R Melts Brains -- An IR for First-Class Environments and Lazy Effectful ArgumentsResearch Paper
The R programming language combines a number of fea- tures considered hard to analyze and implement efficiently: dynamic typing, reflection, lazy evaluation, vectorized prim- itive types, first-class closures, and extensive use of native code. Additionally, variable scopes are reified at runtime as first-class environments. The combination of these features renders most static program analysis techniques impractical, and thus, compiler optimizations based on them ineffective. We present our work on PIR, an intermediate representa- tion with explicit support for first-class environments and effectful lazy evaluation. We describe two dataflow analyses on PIR: the first enables reasoning about variables and their environments, and the second infers where arguments are evaluated. Leveraging their results, we show how to elide environment creation and inline functions.
Sun 20 OctDisplayed time zone: Beirut change
14:00 - 15:30 | |||
14:00 30mTalk | Reflections on the Compatibility, Performance, and Scalability of Parallel PythonExperience Paper DLS 2019 | ||
14:30 30mTalk | R Melts Brains -- An IR for First-Class Environments and Lazy Effectful ArgumentsResearch Paper DLS 2019 Olivier Flückiger Northeastern University, Guido Chari Czech Technical University, Jan Ječmen Czech Technical University, Ming-Ho Yee Northeastern University, Jakob Hain Northeastern University, Jan Vitek Northeastern University Link to publication DOI Pre-print Media Attached | ||
15:00 30mTalk | Python Programmers have GPUs too: Automatic Python Loop Parallelization with Staged Dependence AnalysisResearch Paper DLS 2019 Dejice Jacob University of Glasgow, Phil Trinder University of Glasgow, Jeremy Singer University of Glasgow Link to publication DOI Authorizer link |