Popularity Prediction for Social Media over Arbitrary Time Horizons
Daniel Haimovich, Dima Karamshuk, Thomas Leeper, Evgeniy Riabenko, Milan Vojnovic
Programming Language Design and Implementation (PLDI)
Dynamic languages such as PHP, JavaScript, Python, and Ruby have been gaining popularity over the last two decades. A very popular domain for these languages is web development, including server-side development of large-scale websites. As a result, improving the performance of these languages has become more important. Efficiently compiling programs in these languages is challenging, and many popular dynamic languages still lack efficient production quality implementations. This paper describes the design of the second generation of the HHVM JIT and how it addresses the challenges to efficiently execute PHP and Hack programs. This new design uses profiling to build an aggressive region-based JIT compiler. We discuss the benefits of this approach compared to the more popular method-based and trace-based approaches to compile dynamic languages. Our evaluation running a very large PHP-based code base, the Facebook website, demonstrates the effectiveness of the new JIT design.
Daniel Haimovich, Dima Karamshuk, Thomas Leeper, Evgeniy Riabenko, Milan Vojnovic
Liqi Yan, Qifan Wang, Yiming Cu, Fuli Feng, Xiaojun Quan, Xiangyu Zhang, Dongfang Liu
Barlas Oğuz, Kushal Lakhotia, Anchit Gupta, Patrick Lewis, Vladimir Karpukhin, Aleksandra Piktus, Xilun Chen, Sebastian Riedel, Wen-tau Yih, Sonal Gupta, Yashar Mehdad