Performance Research and Optimization on CPython’s Interpreter

Abstract

Abstract-In this paper, the performance research on CPython's latest interpreter is presented, concluding that bytecode dispatching takes about 25 percent of total execution time on average. Based on this observation, a novel bytecode dispatching mechanism is proposed to reduce the time spent on this phase to a minimum. With this mechanism, the blocks associated with each kind of bytecodes are rewritten in hand-tuned assembly, their opcodes are renumbered, and their memory spaces are rescheduled. With these preparations, this new bytecode dispatching mechanism replaces the time-consuming memory reading operations with rapid operations on registers.This mechanism is implemented in CPython-3.3.0. Experiments on lots of benchmarks demonstrate its correctness and efficiency. The comparison between original CPython and optimized CPython shows that this new mechanism achieves about 8.5 percent performance improvement on average. For some particular benchmarks, the maximum improvement is up to 18 percentages.

Accidental Choices—How JVM Choice and Associated Build Tools Affect Interpreter Performance

“…Nonetheless, performance analysis of early releases of the language was characterised as providing poor performance relative to traditional compiled languages [7,9], with early comparisons of execution time performance of Java code showing significant underperformance relative to C or C++ code [7,[20][21][22][23]. The Java interpreter was especially slow [8,24] in contrast to code compiled to native code [25][26][27], or even Java JIT-compiled code [27], performance challenges that persist with contemporary language interpreters [28][29][30].…”