Widely used compilers like GCC and LLVM usually have hundreds of optimizations controlled by optimization flags, which are enabled or disabled during compilation to improve runtime performance (e.g., small execution time) of the compiler program. Due to the large number of optimization flags and their combination, it is difficult for compiler users to manually tune compiler optimization flags. In the literature, a number of autotuning techniques have been proposed, which tune optimization flags for a compiled program by comparing its actual runtime performance with different optimization flag combination. Due to the huge search space and heavy actual runtime cost, these techniques suffer from the widely-recognized efficiency problem. To reduce the heavy runtime cost, in this paper we propose a lightweight learning approach which uses a small number of actual runtime performance data to predict the runtime performance of a compiled program with various optimization flag combinations. Furthermore, to reduce the search space, we design a novel particle swarm algorithm which tunes compiler optimization flags with the prediction model. To evaluate the performance of the proposed approach CompTuner, we conduct an extensive experimental study on two popular C compilers GCC and LLVM with two widely used benchmarks cBench and PolyBench. The experimental results show that CompTuner significantly outperforms the six compared techniques, including the state-of-art technique BOCA.
Wed 25 JunDisplayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
11:00 - 12:30 | CompilerResearch Papers / Journal First / Ideas, Visions and Reflections at Cosmos 3C Chair(s): Na Meng Virginia Tech | ||
11:00 20mTalk | De-duplicating Silent Compiler Bugs via Deep Semantic Representation Research Papers Junjie Chen Tianjin University, Xingyu Fan Tianjin University, Chen Yang Tianjin University, Shuang Liu Renmin University of China, Jun Sun Singapore Management University DOI | ||
11:20 20mTalk | DiSCo: Towards Decompiling EVM Bytecode to Source Code using Large Language Models Research Papers Xing Su National Key Lab for Novel Software Technology, Nanjing University, China, Hanzhong Liang National Key Lab for Novel Software Technology, Nanjing University, China, Hao Wu , Ben Niu State Key Laboratory of Information Security, Institute of Information Engineering, China, Fengyuan Xu National Key Lab for Novel Software Technology, Nanjing University, China, Sheng Zhong National Key Lab for Novel Software Technology, Nanjing University, China DOI | ||
11:40 20mTalk | Compiler Autotuning through Multiple Phase Learning Journal First | ||
12:00 20mTalk | PDCAT: Preference-Driven Compiler Auto-Tuning Research Papers Mingxuan Zhu Peking University, Zeyu Sun Institute of Software, Chinese Academy of Sciences, Dan Hao Peking University DOI | ||
12:20 10mTalk | Compiler Optimization Testing Based on Optimization-Guided Equivalence Transformations Ideas, Visions and Reflections Jingwen Wu Shandong University, Jiajing Zheng Shandong University, Zhenyu Yang Shandong University, Zhongxing Yu Shandong University | ||
Cosmos 3C is the third room in the Cosmos 3 wing.
When facing the main Cosmos Hall, access to the Cosmos 3 wing is on the left, close to the stairs. The area is accessed through a large door with the number “3”, which will stay open during the event.