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- W2922037604 abstract "Inlining is one of the most important compiler optimizations. It reduces call overheads and widens the scope of other optimizations. But, inlining is somewhat of a black art of an optimizing compiler, and was characterized as a computationally intractable problem. Intricate heuristics, tuned during countless hours of compiler engineering, are often at the core of an inliner implementation. And despite decades of research, well- established inlining heuristics are still missing. In this paper, we describe a novel inlining algorithm for JIT compilers that incrementally explores a program’s call graph, and alternates between inlining and optimizations. We devise three novel heuristics that guide our inliner: adaptive decision thresholds, callsite clustering, and deep inlining trials. We implement the algorithm inside Graal, a dynamic JIT compiler for the HotSpot JVM. We evaluate our algorithm on a set of industry-standard benchmarks, including Java DaCapo, Scalabench, Spark-Perf, STMBench7 and other benchmarks, and we conclude that it significantly improves performance, surpassing state-of-the-art inlining approaches with speedups ranging from 5% up to $3times.$" @default.
- W2922037604 created "2019-03-22" @default.
- W2922037604 creator A5029837015 @default.
- W2922037604 creator A5043562961 @default.
- W2922037604 creator A5069165515 @default.
- W2922037604 creator A5085768233 @default.
- W2922037604 date "2019-02-16" @default.
- W2922037604 modified "2023-10-03" @default.
- W2922037604 title "An optimization-driven incremental inline substitution algorithm for just-in-time compilers" @default.
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- W2922037604 doi "https://doi.org/10.5555/3314872.3314893" @default.
- W2922037604 hasPublicationYear "2019" @default.
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