Source code optimization can heavily improve software code implementation quality while still being complementary to conventional compilers’ optimizations. Source code analysis tools are very useful in supporting source code optimization. This article discusses MemAssist, a source-level optimization environment for semi-automatic locality optimization of loop-dominated code. MemAssist applies reuse distance analysis and a relevant optimization algorithm to explore the design space. It generates a set of suggestions for locality optimizing loop transformations that reduce data cache miss rate and execution time. MemAssist has been used to optimize a number of applications. Experimental results show that MemAssist leads to cache miss rate reduction at all cache layers, memory accesses reduction by up to 42%, and to a speedup of up to three times. Therefore, MemAssist can be used for efficient early-stage software optimization leading to development effort and time reduction.

中文翻译：

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基于重用距离分析的环路主导应用的局部优化器

源代码优化可以极大地提高软件代码的实现质量，同时仍然是对传统编译器优化的补充。源代码分析工具在支持源代码优化方面非常有用。本文讨论了 MemAssist，这是一种源级优化环境，用于对循环主导的代码进行半自动位置优化。MemAssist 应用重用距离分析和相关优化算法来探索设计空间。它为降低数据缓存未命中率和执行时间的局部优化循环转换生成一组建议。MemAssist 已用于优化许多应用程序。实验结果表明，MemAssist 可以降低所有缓存层的缓存未命中率，内存访问减少高达 42%，加速高达 3 倍。