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Chris Cummins

3 accepted papers

2023

Learning Compiler Pass Orders using Coreset and Normalized Value Prediction

ICML 2023poster

Finding the optimal pass sequence of compilation can lead to a significant reduction in program size. Prior works on compilation pass ordering have two major drawbacks. They either require an excessive budget (in terms of the number of compilation passes) at compile time or fail to generalize to uns…

2021

Learning Space Partitions for Path Planning

NeurIPS 2021poster

Path planning, the problem of efficiently discovering high-reward trajectories, often requires optimizing a high-dimensional and multimodal reward function. Popular approaches like CEM and CMA-ES greedily focus on promising regions of the search space and may get trapped in local maxima. DOO and VOO…

2021

ProGraML: A Graph-based Program Representation for Data Flow Analysis and Compiler Optimizations

ICML 2021spotlight

Machine learning (ML) is increasingly seen as a viable approach for building compiler optimization heuristics, but many ML methods cannot replicate even the simplest of the data flow analyses that are critical to making good optimization decisions. We posit that if ML cannot do that, then it is insu…