Computational Complexity of Arranging Music. - William S. Moses; Erik D. Demaine (CoRR, 2016)

Tapir: Embedding Fork-Join Parallelism into LLVM's Intermediate Representation. - Tao B. Schardl; William S. Moses; Charles E. Leiserson (PPoPP, 2017)

OpenMPIR: Implementing OpenMP Tasks with Tapir. - George Stelle; William S. Moses; Stephen L. Olivier; Patrick S. McCormick (LLVM-HPC@SC, 2017)

Tensor Comprehensions: Framework-Agnostic High-Performance Machine Learning Abstractions. - Nicolas Vasilache; Oleksandr Zinenko; Theodoros Theodoridis; Priya Goyal; Zachary DeVito; William S. Moses; Sven Verdoolaege; Andrew Adams; Albert Cohen 001 (CoRR, 2018)

AutoPhase: Compiler Phase-Ordering for HLS with Deep Reinforcement Learning. - Qijing Huang 001; Ameer Haj-Ali; William S. Moses; John Xiang; Ion Stoica; Krste Asanovic; John Wawrzynek (FCCM, 2019)

LiTM: A Lightweight Deterministic Software Transactional Memory System. - Yu Xia 005; Xiangyao Yu; William S. Moses; Julian Shun; Srinivas Devadas (PMAM@PPoPP, 2019)

AutoPhase: Compiler Phase-Ordering for High Level Synthesis with Deep Reinforcement Learning. - Ameer Haj Ali; Qijing Huang 001; William S. Moses; John Xiang; Ion Stoica; Krste Asanovic; John Wawrzynek (CoRR, 2019)

Extracting Incentives from Black-Box Decisions. - Yonadav Shavit; William S. Moses (CoRR, 2019)

Tapir: Embedding Recursive Fork-join Parallelism into LLVM's Intermediate Representation. - Tao B. Schardl; William S. Moses; Charles E. Leiserson (ACM Trans. Parallel Comput., 2019)

AutoPhase: Juggling HLS Phase Orderings in Random Forests with Deep Reinforcement Learning. - Ameer Haj-Ali; Qijing (Jenny) Huang; William S. Moses; John Xiang; Krste Asanovic; John Wawrzynek; Ion Stoica (MLSys, 2020)

Instead of Rewriting Foreign Code for Machine Learning, Automatically Synthesize Fast Gradients. - William S. Moses; Valentin Churavy (NeurIPS, 2020)

ProTuner: Tuning Programs with Monte Carlo Tree Search. - Ameer Haj-Ali; Hasan Genc; Qijing Huang 001; William S. Moses; John Wawrzynek; Krste Asanovic; Ion Stoica (CoRR, 2020)

The Next 700 Accelerated Layers: From Mathematical Expressions of Network Computation Graphs to Accelerated GPU Kernels, Automatically. - Nicolas Vasilache; Oleksandr Zinenko; Theodoros Theodoridis; Priya Goyal; Zachary DeVito; William S. Moses; Sven Verdoolaege; Andrew Adams; Albert Cohen 001 (ACM Trans. Archit. Code Optim., 2020)

Polygeist: Raising C to Polyhedral MLIR. - William S. Moses; Lorenzo Chelini; Ruizhe Zhao; Oleksandr Zinenko (PACT, 2021)

Reverse-mode automatic differentiation and optimization of GPU kernels via enzyme. - William S. Moses; Valentin Churavy; Ludger Paehler; Jan Hückelheim; Sri Hari Krishna Narayanan; Michel Schanen; Johannes Doerfert (SC, 2021)

Enabling Transformers to Understand Low-Level Programs. - Zifan Carl Guo; William S. Moses (HPEC, 2022)

Scalable Automatic Differentiation of Multiple Parallel Paradigms through Compiler Augmentation. - William S. Moses; Sri Hari Krishna Narayanan; Ludger Paehler; Valentin Churavy; Michel Schanen; Jan Hückelheim; Johannes Doerfert; Paul D. Hovland (SC, 2022)

Performance Portable Solid Mechanics via Matrix-Free p-Multigrid. - Jed Brown; Valeria Barra; Natalie Beams; Leila Ghaffari; Matthew G. Knepley; William S. Moses; Rezgar Shakeri; Karen Stengel; Jeremy L. Thompson; Junchao Zhang (CoRR, 2022)

Transparent Checkpointing for Automatic Differentiation of Program Loops Through Expression Transformations. - Michel Schanen; Sri Hari Krishna Narayanan; Sarah Williamson; Valentin Churavy; William S. Moses; Ludger Paehler (ICCS (3), 2023)

High-Performance GPU-to-CPU Transpilation and Optimization via High-Level Parallel Constructs. - William S. Moses; Ivan R. Ivanov; Jens Domke; Toshio Endo; Johannes Doerfert; Oleksandr Zinenko (PPoPP, 2023)

Understanding Automatic Differentiation Pitfalls. - Jan Hückelheim; Harshitha Menon; William S. Moses; Bruce Christianson; Paul D. Hovland; Laurent Hascoët (CoRR, 2023)

ComPile: A Large IR Dataset from Production Sources. - Aiden Grossman; Ludger Paehler; Konstantinos Parasyris; Tal Ben-Nun; Jacob Hegna; William S. Moses; Jose Manuel Monsalve Diaz; Mircea Trofin; Johannes Doerfert (CoRR, 2023)

The Quantum Tortoise and the Classical Hare: A simple framework for understanding which problems quantum computing will accelerate (and which it will not). - Sukwoong Choi; William S. Moses; Neil C. Thompson (CoRR, 2023)

Supercharging Programming through Compiler Technology - William S. Moses (2023)

Retargeting and Respecializing GPU Workloads for Performance Portability. - Ivan R. Ivanov; Oleksandr Zinenko; Jens Domke; Toshio Endo; William S. Moses (CGO, 2024)

Input-Gen: Guided Generation of Stateful Inputs for Testing, Tuning, and Training. - Ivan R. Ivanov; Joachim Meyer 003; Aiden Grossman; William S. Moses; Johannes Doerfert (CoRR, 2024)

A taxonomy of automatic differentiation pitfalls. - Jan Hückelheim; Harshitha Menon; William S. Moses; Bruce Christianson; Paul D. Hovland; Laurent Hascoët (WIREs Data. Mining. Knowl. Discov., 2024)

The MLIR Transform Dialect: Your Compiler Is More Powerful Than You Think. - Martin Paul Lücke; Oleksandr Zinenko; William S. Moses; Michel Steuwer; Albert Cohen 001 (CGO, 2025)

The Quantum Tortoise and the Classical Hare: When Will Quantum Computers Outpace Classical Ones and When Will They Be Left Behind? - Sukwoong Choi; William S. Moses; Neil C. Thompson (Proc. IEEE, 2025)

RAPTOR: Practical Numerical Profiling of Scientific Applications. - Felix Hörold; Ivan R. Ivanov; Akash Dhruv; William S. Moses; Anshu Dubey; Mohamed Wahib; Jens Domke (CoRR, 2025)