Energy-aware adaptation for mobile applications
Proceedings of the seventeenth ACM symposium on Operating systems principles
System-level power optimization: techniques and tools
ACM Transactions on Design Automation of Electronic Systems (TODAES)
The design, implementation, and evaluation of a compiler algorithm for CPU energy reduction
PLDI '03 Proceedings of the ACM SIGPLAN 2003 conference on Programming language design and implementation
21st Century Compilers
A trace-based binary compilation framework for energy-aware computing
Proceedings of the 2004 ACM SIGPLAN/SIGBED conference on Languages, compilers, and tools for embedded systems
PACE: A New Approach to Dynamic Voltage Scaling
IEEE Transactions on Computers
Power reduction techniques for microprocessor systems
ACM Computing Surveys (CSUR)
Dynamic voltage scaling techniques for power efficient video decoding
Journal of Systems Architecture: the EUROMICRO Journal
Optimality and improvement of dynamic voltage scaling algorithms for multimedia applications
Proceedings of the 45th annual Design Automation Conference
The Compiler Design Handbook: Optimizations and Machine Code Generation, Second Edition
The Compiler Design Handbook: Optimizations and Machine Code Generation, Second Edition
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In recent scenarios, power consumption is critical for battery operated devices. There are wide varieties of implementations of dynamic voltage scaling (DVS) algorithm to reduce energy or power. This paper presents a framework called PERMA, power estimator and reducer for multi-core architectures. The PERMA estimates power consumption and suggests analytical procedure to reduce power consumption at basic block level rather than at region level using clock cycles of instructions for a particular architecture (x86). PERMA estimates execution time for each basic block for various voltage levels and chooses best out of these. Therefore, PERMA evaluates the extent to which the voltage can be varied for various Basic Blocks to reduce power consumption without degrading execution time. Finally, it is tested for matrix multiplication of various sizes. There is an improvement in the execution time up to 33.43% with PERMA and 21.89% without PERMA.