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JOG: Java JIT Peephole Optimizations and Tests from Patterns.

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Bibliographic Details
Title:	JOG: Java JIT Peephole Optimizations and Tests from Patterns.
Authors:	Zang, Zhiqiang, Thimmaiah, Aditya, Gligoric, Milos
Source:	ICSE: International Conference on Software Engineering; 2024, p11-15, 5p
Subject Terms:	JAVA programming language, COMPILERS (Computer programs), C++, OPTIMIZATION algorithms, JUST-in-time systems
Abstract:	We present JOG, a framework for developing peephole optimizations and accompanying tests for Java compilers. JOG allows developers to write a peephole optimization as a pattern in Java itself. Such a pattern contains code before and after the desired transformation defined by the peephole optimization, with any necessary preconditions, and the pattern can be written in the same way that tests for the optimization are already written in OpenJDK. JOG automatically translates each pattern into C/C++ code as a JIT optimization pass, and generates tests for the optimization. Also, JOG automatically analyzes the shadow relation between a pair of optimizations where the effect of the shadowed optimization is overridden by the other. We used JOG to write 162 patterns, including many patterns found in OpenJDK and LLVM, as well as some that we proposed. We opened ten pull requests (PRs) for OpenJDK, on introducing new optimizations, removing shadowed optimizations, and adding generated tests for optimizations; nine of PRs have already been integrated into the master branch of OpenJDK. The demo video for JOG can be found at https://youtu.be/z2q6dhOiqgw. [ABSTRACT FROM AUTHOR]
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Database:	Complementary Index

Description
Abstract:	We present JOG, a framework for developing peephole optimizations and accompanying tests for Java compilers. JOG allows developers to write a peephole optimization as a pattern in Java itself. Such a pattern contains code before and after the desired transformation defined by the peephole optimization, with any necessary preconditions, and the pattern can be written in the same way that tests for the optimization are already written in OpenJDK. JOG automatically translates each pattern into C/C++ code as a JIT optimization pass, and generates tests for the optimization. Also, JOG automatically analyzes the shadow relation between a pair of optimizations where the effect of the shadowed optimization is overridden by the other. We used JOG to write 162 patterns, including many patterns found in OpenJDK and LLVM, as well as some that we proposed. We opened ten pull requests (PRs) for OpenJDK, on introducing new optimizations, removing shadowed optimizations, and adding generated tests for optimizations; nine of PRs have already been integrated into the master branch of OpenJDK. The demo video for JOG can be found at https://youtu.be/z2q6dhOiqgw. [ABSTRACT FROM AUTHOR]
DOI:	10.1145/3639478.3640040