Alexander Brauckmann

Orcid: 0000-0001-5774-3970

According to our database1, Alexander Brauckmann authored at least 14 papers between 2019 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
Tensor Program Superoptimization through Cost-Guided Symbolic Program Synthesis.
Proceedings of the IEEE/ACM International Symposium on Code Generation and Optimization, 2026

Accelerating Sparse Algebra with Program Synthesis.
Proceedings of the 35th ACM SIGPLAN International Conference on Compiler Construction, 2026

2025
Guided Tensor Lifting.
Proc. ACM Program. Lang., 2025

Tensorize: Fast Synthesis of Tensor Programs from Legacy Code using Symbolic Tracing, Sketching and Solving.
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.
Proceedings of the 34th ACM SIGPLAN International Conference on Compiler Construction, 2025

Guess, Measure & Edit: Using Lowering to Lift Tensor Code.
Proceedings of the 34th International Conference on Parallel Architectures and Compilation Techniques, 2025

2023
Rewriting History: Repurposing Domain-Specific CGRAs.
CoRR, 2023

mlirSynth: Automatic, Retargetable Program Raising in Multi-Level IR Using Program Synthesis.
Proceedings of the 32nd International Conference on Parallel Architectures and Compilation Techniques, 2023

2022
ExeBench: an ML-scale dataset of executable C functions.
Proceedings of the MAPS@PLDI 2022: 6th ACM SIGPLAN International Symposium on Machine Programming, 2022

2021
A Reinforcement Learning Environment for Polyhedral Optimizations.
CoRR, 2021

PolyGym: Polyhedral Optimizations as an Environment for Reinforcement Learning.
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.
Proceedings of the Forum for Specification and Design Languages, 2020

Compiler-based graph representations for deep learning models of code.
Proceedings of the CC '20: 29th International Conference on Compiler Construction, 2020

2019
A case study on machine learning for synthesizing benchmarks.
Proceedings of the 3rd ACM SIGPLAN International Workshop on Machine Learning and Programming Languages, 2019


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