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Code Size Reduction and Execution performance Improvement with Instruction Set Architecture Design based on Non-homogeneous Register Partition
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  • Code Size Reduction and Execution performance Improvement with Instruction Set Architecture Design based on Non-homogeneous Register Partition
  • Code Size Reduction and Execution performance Improvement with Instruction Set Architecture Design based on Non-homogeneous Register Partition
저자명
권영준,이혁재,Kwon. Young-Jun,Lee. Hyuk-Jae
간행물명
전기학회논문지. The transactions of the Korean Institute of Electrical Engineers. A / A, 전력기술부문
권/호정보
1999년|48권 12호|pp.1575-1579 (5 pages)
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대한전기학회
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정기간행물|ENG|
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이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
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기타언어초록

Embedded processors often accommodate two instruction sets, a standard instruction set and a compressed instruction set. With the compressed instruction set, code size can be reduced while instruction count (and consequently execution time) can be increased. To achieve code size reduction without significant increase of execution time, this paper proposes a new compressed instruction set architecture, called TOE (Two Operations Execution). The proposed instruction set format includes the parallel bit that indicates an instruction can be executed simultaneously with the next instruction. To add the parallel bit, TOE instruction format reduces the destination register field. The reduction of the register field limits the number of registers that are accessible by an instruction. To overcome the limited accessibility of registers, TOE adapts non-homogeneous register partition in which registers are divided into multiple subsets, each of which are accessed by different groups of instructions. With non-homogeneous registers, each instruction can access only a limited number of registers, but an entire program can access all available registers. With efficient non-homogeneous register allocator, all registers can be used in a balanced manner. As a result, the increase of code size due to register spills is negligible. Experimental results show that more than 30% of TOE instructions can be executed in parallel without significant increase of code size when compared to existing Thumb instruction set.