Multi-GPU Island-Based Genetic Algorithm for Solving the Knapsack Problem

Jiri Jaros
ANU College of Engineering & Computer Science, The Australian National University, Canberra, ACT, Australia
IEEE World Congress on Computational Intelligence (WCCI 2012), 2012


   title={Multi-GPU Island-Based Genetic Algorithm for Solving the Knapsack Problem},

   author={Jaros, J.},



This paper introduces a novel implementation of the genetic algorithm exploiting a multi-GPU cluster. The proposed implementation employs an island-based genetic algorithm where every GPU evolves a single island. The individuals are processed by CUDA warps, which enables the solution of large knapsack instances and eliminates undesirable thread divergence. The MPI interface is used to exchange genetic material among isolated islands and collect statistical data. The characteristics of the proposed GAs are investigated on a two-node cluster composed of 14 Fermi GPUs and 4 six-core Intel Xeon processors. The overall GPU performance of the proposed GA reaches 5.67 TFLOPS.
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