Allocation removal by partial evaluation in a tracing JIT
Carl Friedrich Bolz, Antonio Cuni, Maciej FijaBkowski, Michaël Leuschel, Samuele Pedroni, Armin Rigo
Abstract
Carl Friedrich Bolz, Antonio Cuni, Maciej FijaBkowski, Michaël Leuschel, Samuele Pedroni, Armin Rigo
Abstract
The performance of many dynamic language implementations suffers from high allocation rates and runtime type checks. This makes dynamic languages less applicable to purely algorithmic problems, despite their growing popularity. In this paper we present a simple compiler optimization based on online partial evaluation to remove object allocations and runtime type checks in the context of a tracing JIT. We evaluate the optimization using a Python VM and find that it gives good results for all our (real-life) benchmarks.
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The performance of many dynamic language implementations suffers from high allocation rates and runtime type checks. This makes dynamic languages less applicable to purely algorithmic problems, despite their growing popularity. In this paper we present a simple compiler optimization based on online partial evaluation to remove object allocations and runtime type checks in the context of a tracing JIT. We evaluate the optimization using a Python VM and find that it gives good results for all our (real-life) benchmarks.
Key concepts: Computer science, Just-in-time compilation, Programming language, Python (programming language), Dynamic compilation, Tracing, Compiler, Partial evaluation