Optimizing the power consumption is an important topic in embedded system engineering, especially for embedded systems that use battery power source.Power optimization can be achieved by software techniques and instruction scheduling is an effective software pproach for reducing power cost of processor(s). In this thesis, we propose our idea of using agenetic algorithm forlow power instruction scheduling.Our algorithm is applied to each basic block of assembly code to generate lower power program. In the experiment section, we use two open source simulation tools that are SimpleScalar Tool Set and SimplePower, the algorithmis applied to assembly programs of SimpleScalar Instruction Set, these programs are compiled and then have their power consumptions measured by SimplePower. The experimental results showed the effectiveness of our proposed method. This scheduling method will be combined with the idea of reducing memory access for low power design in our further work.
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Optimizing the power consumption is an important topic in embedded system engineering, especially for embedded systems that use battery power source.Power optimization can be achieved by software techniques and instruction scheduling is an effective software pproach for reducing power cost of processor(s). In this thesis, we propose our idea of using agenetic algorithm forlow power instruction scheduling.Our algorithm is applied to each basic block of assembly code to generate lower power program. In the experiment section, we use two open source simulation tools that are SimpleScalar Tool Set and SimplePower, the algorithmis applied to assembly programs of SimpleScalar Instruction Set, these programs are compiled and then have their power consumptions measured by SimplePower. The experimental results showed the effectiveness of our proposed method. This scheduling method will be combined with the idea of reducing memory access for low power design in our further work.
