William S. Moses

Orcid: 0000-0003-2627-0642

Affiliations:
  • University of Illinois Urbana-Champaign (UIUC), IL, USA
  • MIT CSAIL, Cambridge, MA, USA (former)


According to our database1, William S. Moses authored at least 27 papers between 2016 and 2024.

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Bibliography

2024
The MLIR Transform Dialect. Your compiler is more powerful than you think.
CoRR, 2024

Input-Gen: Guided Generation of Stateful Inputs for Testing, Tuning, and Training.
CoRR, 2024

Retargeting and Respecializing GPU Workloads for Performance Portability.
Proceedings of the IEEE/ACM International Symposium on Code Generation and Optimization, 2024

2023
Supercharging Programming through Compiler Technology
PhD thesis, 2023

The Quantum Tortoise and the Classical Hare: A simple framework for understanding which problems quantum computing will accelerate (and which it will not).
CoRR, 2023

ComPile: A Large IR Dataset from Production Sources.
CoRR, 2023

Understanding Automatic Differentiation Pitfalls.
CoRR, 2023

High-Performance GPU-to-CPU Transpilation and Optimization via High-Level Parallel Constructs.
Proceedings of the 28th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming, 2023

Transparent Checkpointing for Automatic Differentiation of Program Loops Through Expression Transformations.
Proceedings of the Computational Science - ICCS 2023, 2023

2022
Performance Portable Solid Mechanics via Matrix-Free p-Multigrid.
CoRR, 2022

Scalable Automatic Differentiation of Multiple Parallel Paradigms through Compiler Augmentation.
Proceedings of the SC22: International Conference for High Performance Computing, 2022

Enabling Transformers to Understand Low-Level Programs.
Proceedings of the IEEE High Performance Extreme Computing Conference, 2022

2021
Reverse-mode automatic differentiation and optimization of GPU kernels via enzyme.
Proceedings of the International Conference for High Performance Computing, 2021

Polygeist: Raising C to Polyhedral MLIR.
Proceedings of the 30th International Conference on Parallel Architectures and Compilation Techniques, 2021

2020
The Next 700 Accelerated Layers: From Mathematical Expressions of Network Computation Graphs to Accelerated GPU Kernels, Automatically.
ACM Trans. Archit. Code Optim., 2020

ProTuner: Tuning Programs with Monte Carlo Tree Search.
CoRR, 2020

Instead of Rewriting Foreign Code for Machine Learning, Automatically Synthesize Fast Gradients.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

AutoPhase: Juggling HLS Phase Orderings in Random Forests with Deep Reinforcement Learning.
Proceedings of the Third Conference on Machine Learning and Systems, 2020

2019
Tapir: Embedding Recursive Fork-join Parallelism into LLVM's Intermediate Representation.
ACM Trans. Parallel Comput., 2019

Extracting Incentives from Black-Box Decisions.
CoRR, 2019

AutoPhase: Compiler Phase-Ordering for High Level Synthesis with Deep Reinforcement Learning.
CoRR, 2019

LiTM: A Lightweight Deterministic Software Transactional Memory System.
Proceedings of the 10th International Workshop on Programming Models and Applications for Multicores and Manycores, 2019

AutoPhase: Compiler Phase-Ordering for HLS with Deep Reinforcement Learning.
Proceedings of the 27th IEEE Annual International Symposium on Field-Programmable Custom Computing Machines, 2019

2018
Tensor Comprehensions: Framework-Agnostic High-Performance Machine Learning Abstractions.
CoRR, 2018

2017
OpenMPIR: Implementing OpenMP Tasks with Tapir.
Proceedings of the Fourth Workshop on the LLVM Compiler Infrastructure in HPC, 2017

Tapir: Embedding Fork-Join Parallelism into LLVM's Intermediate Representation.
Proceedings of the 22nd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2017

2016
Computational Complexity of Arranging Music.
CoRR, 2016


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