Survey of low power techniques for ROMs
ISLPED '97 Proceedings of the 1997 international symposium on Low power electronics and design
Computer architecture (2nd ed.): a quantitative approach
Computer architecture (2nd ed.): a quantitative approach
ISLPED '98 Proceedings of the 1998 international symposium on Low power electronics and design
Synthesis of application-specific memories for power optimization in embedded systems
Proceedings of the 37th Annual Design Automation Conference
A power reduction technique with object code merging for application specific embedded processors
DATE '00 Proceedings of the conference on Design, automation and test in Europe
Proceedings of the 39th annual Design Automation Conference
Proceedings of the 15th international symposium on System Synthesis
An Architectural Level Energy Reduction Technique For Deep-Submicron Cache Memories
ASP-DAC '02 Proceedings of the 2002 Asia and South Pacific Design Automation Conference
A low power approach to system level pipelined interconnect design
Proceedings of the 2004 international workshop on System level interconnect prediction
A static and dynamic energy reduction technique for I-cache and BTB in embedded processors
Proceedings of the 2004 Asia and South Pacific Design Automation Conference
A leakage-energy-reduction technique for highly-associative caches in embedded systems
MEDEA '03 Proceedings of the 2003 workshop on MEmory performance: DEaling with Applications , systems and architecture
CAD for nanometer silicon design challenges and success
IEEE Transactions on Very Large Scale Integration (VLSI) Systems - Nanoelectronic circuits and systems
Simultaneous optimization of memory configuration and code allocation for low power embedded systems
Proceedings of the 18th ACM Great Lakes symposium on VLSI
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A system level approach for a memory power reduction is proposed in this paper. The basic idea is allocating frequently executed object codes into a small subprogram memory and optimizing supply voltage and threshold voltage of the subprogram memory. Since large scale memory contains a lot of direct paths from power supply to round, power dissipation caused by subthreshold leakage current is more serious than dynamic power dissipation. Our approach optimizes the size of subprogram memory, supply voltage, and threshold voltage so as to minimize memory power dissipation including static power dissipation caused by leakage current. A heuristic algorithm which determines code allocation, supply voltage, and threshold voltage simultaneously so as to minimize power dissipation of memories is proposed as well. Our experiments with some benchmark programs demonstrate significant energy reductions up to 80% over a program memory which does not employ our approach.