In this article, we propose a parallel implementation of the dynamic programming method for the knapsack problem on NVIDIA GPU. A GTX 260 (192 cores, 1.4GHz) was 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 up to 26 and permit one to solve large size problems within a reasonable processing time. Furthermore, in order to limit the communication between the CPU and the GPU, a compression technique is presented which decreases significantly the memory occupancy.
In REF , we have proposed an implementation of the dynamic programming method for KP on a CPU/GPU system via CUDA.
Solving knapsack problems on GPU
Comput. Oper. Res.
Comput. Oper. Res.
Computer Science