Improving Reliability of Embedded Systems through Dynamic Memory Manager Optimization using Grammatical Evolution

Technology scaling has offered advantages to embedded systems, such as increased performance, more available memory and reduced energy consumption. However, scaling also brings a number of problems like reliability degradation mechanisms. The intensive activity of devices and high operating temperatures are key factors for reliability degradation in latest technology nodes. Focusing on embedded systems, the memory is prone to suffer reliability problems due to the intensive use of dynamic memory on wireless and multimedia applications. In this work we present a new approach to automatically design dynamic memory managers considering reliability, and improving performance, memory footprint and energy consumption. Our approach, based on Grammatical Evolution, obtains a maximum improvement of 39% in execution time, 38% in memory usage and 50% in energy consumption over state-of-the-art dynamic memory managers for several real-life applications. In addition, the resulting distributions of memory accesses improve reliability. To the best of our knowledge, this is the first proposal for automatic dynamic memory manager design that considers reliability.

Published in:
Proceedings of the 12th ACM Annual Conference on Genetic and Evolutionary Computation (GECCO 2010), 1, 1, 1227-1234
Presented at:
12th ACM Annual Conference on Genetic and Evolutionary Computation (GECCO 2010), Portland, Oregon, USA, July 7-11, 2010
New York, ACM Press

 Record created 2010-03-26, last modified 2018-03-17

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