EAFT: Evolutionary Algorithms for GCC Flag Tuning

Burak Tagtekin, Tuna Çakar
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Abstract

Due to limited resources, some methods come to the fore in finding and applying the factors that affect the working time of the code. The most common one is choosing the correct GCC flags using heuristic algorithms. For the codes compiled with GCC, the selection of optimization flags directly affects the speed of the processing, however, choosing the right one among hundreds of markers during this process is a resource consuming problem. This article explains how to solve the GCC flag optimization problem with EAFT. Rather than other autotuner tools such as Opentuner, EAFT is an optimized tool for GCC marker selection. Search infrastructure has been developed with particle swarm optimization and genetic algorithm with diffent submodels rather than using only Genetic Algorithm like FOGA.
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GCC标志调优的进化算法
由于资源有限,一些方法在寻找和应用影响代码工作时间的因素方面脱颖而出。最常见的是使用启发式算法选择正确的GCC标志。对于使用GCC编译的代码,优化标志的选择直接影响处理速度,然而,在此过程中从数百个标记中选择正确的标记是一个消耗资源的问题。本文解释了如何使用EAFT解决GCC标志优化问题。与Opentuner等其他自动调谐器工具不同,EAFT是用于GCC标记选择的优化工具。基于粒子群优化和不同子模型的遗传算法开发了搜索基础架构,而不仅仅是像FOGA这样的遗传算法。
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