演讲人：王峥 英国兰卡斯特大学助理
时间：2018 年 3 月 30 日（周五）
地点：张江校区软件楼 102 第二会议室
联系人：李弋 liy@fudan.edu.cn
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 two of our recent award-winning studies that use deep learning to generate synthetic benchmarks and to automate the design process of compiler optimisation heuristics.
简历:
王峥目前是英国兰卡斯特大学助理教授，他的主要研究方向是编译技术及并行程序优化。王峥于 2011 年在英国爱丁堡大学取得博士学位。在此之前他在 IBM 中国研究院从事并行编程模型的研究工作。王峥的研究工作首创性的将机器学习的方法应用于并行程序优化中。目前已经在相关高水平会议和权威期刊发表 40 余篇相关论文。部分工作获得 PACT 2010， PACT 2017, CGO 2017 的最佳论文奖，以及 PACT 2010, CGO 2013 大会最佳报告奖。相关工作被 10 多所大学在编译课程中选讲。
