Alexander Brauckmann

According to our database, Alexander Brauckmann authored at least 11 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Guided Tensor Lifting.

Yixuan Li, José Wesley de Souza Magalhães, Alexander Brauckmann, Michael F. P. O'Boyle, Elizabeth Polgreen

Proc. ACM Program. Lang., 2025

Tensorize: Fast Synthesis of Tensor Programs from Legacy Code using Symbolic Tracing, Sketching and Solving.

Alexander Brauckmann, Luc Jaulmes, José Wesley de Souza Magalhães, Elizabeth Polgreen, Michael F. P. O'Boyle

Proceedings of the 23rd ACM/IEEE International Symposium on Code Generation and Optimization, 2025

DFA-Net: A Compiler-Specific Neural Architecture for Robust Generalization in Data Flow Analyses.

Alexander Brauckmann, Anderson Faustino da Silva, Gabriel Synnaeve, Michael F. P. O'Boyle, Jerónimo Castrillón, Hugh Leather

Proceedings of the 34th ACM SIGPLAN International Conference on Compiler Construction, 2025

2023

Rewriting History: Repurposing Domain-Specific CGRAs.

Jackson Woodruff, Thomas Koehler, Alexander Brauckmann, Chris Cummins, Sam Ainsworth, Michael F. P. O'Boyle

CoRR, 2023

mlirSynth: Automatic, Retargetable Program Raising in Multi-Level IR Using Program Synthesis.

Alexander Brauckmann, Elizabeth Polgreen, Tobias Grosser, Michael F. P. O'Boyle

Proceedings of the 32nd International Conference on Parallel Architectures and Compilation Techniques, 2023

2022

ExeBench: an ML-scale dataset of executable C functions.

Jordi Armengol-Estapé, Jackson Woodruff, Alexander Brauckmann, José Wesley de Souza Magalhães, Michael F. P. O'Boyle

Proceedings of the MAPS@PLDI 2022: 6th ACM SIGPLAN International Symposium on Machine Programming, 2022

2021

A Reinforcement Learning Environment for Polyhedral Optimizations.

Alexander Brauckmann, Andrés Goens, Jerónimo Castrillón

CoRR, 2021

PolyGym: Polyhedral Optimizations as an Environment for Reinforcement Learning.

Alexander Brauckmann, Andrés Goens, Jerónimo Castrillón

Proceedings of the 30th International Conference on Parallel Architectures and Compilation Techniques, 2021

2020

ComPy-Learn: A toolbox for exploring machine learning representations for compilers.

Alexander Brauckmann, Andrés Goens, Jerónimo Castrillón

Proceedings of the Forum for Specification and Design Languages, 2020

Compiler-based graph representations for deep learning models of code.

Alexander Brauckmann, Andrés Goens, Sebastian Ertel, Jerónimo Castrillón

Proceedings of the CC '20: 29th International Conference on Compiler Construction, 2020

2019

A case study on machine learning for synthesizing benchmarks.

Andrés Goens, Alexander Brauckmann, Sebastian Ertel, Chris Cummins, Hugh Leather, Jerónimo Castrillón

Proceedings of the 3rd ACM SIGPLAN International Workshop on Machine Learning and Programming Languages, 2019