2008•Journal of Zhejiang University. Science ARequires access

Efficient SIMD optimization for media processors

Jianpeng Zhou, Ce Shi

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Abstract

Single instruction multiple data (SIMD) instructions are often implemented in modern media processors. Although SIMD instructions are useful in multimedia applications, most compilers do not have good support for SIMD instructions. This paper focuses on SIMD instructions generation for media processors. We present an efficient code optimization approach that is integrated into a retargetable C compiler. SIMD instructions are generated by finding and combining the same operations in programs. Experimental results for the UltraSPARC VIS instruction set show that a speedup factor up to 2.639 is obtained.

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What this paper is about

Single instruction multiple data (SIMD) instructions are often implemented in modern media processors. Although SIMD instructions are useful in multimedia applications, most compilers do not have good support for SIMD instructions. This paper focuses on SIMD instructions generation for media processors. We present an efficient code optimization approach that is integrated into a retargetable C compiler. SIMD instructions are generated by finding and combining the same operations in programs. Experimental results for the UltraSPARC VIS instruction set show that a speedup factor up to 2.639 is obtained.

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Available abstract

Single instruction multiple data (SIMD) instructions are often implemented in modern media processors. Although SIMD instructions are useful in multimedia applications, most compilers do not have good support for SIMD instructions. This paper focuses on SIMD instructions generation for media processors. We present an efficient code optimization approach that is integrated into a retargetable C compiler. SIMD instructions are generated by finding and combining the same operations in programs. Experimental results for the UltraSPARC VIS instruction set show that a speedup factor up to 2.639 is obtained.

Key concepts: SIMD, Compiler, Computer science, Parallel computing, Speedup, Code (set theory), Instruction set, Optimizing compiler

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