113 citations · 232 across the 18 of their papers we have counts for
19 papers
SLaDe: A Portable Small Language Model Decompiler for Optimized Assembly
Jordi Armengol-Estapé, Jackson Woodruff, Chris Cummins +1
Decompilation is a well-studied area with numerous high-quality tools available. These are frequently used for security tasks and to port legacy code. However, they regularly gener…
Matching Linear Algebra and Tensor Code to Specialized Hardware Accelerators
Pablo Antonio Martínez, Jackson Woodruff, Jordi Armengol-Estapé +3
Dedicated tensor accelerators demonstrate the importance of linear algebra in modern applications. Such accelerators have the potential for impressive performance gains, but requir…
Learning C to x86 Translation: An Experiment in Neural Compilation
Jordi Armengol-Estapé, Michael F. P. O'Boyle
Deep learning has had a significant impact on many fields. Recently, code-to-code neural models have been used in code translation, code refinement and decompilation. However, the…
Neural Architecture Search as Program Transformation Exploration
Jack Turner, Elliot J. Crowley, Michael O'Boyle
Improving the performance of deep neural networks (DNNs) is important to both the compiler and neural architecture search (NAS) communities. Compilers apply program transformations…
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…