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2020 – today
- 2026
[c10]José Wesley de Souza Magalhães, Shideh Hashemian
, Alexander Brauckmann, Jackson Woodruff, Elizabeth Polgreen, Michael F. P. O'Boyle:
Accelerating Sparse Algebra with Program Synthesis. CC 2026: 106-118- 2025
- [j1]Yixuan Li, José Wesley de Souza Magalhães, Alexander Brauckmann, Michael F. P. O'Boyle, Elizabeth Polgreen:
Guided Tensor Lifting. Proc. ACM Program. Lang. 9(PLDI): 1984-2006 (2025) - [c9]José Wesley de Souza Magalhães, Jackson Woodruff, Jordi Armengol-Estapé, Alexander Brauckmann, Luc Jaulmes, Elizabeth Polgreen, Michael F. P. O'Boyle:
Guess, Measure & Edit: Using Lowering to Lift Tensor Code. PACT 2025: 216-228 - [c8]Alexander Brauckmann, Anderson Faustino da Silva, Gabriel Synnaeve, Michael F. P. O'Boyle, Jerónimo Castrillón, Hugh Leather:
DFA-Net: A Compiler-Specific Neural Architecture for Robust Generalization in Data Flow Analyses. CC 2025: 92-103 - [c7]Alexander Brauckmann, Luc Jaulmes, José Wesley de Souza Magalhães, Elizabeth Polgreen, Michael F. P. O'Boyle:
Tensorize: Fast Synthesis of Tensor Programs from Legacy Code using Symbolic Tracing, Sketching and Solving. CGO 2025: 15-30 - [i4]Yixuan Li, José Wesley de Souza Magalhães, Alexander Brauckmann, Michael F. P. O'Boyle, Elizabeth Polgreen:
Guided Tensor Lifting. CoRR abs/2504.19705 (2025) - 2023
- [c6]Alexander Brauckmann, Elizabeth Polgreen, Tobias Grosser, Michael F. P. O'Boyle:
mlirSynth: Automatic, Retargetable Program Raising in Multi-Level IR Using Program Synthesis. PACT 2023: 39-50 - [i3]Jackson Woodruff, Thomas Koehler, Alexander Brauckmann, Chris Cummins, Sam Ainsworth, Michael F. P. O'Boyle:
Rewriting History: Repurposing Domain-Specific CGRAs. CoRR abs/2309.09112 (2023) - [i2]Alexander Brauckmann, Elizabeth Polgreen, Tobias Grosser, Michael F. P. O'Boyle:
mlirSynth: Automatic, Retargetable Program Raising in Multi-Level IR using Program Synthesis. CoRR abs/2310.04196 (2023) - 2022
- [c5]Jordi Armengol-Estapé, Jackson Woodruff, Alexander Brauckmann, José Wesley de Souza Magalhães, Michael F. P. O'Boyle:
ExeBench: an ML-scale dataset of executable C functions. MAPS@PLDI 2022: 50-59 - 2021
- [c4]Alexander Brauckmann, Andrés Goens, Jerónimo Castrillón:
PolyGym: Polyhedral Optimizations as an Environment for Reinforcement Learning. PACT 2021: 17-29 - [i1]Alexander Brauckmann, Andrés Goens, Jerónimo Castrillón:
A Reinforcement Learning Environment for Polyhedral Optimizations. CoRR abs/2104.13732 (2021) - 2020
- [c3]Alexander Brauckmann, Andrés Goens, Sebastian Ertel, Jerónimo Castrillón:
Compiler-based graph representations for deep learning models of code. CC 2020: 201-211 - [c2]Alexander Brauckmann, Andrés Goens, Jerónimo Castrillón:
ComPy-Learn: A toolbox for exploring machine learning representations for compilers. FDL 2020: 1-4
2010 – 2019
- 2019
- [c1]Andrés Goens, Alexander Brauckmann, Sebastian Ertel, Chris Cummins, Hugh Leather, Jerónimo Castrillón:
A case study on machine learning for synthesizing benchmarks. MAPL@PLDI 2019: 38-46
Coauthor Index
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