Open Access

Algorithms for Optimally Arranging Multicore Memory Structures

  • Wei-Che Tseng1Email author,
  • Jingtong Hu1,
  • Qingfeng Zhuge1,
  • Yi He1 and
  • EdwinH-M Sha1
EURASIP Journal on Embedded Systems20102010:871510

DOI: 10.1155/2010/871510

Received: 31 December 2009

Accepted: 6 May 2010

Published: 3 June 2010


As more processing cores are added to embedded systems processors, the relationships between cores and memories have more influence on the energy consumption of the processor. In this paper, we conduct fundamental research to explore the effects of memory sharing on energy in a multicore processor. We study the Memory Arrangement (MA) Problem. We prove that the general case of MA is NP-complete. We present an optimal algorithm for solving linear MA and optimal and heuristic algorithms for solving rectangular MA. On average, we can produce arrangements that consume 49% less energy than an all shared memory arrangement and 14% less energy than an all private memory arrangement for randomly generated instances. For DSP benchmarks, we can produce arrangements that, on average, consume 20% less energy than an all shared memory arrangement and 27% less energy than an all private memory arrangement.

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Authors’ Affiliations

Department of Computer Science, University of Texas at Dallas


© Wei-Che Tseng et al. 2010

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.