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 in:2012 26th IEEE International Parallel and Distributed Processing Symposium Workshops pp. 1769 - 1777
Main Authors: Lalami, M. E., El-Baz, D.
Format: Conference Proceeding
Language:English
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
ISBN:1467309745, 9781467309745
Online Access:Get full text
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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