| Autor: |
Jessica Brazelton, Miguel Cabral, Fan Wu |
| Rok vydání: |
2010 |
| Předmět: |
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| Zdroj: |
2010 International Conference on Computational Intelligence and Software Engineering. |
| DOI: |
10.1109/cise.2010.5677044 |
| Popis: |
In recent years, there has been significant interest from both academia and industry in applying commodity graphics processing units (GPUs) toward general computing problems. The nVidia CUDA programming model provides a straightforward means of describing inherently parallel computations. In this paper, we present our GPU-based matrix multiplication with high performance on General Purpose Graphics Processing Unit (GPGPUs). We implemented our algorithm using nVidia CUDA API and compared its performance with an optimized CPU-implementation on a high-end AMD Opteron Dual Core CPU. Our experimental results show that a significant performance improvement over CPU-based algorithm and the maximum observed speedups are about 100 times. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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