
Contention on shared resources such as cache and main memory slows down the execution of the applications affecting not only application performance but also induces inefficient use of energy. Therefore, in this paper we deal with the contention problem and energy optimization on shared resources multicore-based machines. Our main contribution is a memory-aware resource allocation algorithm that minimize energy consumption by reducing contention conflicts and maximizing performance. We design a heuristic that includes in its objective function the impact of the contention on the application performance. Experimental results emphasize the interest of the provided solution.
operating systems, Sciences informatiques, green computing, memory contention, multi-core processors, memory-aware, scheduling, Computer science, Engineering, computing & technology, Ingénierie, informatique & technologie
operating systems, Sciences informatiques, green computing, memory contention, multi-core processors, memory-aware, scheduling, Computer science, Engineering, computing & technology, Ingénierie, informatique & technologie
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