DLS 2019
Sun 20 - Fri 25 October 2019 Athens, Greece
co-located with SPLASH 2019
Sun 20 Oct 2019 14:30 - 15:00 at Room 2A - Optimizing Computations Chair(s): Marc Feeley

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 Oct
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14:00 - 15:30: Optimizing ComputationsDLS 2019 at Room 2A
Chair(s): Marc FeeleyUniversité de Montréal
14:00 - 14:30
Reflections on the Compatibility, Performance, and Scalability of Parallel PythonExperience Paper
DLS 2019
Remigius MeierETH Zurich, Switzerland, Thomas GrossETH Zurich, Switzerland
14:30 - 15:00
R Melts Brains -- An IR for First-Class Environments and Lazy Effectful ArgumentsResearch Paper
DLS 2019
Olivier FlückigerNortheastern University, Guido ChariCzech Technical University, Jan JečmenCzech Technical University, Ming-Ho YeeNortheastern University, Jakob HainNortheastern University, Jan VitekNortheastern University
Link to publication DOI Pre-print Media Attached
15:00 - 15:30
Python Programmers have GPUs too: Automatic Python Loop Parallelization with Staged Dependence AnalysisResearch Paper
DLS 2019
Dejice JacobUniversity of Glasgow, Phil TrinderUniversity of Glasgow, Jeremy SingerUniversity of Glasgow
Link to publication DOI Authorizer link