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Optimal task allocation on non-volatile memory based hybrid main memory

Published: 02 November 2011 Publication History

Abstract

This paper targets task allocation problem on hybrid main memory composed of non-volatile memory (NVM) and DRAM. Compared to the conventional memory technology DRAM, the emerging NVM has excellent energy performance due to the ultra low leakage power. However, most types of NVMs come with the disadvantages of much shorter write endurance and longer write latency as opposed to DRAM. This paper explores task allocation problems on hybrid memory which consists of energy-efficient NVM and write-endurable DRAM. The objectives of the task allocation include minimizing the energy consumption, extending the lifetime and minimizing the size. The contributions of this work are twofold. First, we design Integer Linear Programming (ILP) formulations that can solve different objectives optimally. Then, we propose three effective polynomial time heuristic algorithms. All the ILP formulations and the proposed heuristics are executed to optimize multiple objectives offline. Experiments show that compared to the optimal solutions generated by the ILP formulations, the proposed heuristics can produce near-optimal results.

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cover image ACM Conferences
RACS '11: Proceedings of the 2011 ACM Symposium on Research in Applied Computation
November 2011
355 pages
ISBN:9781450310871
DOI:10.1145/2103380
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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  • SIGAPP: ACM Special Interest Group on Applied Computing
  • ACCT: Association of Convergent Computing Technology
  • CUSST: University of Suwon: Center for U-city Security & Surveillance Technology of the University of Suwon
  • KIISE: Korean Institute of Information Scientists and Engineers
  • KISTI

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Association for Computing Machinery

New York, NY, United States

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Published: 02 November 2011

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Author Tags

  1. ILP
  2. hybrid memory
  3. optimal task allocation

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RACS '11
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RACS '11: Research in Applied Computation Symposium
November 2 - 5, 2011
Florida, Miami

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