Machine Learning in Compilers
主講人：王崢,Associate Professor ,Lancaster University
時(shí)間： 2018年9月27日（周四）上午 10:00-11:30
地點(diǎn)： 計(jì)算所 446室
摘要：
Developing an optimising compiler is a highly skilled and arduous process and there is inevitably a software delay whenever a new processor is designed. It often takes several generations of a compiler to start to effectively exploit the processors' potential, by which time a new processor appears and the process starts again. This never-ending game of catch-up means that we rarely fully exploit a shipped processor and it inevitably delays time to market. As we move to multi- and many-core platforms, this problem increases.
This talk will look at research undertaken in my group which uses machine learning to automatically learn how to design compiler optimisation heuristics. It will discuss some of our award-winning studies that use deep learning to generate synthetic benchmarks and to automate the design process of compiler optimisation heuristics.
簡歷:
王崢目前是英國蘭卡斯特大學(xué)副教授，他的主要研究方向是編譯技術(shù)及并行程序優(yōu)化。王崢于2011年在英國愛丁堡大學(xué)取得博士學(xué)位，在此之前他在IBM中國研究院從事并行編程模型的研究工作。他目前已經(jīng)在并行計(jì)算寄編譯器相關(guān)的高水平會議和期刊發(fā)表50余篇相關(guān)論文。部分工作獲得PACT 2010， PACT 2017, CGO 2017的最佳論文獎(jiǎng)，以及PACT 2010, CGO 2013大會最佳報(bào)告獎(jiǎng)，相關(guān)工作被10多所大學(xué)在編譯課程中選講。