GPU Implementation of the Branch and Bound Method for Knapsack Problems

In this paper, we propose an efficient implementation of the branch and bound method for knapsack problems on a CPU-GPU system via CUDA. Branch and bound computations can be carried out either on the CPU or on a GPU according to the size of the branch and bound list. A better management of GPUs memo...

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Bibliographic Details
Published in2012 26th IEEE International Parallel and Distributed Processing Symposium Workshops pp. 1769 - 1777
Main Authors Lalami, M. E., El-Baz, D.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2012
Subjects
branch and bound method
Central Processing Unit
combinatorial optimization
Computer architecture
CUDA
GPU computing
Graphics processing unit
hybrid computing
Instruction sets
Kernel
knapsack problems
Optimization
Upper bound
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ISBN1467309745
9781467309745
DOI10.1109/IPDPSW.2012.219

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Summary:In this paper, we propose an efficient implementation of the branch and bound method for knapsack problems on a CPU-GPU system via CUDA. Branch and bound computations can be carried out either on the CPU or on a GPU according to the size of the branch and bound list. A better management of GPUs memories, less GPU-CPU communications and better synchronization between GPU threads are proposed in this new implementation in order to increase efficiency. Indeed, a series of computational results is displayed and analyzed showing a substantial speedup on a Tesla C2050 GPU.
ISBN:1467309745
9781467309745
DOI:10.1109/IPDPSW.2012.219