Solving knapsack problems on GPU |
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Authors: | V. Boyer D. El Baz M. Elkihel |
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Affiliation: | a CNRS, LAAS, 7 avenue du Colonel Roche, F-31077 Toulouse, France b Université de Toulouse, UPS, INSA, INP, ISAE, LAAS, F-31077 Toulouse, France |
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Abstract: | A parallel implementation via CUDA of the dynamic programming method for the knapsack problem on NVIDIA GPU is presented. A GTX 260 card with 192 cores (1.4 GHz) is used for computational tests and processing times obtained with the parallel code are compared to the sequential one on a CPU with an Intel Xeon 3.0 GHz. The results show a speedup factor of 26 for large size problems. Furthermore, in order to limit the communication between the CPU and the GPU, a compression technique is presented which decreases significantly the memory occupancy. |
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Keywords: | Combinatorial optimization problems Dense dynamic programming Parallel computing GPU computing CUDA |
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