Voltage Reduction of Application-Specific Heterogeneous Multiprocessor Systems for Power Minimisation
Summary :
We present a design strategy to reduce power demands in application-specific, heterogeneous multiprocessor systems with interdependent subtasks. This power reduction scheme can be used with a randomised search such as a genetic algorithm where multiple trial solutions are tested. The scheme is applied to each trial solution after allocation and scheduling have been performed. Power savings are achieved by equally expanding each processor's execution time with a corresponding reduction in their respective operating voltage. Lowest cost solutions achieve average reductions of 24% while minimum power solutions average 58%.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E84-A No.9 pp.2296-2302
- Publication Date
- 2001/09/01
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- PAPER
- Category
- VLSI Design Technology and CAD
Authors
Keyword
Latest Issue
Copyrights notice of machine-translated contents
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Cite this
Copy
Allan RAE, Sri PARAMESWARAN, "Voltage Reduction of Application-Specific Heterogeneous Multiprocessor Systems for Power Minimisation" in IEICE TRANSACTIONS on Fundamentals,
vol. E84-A, no. 9, pp. 2296-2302, September 2001, doi: .
Abstract: We present a design strategy to reduce power demands in application-specific, heterogeneous multiprocessor systems with interdependent subtasks. This power reduction scheme can be used with a randomised search such as a genetic algorithm where multiple trial solutions are tested. The scheme is applied to each trial solution after allocation and scheduling have been performed. Power savings are achieved by equally expanding each processor's execution time with a corresponding reduction in their respective operating voltage. Lowest cost solutions achieve average reductions of 24% while minimum power solutions average 58%.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e84-a_9_2296/_p
Copy
@ARTICLE{e84-a_9_2296,
author={Allan RAE, Sri PARAMESWARAN, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Voltage Reduction of Application-Specific Heterogeneous Multiprocessor Systems for Power Minimisation},
year={2001},
volume={E84-A},
number={9},
pages={2296-2302},
abstract={We present a design strategy to reduce power demands in application-specific, heterogeneous multiprocessor systems with interdependent subtasks. This power reduction scheme can be used with a randomised search such as a genetic algorithm where multiple trial solutions are tested. The scheme is applied to each trial solution after allocation and scheduling have been performed. Power savings are achieved by equally expanding each processor's execution time with a corresponding reduction in their respective operating voltage. Lowest cost solutions achieve average reductions of 24% while minimum power solutions average 58%.},
keywords={},
doi={},
ISSN={},
month={September},}
Copy
TY - JOUR
TI - Voltage Reduction of Application-Specific Heterogeneous Multiprocessor Systems for Power Minimisation
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2296
EP - 2302
AU - Allan RAE
AU - Sri PARAMESWARAN
PY - 2001
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E84-A
IS - 9
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - September 2001
AB - We present a design strategy to reduce power demands in application-specific, heterogeneous multiprocessor systems with interdependent subtasks. This power reduction scheme can be used with a randomised search such as a genetic algorithm where multiple trial solutions are tested. The scheme is applied to each trial solution after allocation and scheduling have been performed. Power savings are achieved by equally expanding each processor's execution time with a corresponding reduction in their respective operating voltage. Lowest cost solutions achieve average reductions of 24% while minimum power solutions average 58%.
ER -
English
