Multi-objective evolutionary auto-tuning for optimising algorithm speed and cache memory usage

  • Authors:

  • Darren M. Chitty

  • Affiliations:

  • Bristol University, Bristol, United Kingdom

  • Venue:
  • Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
  • Year:
  • 2013

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Abstract

Modern CPUs are complex with hierarchical cache memory levels, vector instruction sets, instruction level parallelism and multiple processor cores. Hence, extracting the maximum performance for a given algorithm is a complex task and can require the optimisation of a number of parameters. This paper will demonstrate the use of an evolutionary approach to tune a matrix multiplication algorithm in terms of both execution speed and also cache memory usage. Moreover, it will be shown that these objectives conflict to some degree. Hence, a multi-objective evolutionary tuning approach is demonstrated that optimises for both of these objectives establishing a Pareto front of solutions.