基于四阶段人工优化的软件流水技术

Software Pipelining Technique Based on Four-Phase Manual Optimization

代码体积是优化存储资源有限的嵌入式系统的重要因素之一。针对该特点,使用oprofile性能分析工具,以EEMBC基准程序集作为工作负载,提出四阶段人工优化软件流水方法(FPMO)。电信类的自相关程序实验结果表明,FPMO以2.04%的代码增量为代价换来40.678%的性能提升,而单纯的编译器自动优化则以33.35%的体积膨胀换来38.33%的性能提升。

For embedded systems with very limited memory resources, code size becomes one of the most important optimization concerns. Using the oprofile profiling tool, this paper focuses on the Four-Phase Manual Optimization（FPMO） for the software pipelining technique when running the EEMBC benchmark. Experimental result of telecom-autocorrelation shows the FPMO method gets 40.678% performance promotion by increasing 2.04% code size but the pure compiler automatic optimization trades 38.33% performance improvements by 33.35% code size expansion.