113 citations · 232 across the 18 of their papers we have counts for
7 papers · 1 filter
Deep Data Flow Analysis
Chris Cummins, Hugh Leather, Zacharias Fisches +3
Compiler architects increasingly look to machine learning when building heuristics for compiler optimization. The promise of automatic heuristic design, freeing the compiler engine…
Modeling Black-Box Components with Probabilistic Synthesis
Bruce Collie, Jackson Woodruff, Michael F. P. O'Boyle
This paper is concerned with synthesizing programs based on black-box oracles: we are interested in the case where there exists an executable implementation of a component or libra…
M3: Semantic API Migrations
Bruce Collie, Philip Ginsbach, Jackson Woodruff +2
Library migration is a challenging problem, where most existing approaches rely on prior knowledge. This can be, for example, information derived from changelogs or statistical mod…
Optimizing Grouped Convolutions on Edge Devices
Perry Gibson, José Cano, Jack Turner +3
When deploying a deep neural network on constrained hardware, it is possible to replace the network's standard convolutions with grouped convolutions. This allows for substantial m…
Retrofitting Symbolic Holes to LLVM IR
Bruce Collie, Michael O'Boyle
Symbolic holes are one of the fundamental building blocks of solver-aided and interactive programming. Unknown values can be soundly integrated into programs, and automated tools s…
TASO: Time and Space Optimization for Memory-Constrained DNN Inference
Yuan Wen, Andrew Anderson, Valentin Radu +2
Convolutional neural networks (CNNs) are used in many embedded applications, from industrial robotics and automation systems to biometric identification on mobile devices. State-of…
Automatically Harnessing Sparse Acceleration
Philip Ginsbach, Bruce Collie, Michael F. P. O'Boyle
Sparse linear algebra is central to many scientific programs, yet compilers fail to optimize it well. High-performance libraries are available, but adoption costs are significant.…