Sun 4 Nov 2018 14:30 - 14:55 at Stuart - Keynote: Stenman Chair(s): Stephen Kell

Compilers provide many architecture-agnostic, high-level optimizations trading off peak performance for code size. High-level optimizations typically cannot precisely reason about their impact, as they are applied before the final shape of the generated machine code can be determined. However, they still need a way to estimate their transformation’s impact on the performance of a compilation unit. Therefore, compilers typically resort to model these estimations as trade-off functions that heuristically guide optimization decisions. Compilers such as Graal implement many such handcrafted heuristic trade-off functions, which are tuned for one particular high-level optimization. Heuristic trade-off functions base their reasoning on limited knowledge of the compilation unit, often causing transformations that heavily increase code size or even decrease performance. To address this problem, we propose a cost model for Graal’s high-level intermediate representation that models relative operation latencies and operation sizes in order to be used in trade-off functions of compiler optimizations. We implemented the cost model in Graal and used it in two code-duplication-based optimizations. This allowed us to perform a more fine-grained code size trade-off in existing compiler optimizations, reducing the code size increase of our optimizations by up to $50%$ without sacrificing performance. Our evaluation demonstrates that the cost model allows optimizations to perform fine-grained code size and performance trade-offs outperforming hard-coded heuristics.

Sun 4 Nov

13:30 - 15:00: VMIL 2018 - Keynote: Stenman at Stuart
Chair(s): Stephen KellUniversity of Kent
vmil-201813:30 - 14:30
vmil-201814:30 - 14:55
Research paper
David LeopoldsederJohannes Kepler University Linz, Lukas StadlerOracle Labs, Austria, Manuel RiggerJohannes Kepler University Linz, Thomas WuerthingerOracle Labs, Hanspeter MössenböckJKU Linz, Austria