Emergency Evacuation using Wireless Sensor Networks. - Matthew Barnes; Hugh Leather; D. K. Arvind 001 (LCN, 2007)

Automatic Feature Generation for Machine Learning Based Optimizing Compilation. - Hugh Leather; Edwin V. Bonilla; Michael F. P. O'Boyle (CGO, 2009)

Raced profiles: efficient selection of competing compiler optimizations. - Hugh Leather; Michael F. P. O'Boyle; Bruce Worton (LCTES, 2009)

Machine learning in compilers. - Hugh Leather (2011)

MaSiF: machine learning guided auto-tuning of parallel skeletons. - Alexander Collins; Christian Fensch; Hugh Leather (PACT, 2012)

Efficiently parallelizing instruction set simulation of embedded multi-core processors using region-based just-in-time dynamic binary translation. - Stephen C. Kyle; Igor Böhm; Björn Franke; Hugh Leather; Nigel P. Topham (LCTES, 2012)

Auto-Tuning Parallel Skeletons. - Alexander Collins; Christian Fensch; Hugh Leather (Parallel Process. Lett., 2012)

MaSiF: Machine learning guided auto-tuning of parallel skeletons. - Alexander Collins; Christian Fensch; Hugh Leather; Murray Cole (HiPC, 2013)

Active learning accelerated automatic heuristic construction for parallel program mapping. - William F. Ogilvie; Pavlos Petoumenos; Zheng Wang 001; Hugh Leather (PACT, 2014)

Measuring QoE of interactive workloads and characterising frequency governors on mobile devices. - Volker Seeker; Pavlos Petoumenos; Hugh Leather; Björn Franke (IISWC, 2014)

Fast Automatic Heuristic Construction Using Active Learning. - William F. Ogilvie; Pavlos Petoumenos; Zheng Wang 001; Hugh Leather (LCPC, 2014)

Automatic feature generation for machine learning-based optimising compilation. - Hugh Leather; Edwin V. Bonilla; Michael F. P. O'Boyle (ACM Trans. Archit. Code Optim., 2014)

Power Capping: What Works, What Does Not. - Pavlos Petoumenos; Lev Mukhanov; Zheng Wang 001; Hugh Leather; Dimitrios S. Nikolopoulos (ICPADS, 2015)

Application of Domain-aware Binary Fuzzing to Aid Android Virtual Machine Testing. - Stephen C. Kyle; Hugh Leather; Björn Franke; Dave Butcher; Stuart Monteith (VEE, 2015)

Autotuning OpenCL Workgroup Size for Stencil Patterns. - Chris Cummins; Pavlos Petoumenos; Michel Steuwer; Hugh Leather (CoRR, 2015)

Iterative compilation on mobile devices. - Paschalis Mpeis; Pavlos Petoumenos; Hugh Leather (CoRR, 2015)

The Lambda Calculus: Practice and Principle. - Hugh Leather; Janne Irgens (A List of Successes That Can Change the World, 2016)

On the Inference of User Paths from Anonymized Mobility Data. - Galini Tsoukaneri; George Theodorakopoulos 001; Hugh Leather; Mahesh K. Marina (EuroS&P, 2016)

Predicting and Optimizing Image Compression. - Oleksandr Murashko; John Thomson; Hugh Leather (ACM Multimedia, 2016)

End-to-End Deep Learning of Optimization Heuristics. - Chris Cummins; Pavlos Petoumenos; Zheng Wang 001; Hugh Leather (PACT, 2017)

Synthesizing benchmarks for predictive modeling. - Chris Cummins; Pavlos Petoumenos; Zheng Wang 001; Hugh Leather (CGO, 2017)

Minimizing the cost of iterative compilation with active learning. - William F. Ogilvie; Pavlos Petoumenos; Zheng Wang 001; Hugh Leather (CGO, 2017)

ALEA: A Fine-Grained Energy Profiling Tool. - Lev Mukhanov; Pavlos Petoumenos; Zheng Wang 001; Konstantinos Parasyris; Dimitrios S. Nikolopoulos; Bronis R. de Supinski; Hugh Leather (ACM Trans. Archit. Code Optim., 2017)

Right-Sizing Server Capacity Headroom for Global Online Services. - Chad Verbowski; Ed Thayer; Paolo Costa; Hugh Leather; Björn Franke (ICDCS, 2018)

Compiler fuzzing through deep learning. - Chris Cummins; Pavlos Petoumenos; Alastair Murray; Hugh Leather (ISSTA, 2018)

POSTER: A Collaborative Multi-Factor Scheduler for Asymmetric Multicore Processors. - Teng Yu; Pavlos Petoumenos; Vladimir Janjic; Mingcan Zhu; Hugh Leather; John Thomson (PACT, 2019)

Function Merging by Sequence Alignment. - Rodrigo C. O. Rocha; Pavlos Petoumenos; Zheng Wang 001; Murray Cole; Hugh Leather (CGO, 2019)

A case study on machine learning for synthesizing benchmarks. - Andrés Goens; Alexander Brauckmann; Sebastian Ertel; Chris Cummins; Hugh Leather; Jerónimo Castrillón (MAPL@PLDI, 2019)

Vectorization-aware loop unrolling with seed forwarding. - Rodrigo C. O. Rocha; Vasileios Porpodas; Pavlos Petoumenos; Luís F. W. Góes; Zheng Wang 001; Murray Cole; Hugh Leather (CC, 2020)

COLAB: a collaborative multi-factor scheduler for asymmetric multicore processors. - Teng Yu; Pavlos Petoumenos; Vladimir Janjic; Hugh Leather; John Thomson (CGO, 2020)

Machine Learning in Compilers: Past, Present and Future. - Hugh Leather; Chris Cummins (FDL, 2020)

Effective function merging in the SSA form. - Rodrigo C. O. Rocha; Pavlos Petoumenos; Zheng Wang 001; Murray Cole; Hugh Leather (PLDI, 2020)

ProGraML: Graph-based Deep Learning for Program Optimization and Analysis. - Chris Cummins; Zacharias V. Fisches; Tal Ben-Nun; Torsten Hoefler; Hugh Leather (CoRR, 2020)

Value Function Based Performance Optimization of Deep Learning Workloads. - Benoit Steiner; Chris Cummins; Horace He; Hugh Leather (CoRR, 2020)

Deep Data Flow Analysis. - Chris Cummins; Hugh Leather; Zacharias V. Fisches; Tal Ben-Nun; Torsten Hoefler; Michael F. P. O'Boyle (CoRR, 2020)

ProGraML: A Graph-based Program Representation for Data Flow Analysis and Compiler Optimizations. - Chris Cummins; Zacharias V. Fisches; Tal Ben-Nun; Torsten Hoefler; Michael F. P. O'Boyle; Hugh Leather (ICML, 2021)

HyFM: function merging for free. - Rodrigo C. O. Rocha; Pavlos Petoumenos; Zheng Wang 001; Murray Cole; Kim M. Hazelwood; Hugh Leather (LCTES, 2021)

Value Learning for Throughput Optimization of Deep Learning Workloads. - Benoit Steiner; Chris Cummins; Horace He; Hugh Leather (MLSys, 2021)

Developer and user-transparent compiler optimization for interactive applications. - Paschalis Mpeis; Pavlos Petoumenos; Kim M. Hazelwood; Hugh Leather (PLDI, 2021)

Using Graph Neural Networks to model the performance of Deep Neural Networks. - Shikhar Singh; Benoit Steiner; James Hegarty; Hugh Leather (CoRR, 2021)

Collaborative Heterogeneity-Aware OS Scheduler for Asymmetric Multicore Processors. - Teng Yu; Runxin Zhong; Vladimir Janjic; Pavlos Petoumenos; Jidong Zhai; Hugh Leather; John Thomson (IEEE Trans. Parallel Distributed Syst., 2021)

Q-gym: An Equality Saturation Framework for DNN Inference Exploiting Weight Repetition. - Cheng Fu 002; Hanxian Huang; Bram Wasti; Chris Cummins; Riyadh Baghdadi; Kim M. Hazelwood; Yuandong Tian; Jishen Zhao; Hugh Leather (PACT, 2022)

BenchPress: A Deep Active Benchmark Generator. - Foivos Tsimpourlas; Pavlos Petoumenos; Min Xu; Chris Cummins; Kim M. Hazelwood; Ajitha Rajan; Hugh Leather (PACT, 2022)

Caviar: an e-graph based TRS for automatic code optimization. - Smail Kourta; Adel Abderahmane Namani; Fatima Benbouzid-Si Tayeb; Kim M. Hazelwood; Chris Cummins; Hugh Leather; Riyadh Baghdadi (CC, 2022)

Automating reinforcement learning architecture design for code optimization. - Huanting Wang; Zhanyong Tang; Cheng Zhang 007; Jiaqi Zhao; Chris Cummins; Hugh Leather; Zheng Wang 001 (CC, 2022)

CompilerGym: Robust, Performant Compiler Optimization Environments for AI Research. - Chris Cummins; Bram Wasti; Jiadong Guo; Brandon Cui; Jason Ansel; Sahir Gomez; Somya Jain; Jia Liu; Olivier Teytaud; Benoit Steiner; Yuandong Tian; Hugh Leather (CGO, 2022)

F3M: Fast Focused Function Merging. - Sean Stirling; Rodrigo C. O. Rocha; Kim M. Hazelwood; Hugh Leather; Michael F. P. O'Boyle; Pavlos Petoumenos (CGO, 2022)

A graph neural network-based performance model for deep learning applications. - Shikhar Singh; James Hegarty; Hugh Leather; Benoit Steiner (MAPS@PLDI, 2022)

LoopStack: a Lightweight Tensor Algebra Compiler Stack. - Bram Wasti; José Pablo Cambronero; Benoit Steiner; Hugh Leather; Aleksandar Zlateski (CoRR, 2022)

Progress Report: A Deep Learning Guided Exploration of Affine Unimodular Loop Transformations. - Massinissa Merouani; Khaled Afif Boudaoud; Iheb Nassim Aouadj; Nassim Tchoulak; Fatima Benbouzid-Sitayeb; Karima Benatchba; Hugh Leather; Riyadh Baghdadi (CoRR, 2022)

Contrastive Distillation Is a Sample-Efficient Self-Supervised Loss Policy for Transfer Learning. - Chris Lengerich; Gabriel Synnaeve; Amy Zhang 001; Hugh Leather; Kurt Shuster 001; François Charton; Charysse Redwood (CoRR, 2022)

Object Intersection Captures on Interactive Apps to Drive a Crowd-sourced Replay-based Compiler Optimization. - Paschalis Mpeis; Pavlos Petoumenos; Kim M. Hazelwood; Hugh Leather (ACM Trans. Archit. Code Optim., 2022)

Code Translation with Compiler Representations. - Marc Szafraniec; Baptiste Rozière; Hugh Leather; Patrick Labatut; François Charton; Gabriel Synnaeve (ICLR, 2023)

Learning Compiler Pass Orders using Coreset and Normalized Value Prediction. - Youwei Liang; Kevin Stone; Ali Shameli; Chris Cummins; Mostafa Elhoushi; Jiadong Guo; Benoit Steiner; Xiaomeng Yang; Pengtao Xie; Hugh James Leather; Yuandong Tian (ICML, 2023)

CoLLAT: On Adding Fine-grained Audio Understanding to Language Models using Token-Level Locked-Language Tuning. - Dadallage A. R. Silva; Spencer Whitehead; Christopher T. Lengerich; Hugh Leather (NeurIPS, 2023)

BenchDirect: A Directed Language Model for Compiler Benchmarks. - Foivos Tsimpourlas; Pavlos Petoumenos; Min Xu; Chris Cummins; Kim M. Hazelwood; Ajitha Rajan; Hugh Leather (CoRR, 2023)

Large Language Models for Compiler Optimization. - Chris Cummins; Volker Seeker; Dejan Grubisic; Mostafa Elhoushi; Youwei Liang; Baptiste Rozière; Jonas Gehring; Fabian Gloeckle; Kim M. Hazelwood; Gabriel Synnaeve; Hugh Leather (CoRR, 2023)

Revealing Compiler Heuristics Through Automated Discovery and Optimization. - Volker Seeker; Chris Cummins; Murray Cole; Björn Franke; Kim M. Hazelwood; Hugh Leather (CGO, 2024)

Sieve: Multimodal Dataset Pruning Using Image Captioning Models. - Anas Mahmoud 002; Mostafa Elhoushi; Amro Abbas; Yu Yang; Newsha Ardalani; Hugh Leather; Ari S. Morcos (CVPR, 2024)

Priority Sampling of Large Language Models for Compilers. - Dejan Grubisic; Volker Seeker; Gabriel Synnaeve; Hugh Leather; John M. Mellor-Crummey; Chris Cummins (EuroMLSys@EuroSys, 2024)

CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution. - Alex Gu; Baptiste Rozière; Hugh James Leather; Armando Solar-Lezama; Gabriel Synnaeve; Sida Wang 001 (ICML, 2024)

Priority Sampling of Large Language Models for Compilers. - Dejan Grubisic; Chris Cummins; Volker Seeker; Hugh Leather (CoRR, 2024)

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers. - Massinissa Merouani; Khaled Afif Boudaoud; Iheb Nassim Aouadj; Nassim Tchoulak; Islem Kara Bernou; Hamza Benyamina; Fatima Benbouzid-Si Tayeb; Karima Benatchba; Hugh Leather; Riyadh Baghdadi (CoRR, 2024)

Compiler generated feedback for Large Language Models. - Dejan Grubisic; Chris Cummins; Volker Seeker; Hugh Leather (CoRR, 2024)

Meta Large Language Model Compiler: Foundation Models of Compiler Optimization. - Chris Cummins; Volker Seeker; Dejan Grubisic; Baptiste Rozière; Jonas Gehring; Gabriel Synnaeve; Hugh Leather (CoRR, 2024)

Don't Transform the Code, Code the Transforms: Towards Precise Code Rewriting using LLMs. - Chris Cummins; Volker Seeker; Jordi Armengol-Estapé; Aram H. Markosyan; Gabriel Synnaeve; Hugh Leather (CoRR, 2024)

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 (CC, 2025)

LLM Compiler: Foundation Language Models for Compiler Optimization. - Chris Cummins; Volker Seeker; Dejan Grubisic; Baptiste Rozière; Jonas Gehring; Gabriel Synnaeve; Hugh Leather (CC, 2025)

What I cannot execute, I do not understand: Training and Evaluating LLMs on Program Execution Traces. - Jordi Armengol-Estapé; Quentin Carbonneaux; Tianjun Zhang; Aram H. Markosyan; Volker Seeker; Chris Cummins; Melanie Kambadur; Michael F. P. O'Boyle; Sida I. Wang; Gabriel Synnaeve; Hugh James Leather (CoRR, 2025)