Implementation of Stack Data Placement and Run Time Management Using a Scratch-Pad Memory for Energy Consumption Reduction of Embedded Applications

Lovic GAUTHIER; Tohru ISHIHARA

doi:10.1587/transfun.E94.A.2597

Implementation of Stack Data Placement and Run Time Management Using a Scratch-Pad Memory for Energy Consumption Reduction of Embedded Applications

Lovic GAUTHIER, Tohru ISHIHARA

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Memory accesses are a major cause of energy consumption for embedded systems. This paper presents the implementation of a fully software technique which places stack and static data into a scratch-pad memory (SPM) in order to reduce the energy consumed by the processor while accessing them. Since an SPM is usually too small to include all these data, some of them must be left into the external main memory (MM). Therefore, further energy reduction is achieved by moving some stack data between both memories at run time. The technique employs integer linear programming in order to find at compile time the optimal placement of static data and management of the stack and implements it by inserting stack operations inside the code. Experimental results show that with an SPM of only 1 KB, our technique is able to exploit it for reducing the energy consumption related to the static and stack data accesses by more than 90% for several applications and on an average by 57% compared to the case where these data are fully placed into the main memory.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E94-A No.12 pp.2597-2608

Publication Date: 2011/12/01

Publicized

Online ISSN: 1745-1337

DOI: 10.1587/transfun.E94.A.2597

Type of Manuscript: Special Section PAPER (Special Section on VLSI Design and CAD Algorithms)

Category: High-Level Synthesis and System-Level Design

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Lovic GAUTHIER, Tohru ISHIHARA, "Implementation of Stack Data Placement and Run Time Management Using a Scratch-Pad Memory for Energy Consumption Reduction of Embedded Applications" in IEICE TRANSACTIONS on Fundamentals, vol. E94-A, no. 12, pp. 2597-2608, December 2011, doi: 10.1587/transfun.E94.A.2597.
Abstract: Memory accesses are a major cause of energy consumption for embedded systems. This paper presents the implementation of a fully software technique which places stack and static data into a scratch-pad memory (SPM) in order to reduce the energy consumed by the processor while accessing them. Since an SPM is usually too small to include all these data, some of them must be left into the external main memory (MM). Therefore, further energy reduction is achieved by moving some stack data between both memories at run time. The technique employs integer linear programming in order to find at compile time the optimal placement of static data and management of the stack and implements it by inserting stack operations inside the code. Experimental results show that with an SPM of only 1 KB, our technique is able to exploit it for reducing the energy consumption related to the static and stack data accesses by more than 90% for several applications and on an average by 57% compared to the case where these data are fully placed into the main memory.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E94.A.2597/_p

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@ARTICLE{e94-a_12_2597,
author={Lovic GAUTHIER, Tohru ISHIHARA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Implementation of Stack Data Placement and Run Time Management Using a Scratch-Pad Memory for Energy Consumption Reduction of Embedded Applications},
year={2011},
volume={E94-A},
number={12},
pages={2597-2608},
abstract={Memory accesses are a major cause of energy consumption for embedded systems. This paper presents the implementation of a fully software technique which places stack and static data into a scratch-pad memory (SPM) in order to reduce the energy consumed by the processor while accessing them. Since an SPM is usually too small to include all these data, some of them must be left into the external main memory (MM). Therefore, further energy reduction is achieved by moving some stack data between both memories at run time. The technique employs integer linear programming in order to find at compile time the optimal placement of static data and management of the stack and implements it by inserting stack operations inside the code. Experimental results show that with an SPM of only 1 KB, our technique is able to exploit it for reducing the energy consumption related to the static and stack data accesses by more than 90% for several applications and on an average by 57% compared to the case where these data are fully placed into the main memory.},
keywords={},
doi={10.1587/transfun.E94.A.2597},
ISSN={1745-1337},
month={December},}

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TY - JOUR
TI - Implementation of Stack Data Placement and Run Time Management Using a Scratch-Pad Memory for Energy Consumption Reduction of Embedded Applications
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2597
EP - 2608
AU - Lovic GAUTHIER
AU - Tohru ISHIHARA
PY - 2011
DO - 10.1587/transfun.E94.A.2597
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E94-A
IS - 12
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - December 2011
AB - Memory accesses are a major cause of energy consumption for embedded systems. This paper presents the implementation of a fully software technique which places stack and static data into a scratch-pad memory (SPM) in order to reduce the energy consumed by the processor while accessing them. Since an SPM is usually too small to include all these data, some of them must be left into the external main memory (MM). Therefore, further energy reduction is achieved by moving some stack data between both memories at run time. The technique employs integer linear programming in order to find at compile time the optimal placement of static data and management of the stack and implements it by inserting stack operations inside the code. Experimental results show that with an SPM of only 1 KB, our technique is able to exploit it for reducing the energy consumption related to the static and stack data accesses by more than 90% for several applications and on an average by 57% compared to the case where these data are fully placed into the main memory.
ER -