IEICE TRANSACTIONS on Information
Battery-Aware Task Mapping for Coarse-Grained Reconfigurable Architecture
Summary :
Coarse-grained Reconfigurable Architecture (CGRA) is a parallel computing platform that provides both high performance of hardware and high flexibility of software. It is becoming a promising platform for embedded and mobile applications. Since the embedded and mobile devices are usually battery-powered, improving battery lifetime becomes one of the primary design issues in using CGRAs. In this paper, we propose a battery-aware task-mapping method to optimize energy consumption and improve battery lifetime. The proposed method mainly addresses two problems: task partitioning and task scheduling when mapping applications onto CGRA. The task partitioning and scheduling are formulated as a joint optimization problem of minimizing the energy consumption. The nonlinear effects of real battery are taken into account in problem formulation. Using the insights from the problem formulation, we design the task-mapping algorithm. We have used several real-world benchmarks to test the effectiveness of the proposed method. Experiment results show that our method can dramatically lower the energy consumption and prolong the battery-life.
- Publication
- IEICE TRANSACTIONS on Information Vol.E96-D No.12 pp.2524-2535
- Publication Date
- 2013/12/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.E96.D.2524
- Type of Manuscript
- Special Section PAPER (Special Section on Parallel and Distributed Computing and Networking)
- Category
Authors
Shouyi YIN
Tsinghua University
Rui SHI
Tsinghua University
Leibo LIU
Tsinghua University
Shaojun WEI
Tsinghua University
Keyword
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Shouyi YIN, Rui SHI, Leibo LIU, Shaojun WEI, "Battery-Aware Task Mapping for Coarse-Grained Reconfigurable Architecture" in IEICE TRANSACTIONS on Information,
vol. E96-D, no. 12, pp. 2524-2535, December 2013, doi: 10.1587/transinf.E96.D.2524.
Abstract: Coarse-grained Reconfigurable Architecture (CGRA) is a parallel computing platform that provides both high performance of hardware and high flexibility of software. It is becoming a promising platform for embedded and mobile applications. Since the embedded and mobile devices are usually battery-powered, improving battery lifetime becomes one of the primary design issues in using CGRAs. In this paper, we propose a battery-aware task-mapping method to optimize energy consumption and improve battery lifetime. The proposed method mainly addresses two problems: task partitioning and task scheduling when mapping applications onto CGRA. The task partitioning and scheduling are formulated as a joint optimization problem of minimizing the energy consumption. The nonlinear effects of real battery are taken into account in problem formulation. Using the insights from the problem formulation, we design the task-mapping algorithm. We have used several real-world benchmarks to test the effectiveness of the proposed method. Experiment results show that our method can dramatically lower the energy consumption and prolong the battery-life.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E96.D.2524/_p
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@ARTICLE{e96-d_12_2524,
author={Shouyi YIN, Rui SHI, Leibo LIU, Shaojun WEI, },
journal={IEICE TRANSACTIONS on Information},
title={Battery-Aware Task Mapping for Coarse-Grained Reconfigurable Architecture},
year={2013},
volume={E96-D},
number={12},
pages={2524-2535},
abstract={Coarse-grained Reconfigurable Architecture (CGRA) is a parallel computing platform that provides both high performance of hardware and high flexibility of software. It is becoming a promising platform for embedded and mobile applications. Since the embedded and mobile devices are usually battery-powered, improving battery lifetime becomes one of the primary design issues in using CGRAs. In this paper, we propose a battery-aware task-mapping method to optimize energy consumption and improve battery lifetime. The proposed method mainly addresses two problems: task partitioning and task scheduling when mapping applications onto CGRA. The task partitioning and scheduling are formulated as a joint optimization problem of minimizing the energy consumption. The nonlinear effects of real battery are taken into account in problem formulation. Using the insights from the problem formulation, we design the task-mapping algorithm. We have used several real-world benchmarks to test the effectiveness of the proposed method. Experiment results show that our method can dramatically lower the energy consumption and prolong the battery-life.},
keywords={},
doi={10.1587/transinf.E96.D.2524},
ISSN={1745-1361},
month={December},}
Copy
TY - JOUR
TI - Battery-Aware Task Mapping for Coarse-Grained Reconfigurable Architecture
T2 - IEICE TRANSACTIONS on Information
SP - 2524
EP - 2535
AU - Shouyi YIN
AU - Rui SHI
AU - Leibo LIU
AU - Shaojun WEI
PY - 2013
DO - 10.1587/transinf.E96.D.2524
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E96-D
IS - 12
JA - IEICE TRANSACTIONS on Information
Y1 - December 2013
AB - Coarse-grained Reconfigurable Architecture (CGRA) is a parallel computing platform that provides both high performance of hardware and high flexibility of software. It is becoming a promising platform for embedded and mobile applications. Since the embedded and mobile devices are usually battery-powered, improving battery lifetime becomes one of the primary design issues in using CGRAs. In this paper, we propose a battery-aware task-mapping method to optimize energy consumption and improve battery lifetime. The proposed method mainly addresses two problems: task partitioning and task scheduling when mapping applications onto CGRA. The task partitioning and scheduling are formulated as a joint optimization problem of minimizing the energy consumption. The nonlinear effects of real battery are taken into account in problem formulation. Using the insights from the problem formulation, we design the task-mapping algorithm. We have used several real-world benchmarks to test the effectiveness of the proposed method. Experiment results show that our method can dramatically lower the energy consumption and prolong the battery-life.
ER -
English
