Hugh Leather

According to our database, Hugh Leather authored at least 63 papers between 2007 and 2024.

Collaborative distances:

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

2024

Compiler generated feedback for Large Language Models.

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

Priority Sampling of Large Language Models for Compilers.

Dejan Grubisic, Chris Cummins, Volker Seeker, Hugh Leather

CoRR, 2024

CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution.

Alex Gu, Baptiste Rozière, Hugh Leather, Armando Solar-Lezama, Gabriel Synnaeve, Sida I. Wang

CoRR, 2024

Revealing Compiler Heuristics Through Automated Discovery and Optimization.

Volker Seeker, Chris Cummins, Murray Cole, Björn Franke, Kim M. Hazelwood, Hugh Leather

Proceedings of the IEEE/ACM International Symposium on Code Generation and Optimization, 2024

2023

SIEVE: Multimodal Dataset Pruning Using Image Captioning Models.

Anas Mahmoud, Mostafa Elhoushi, Amro Abbas, Yu Yang, Newsha Ardalani, Hugh Leather, Ari Morcos

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

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

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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 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

Proceedings of the International Conference on Machine Learning, 2023

Code Translation with Compiler Representations.

Marc Szafraniec, Baptiste Rozière, Hugh Leather, Patrick Labatut, François Charton, Gabriel Synnaeve

Proceedings of the Eleventh International Conference on Learning Representations, 2023

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

Contrastive Distillation Is a Sample-Efficient Self-Supervised Loss Policy for Transfer Learning.

Chris Lengerich, Gabriel Synnaeve, Amy Zhang, Hugh Leather, Kurt Shuster, François Charton, Charysse Redwood

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

LoopStack: a Lightweight Tensor Algebra Compiler Stack.

Bram Wasti, José Pablo Cambronero, Benoit Steiner, Hugh Leather, Aleksandar Zlateski

CoRR, 2022

A graph neural network-based performance model for deep learning applications.

Shikhar Singh, James Hegarty, Hugh Leather, Benoit Steiner

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

F3M: Fast Focused Function Merging.

Sean Stirling, Rodrigo C. O. Rocha, Kim M. Hazelwood, Hugh Leather, Michael F. P. O'Boyle, Pavlos Petoumenos

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

Proceedings of the IEEE/ACM International Symposium on Code Generation and Optimization, 2022

Automating reinforcement learning architecture design for code optimization.

Huanting Wang, Zhanyong Tang, Cheng Zhang, Jiaqi Zhao, Chris Cummins, Hugh Leather, Zheng Wang

Proceedings of the CC '22: 31st ACM SIGPLAN International Conference on Compiler Construction, Seoul, South Korea, April 2, 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

Proceedings of the CC '22: 31st ACM SIGPLAN International Conference on Compiler Construction, Seoul, South Korea, April 2, 2022

BenchPress: A Deep Active Benchmark Generator.

Foivos Tsimpourlas, Pavlos Petoumenos, Min Xu, Chris Cummins, Kim M. Hazelwood, Ajitha Rajan, Hugh Leather

Proceedings of the International Conference on Parallel Architectures and Compilation Techniques, 2022

Q-gym: An Equality Saturation Framework for DNN Inference Exploiting Weight Repetition.

Cheng Fu, Hanxian Huang, Bram Wasti, Chris Cummins, Riyadh Baghdadi, Kim M. Hazelwood, Yuandong Tian, Jishen Zhao, Hugh Leather

Proceedings of the International Conference on Parallel Architectures and Compilation Techniques, 2022

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

Using Graph Neural Networks to model the performance of Deep Neural Networks.

Shikhar Singh, Benoit Steiner, James Hegarty, Hugh Leather

CoRR, 2021

Developer and user-transparent compiler optimization for interactive applications.

Paschalis Mpeis, Pavlos Petoumenos, Kim M. Hazelwood, Hugh Leather

Proceedings of the PLDI '21: 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation, 2021

Value Learning for Throughput Optimization of Deep Learning Workloads.

Benoit Steiner, Chris Cummins, Horace He, Hugh Leather

Proceedings of Machine Learning and Systems 2021, 2021

HyFM: function merging for free.

Rodrigo C. O. Rocha, Pavlos Petoumenos, Zheng Wang, Murray Cole, Kim M. Hazelwood, Hugh Leather

Proceedings of the LCTES '21: 22nd ACM SIGPLAN/SIGBED International Conference on Languages, 2021

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

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Deep Data Flow Analysis.

Chris Cummins, Hugh Leather, Zacharias V. Fisches, Tal Ben-Nun, Torsten Hoefler, Michael F. P. O'Boyle

CoRR, 2020

Value Function Based Performance Optimization of Deep Learning Workloads.

Benoit Steiner, Chris Cummins, Horace He, Hugh Leather

CoRR, 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

Effective function merging in the SSA form.

Rodrigo C. O. Rocha, Pavlos Petoumenos, Zheng Wang, Murray Cole, Hugh Leather

Proceedings of the 41st ACM SIGPLAN International Conference on Programming Language Design and Implementation, 2020

Machine Learning in Compilers: Past, Present and Future.

Hugh Leather, Chris Cummins

Proceedings of the Forum for Specification and Design Languages, 2020

COLAB: a collaborative multi-factor scheduler for asymmetric multicore processors.

Teng Yu, Pavlos Petoumenos, Vladimir Janjic, Hugh Leather, John Thomson

Proceedings of the CGO '20: 18th ACM/IEEE International Symposium on Code Generation and Optimization, 2020

Vectorization-aware loop unrolling with seed forwarding.

Rodrigo C. O. Rocha, Vasileios Porpodas, Pavlos Petoumenos, Luís F. W. Góes, Zheng Wang, Murray Cole, Hugh Leather

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

Function Merging by Sequence Alignment.

Rodrigo C. O. Rocha, Pavlos Petoumenos, Zheng Wang, Murray Cole, Hugh Leather

Proceedings of the IEEE/ACM International Symposium on Code Generation and Optimization, 2019

POSTER: A Collaborative Multi-Factor Scheduler for Asymmetric Multicore Processors.

Teng Yu, Pavlos Petoumenos, Vladimir Janjic, Mingcan Zhu, Hugh Leather, John Thomson

Proceedings of the 28th International Conference on Parallel Architectures and Compilation Techniques, 2019

2018

Compiler fuzzing through deep learning.

Chris Cummins, Pavlos Petoumenos, Alastair Murray, Hugh Leather

Proceedings of the 27th ACM SIGSOFT International Symposium on Software Testing and Analysis, 2018

Right-Sizing Server Capacity Headroom for Global Online Services.

Chad Verbowski, Ed Thayer, Paolo Costa, Hugh Leather, Björn Franke

Proceedings of the 38th IEEE International Conference on Distributed Computing Systems, 2018

2017

ALEA: A Fine-Grained Energy Profiling Tool.

Lev Mukhanov, Pavlos Petoumenos, Zheng Wang, Konstantinos Parasyris, Dimitrios S. Nikolopoulos, Bronis R. de Supinski, Hugh Leather

ACM Trans. Archit. Code Optim., 2017

Minimizing the cost of iterative compilation with active learning.

William F. Ogilvie, Pavlos Petoumenos, Zheng Wang, Hugh Leather

Proceedings of the 2017 International Symposium on Code Generation and Optimization, 2017

Synthesizing benchmarks for predictive modeling.

Chris Cummins, Pavlos Petoumenos, Zheng Wang, Hugh Leather

Proceedings of the 2017 International Symposium on Code Generation and Optimization, 2017

End-to-End Deep Learning of Optimization Heuristics.

Chris Cummins, Pavlos Petoumenos, Zheng Wang, Hugh Leather

Proceedings of the 26th International Conference on Parallel Architectures and Compilation Techniques, 2017

2016

Predicting and Optimizing Image Compression.

Oleksandr Murashko, John Thomson, Hugh Leather

Proceedings of the 2016 ACM Conference on Multimedia Conference, 2016

On the Inference of User Paths from Anonymized Mobility Data.

Galini Tsoukaneri, George Theodorakopoulos, Hugh Leather, Mahesh K. Marina

Proceedings of the IEEE European Symposium on Security and Privacy, 2016

The Lambda Calculus: Practice and Principle.

Hugh Leather, Janne Irgens

Proceedings of the A List of Successes That Can Change the World, 2016

2015

Iterative compilation on mobile devices.

Paschalis Mpeis, Pavlos Petoumenos, Hugh Leather

CoRR, 2015

Autotuning OpenCL Workgroup Size for Stencil Patterns.

Chris Cummins, Pavlos Petoumenos, Michel Steuwer, Hugh Leather

CoRR, 2015

Application of Domain-aware Binary Fuzzing to Aid Android Virtual Machine Testing.

Stephen C. Kyle, Hugh Leather, Björn Franke, Dave Butcher, Stuart Monteith

Proceedings of the 11th ACM SIGPLAN/SIGOPS International Conference on Virtual Execution Environments, 2015

Power Capping: What Works, What Does Not.

Pavlos Petoumenos, Lev Mukhanov, Zheng Wang, Hugh Leather, Dimitrios S. Nikolopoulos

Proceedings of the 21st IEEE International Conference on Parallel and Distributed Systems, 2015

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

Fast Automatic Heuristic Construction Using Active Learning.

William F. Ogilvie, Pavlos Petoumenos, Zheng Wang, Hugh Leather

Proceedings of the Languages and Compilers for Parallel Computing, 2014

Measuring QoE of interactive workloads and characterising frequency governors on mobile devices.

Volker Seeker, Pavlos Petoumenos, Hugh Leather, Björn Franke

Proceedings of the 2014 IEEE International Symposium on Workload Characterization, 2014

Active learning accelerated automatic heuristic construction for parallel program mapping.

William F. Ogilvie, Pavlos Petoumenos, Zheng Wang, Hugh Leather

Proceedings of the International Conference on Parallel Architectures and Compilation, 2014

2013

MaSiF: Machine learning guided auto-tuning of parallel skeletons.

Alexander Collins, Christian Fensch, Hugh Leather, Murray Cole

Proceedings of the 20th Annual International Conference on High Performance Computing, 2013

2012

Auto-Tuning Parallel Skeletons.

Alexander Collins, Christian Fensch, Hugh Leather

Parallel Process. Lett., 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

Proceedings of the SIGPLAN/SIGBED Conference on Languages, 2012

MaSiF: machine learning guided auto-tuning of parallel skeletons.

Alexander Collins, Christian Fensch, Hugh Leather

Proceedings of the International Conference on Parallel Architectures and Compilation Techniques, 2012

2011

Machine learning in compilers.

Hugh Leather

PhD thesis, 2011

2009

Raced profiles: efficient selection of competing compiler optimizations.

Hugh Leather, Michael F. P. O'Boyle, Bruce Worton

Proceedings of the 2009 ACM SIGPLAN/SIGBED conference on Languages, 2009

Automatic Feature Generation for Machine Learning Based Optimizing Compilation.

Hugh Leather, Edwin V. Bonilla, Michael F. P. O'Boyle

Proceedings of the CGO 2009, 2009

2007

Emergency Evacuation using Wireless Sensor Networks.

Matthew Barnes, Hugh Leather, D. K. Arvind

Proceedings of the 32nd Annual IEEE Conference on Local Computer Networks (LCN 2007), 2007