many-core processors |
title_full |
High performance computing systems for many-core processors |
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High performance computing systems for many-core processors |
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High performance computing systems for many-core processors |
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high performance computing systems for many-core processors |
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2014 |
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http://hdl.handle.net/10356/59201 |
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1759857362602033152 |