一句话：提出 Artemis++，用遗传算法自动探索并转换数据结构，以优化 C++ 程序性能。
开发者常因评估成本高而沿用低效的数据结构或库接口，缺乏自动化设计空间探索工具。本文提出代码优化方案 Artemis++，通过遗传优化自动搜索并实施数据结构的替换与程序变换，从而提升软件性能。初步评估在三个主流 C++ 库上进行，结果显示 CPU 使用率最高改善 16.09%，运行时最高改善 27.90%，内存最高改善 2.74%。
Software developers sometimes use inefficient data structures or library interfaces without considering the potential impact they may have during the runtime of a program. This is due to the significant effort required to research and evaluate possibly more efficient alternatives. Consequently, there is a need for tooling to automate the design space exploration. Our proposed code optimisation solution, called Artemis++, tries to address this issue with automatic exploration and transformation of data structures to optimise software performance. In preliminary testing on three mainstream C++ libraries, we have observed improvements up to 16.09%, 27.90%, and 2.74% for CPU usage, runtime and memory, respectively.
DOI 原文 ·
@inproceedings{paperbot6520,
title = {Genetic Optimisation of C++ Applications},
author = {Rafail Giavrimis and Alexis Butler and Constantin Cezar Petrescu and Michail Basios and Santanu Kumar Dash},
booktitle = {ASE},
year = {2021},
doi = {10.1109/ase51524.2021.9678650}
}