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Integer linear programming based energy optimization for banked DRAMs

Published: 17 April 2005 Publication History

Abstract

Memory system can be a major energy consumer in an embedded architecture. One way of reducing its energy consumption is banking, i.e., dividing available memory space into multiple, equally sized banks and placing an unused (idle) memory bank into a low-power operating mode. Prior work investigated code restructuring and data layout reorganization based approaches for increasing energy benefits that could be obtained from a banked memory architecture. This paper takes a different look at the problem of energy optimization in banked memory systems, and explores two compiler-assisted techniques that can co-exist with code/data transformations: data migration and data compression. The goal of data migration is to cluster data with similar access patterns in the same set of banks, thereby increasing the chances for utilizing low-power operating modes in a more effective manner. Data compression reduces the size of the data used by the application, and thus helps reduce the number of memory banks occupied by data. This in turn allows us place a larger number of banks into the low-power operating modes. We formulate the memory bank management problem as an ILP (integer linear programming) problem, and solve it using a publicly available ILP package.

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  1. Integer linear programming based energy optimization for banked DRAMs

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    cover image ACM Conferences
    GLSVLSI '05: Proceedings of the 15th ACM Great Lakes symposium on VLSI
    April 2005
    518 pages
    ISBN:1595930574
    DOI:10.1145/1057661
    • General Chair:
    • John Lach,
    • Program Chairs:
    • Gang Qu,
    • Yehea Ismail
    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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    Publication History

    Published: 17 April 2005

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    Author Tags

    1. DRAM
    2. ILP
    3. data compression
    4. data migration
    5. low-power
    6. memory banking

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    GLSVLSI05: Great Lakes Symposium on VLSI 2005
    April 17 - 19, 2005
    Illinois, Chicago, USA

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    Overall Acceptance Rate 312 of 1,156 submissions, 27%

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    • (2013)Hybrid Storage System Power OptimizationProceedings of the 2013 IEEE Green Technologies Conference10.1109/GreenTech.2013.51(285-292)Online publication date: 4-Apr-2013
    • (2012)“An Integer Programming Power Optimization in Storage Systems”Procedia Computer Science10.1016/j.procs.2012.09.07912(326-331)Online publication date: 2012
    • (2008)ILP-Based energy minimization techniques for banked memoriesACM Transactions on Design Automation of Electronic Systems10.1145/1367045.136705913:3(1-40)Online publication date: 25-Jul-2008
    • (2007)Compiler-Directed Code Restructuring for Operating with Compressed ArraysProceedings of the 20th International Conference on VLSI Design held jointly with 6th International Conference: Embedded Systems10.1109/VLSID.2007.50(221-226)Online publication date: 6-Jan-2007
    • (2006)Data Replication in Banked DRAMs for Reducing Energy ConsumptionProceedings of the 7th International Symposium on Quality Electronic Design10.1109/ISQED.2006.43(551-556)Online publication date: 27-Mar-2006

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