Solving knapsack problems on GPU

V. Boyer, D. El Baz, M. Elkihel
CNRS; LAAS; 7 avenue du Colonel Roche, F-31077 Toulouse, France
Computers & Operations Research (April 2011)


   title={Solving knapsack problems on gpu},

   author={Boyer, V. and El Baz, D. and Elkihel, M.},

   journal={Computers & Operations Research},





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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 (1.4GHz) 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 3.0GHz. 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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