Hugh Leather

Orcid: 0000-0003-0664-4176

According to our database1, Hugh Leather authored at least 66 papers between 2007 and 2024.

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

Timeline

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Bibliography

2024
Don't Transform the Code, Code the Transforms: Towards Precise Code Rewriting using LLMs.
CoRR, 2024

Meta Large Language Model Compiler: Foundation Models of Compiler Optimization.
CoRR, 2024

Compiler generated feedback for Large Language Models.
CoRR, 2024

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers.
CoRR, 2024

Priority Sampling of Large Language Models for Compilers.
CoRR, 2024

CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Priority Sampling of Large Language Models for Compilers.
Proceedings of the 4th Workshop on Machine Learning and Systems, 2024

Sieve: Multimodal Dataset Pruning Using Image Captioning Models.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Revealing Compiler Heuristics Through Automated Discovery and Optimization.
Proceedings of the IEEE/ACM International Symposium on Code Generation and Optimization, 2024

2023
Large Language Models for Compiler Optimization.
CoRR, 2023

BenchDirect: A Directed Language Model for Compiler Benchmarks.
CoRR, 2023

CoLLAT: On Adding Fine-grained Audio Understanding to Language Models using Token-Level Locked-Language Tuning.
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.
Proceedings of the International Conference on Machine Learning, 2023

Code Translation with Compiler Representations.
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.
ACM Trans. Archit. Code Optim., 2022

Contrastive Distillation Is a Sample-Efficient Self-Supervised Loss Policy for Transfer Learning.
CoRR, 2022

Progress Report: A Deep Learning Guided Exploration of Affine Unimodular Loop Transformations.
CoRR, 2022

LoopStack: a Lightweight Tensor Algebra Compiler Stack.
CoRR, 2022

A graph neural network-based performance model for deep learning applications.
Proceedings of the MAPS@PLDI 2022: 6th ACM SIGPLAN International Symposium on Machine Programming, 2022

F3M: Fast Focused Function Merging.
Proceedings of the IEEE/ACM International Symposium on Code Generation and Optimization, 2022

CompilerGym: Robust, Performant Compiler Optimization Environments for AI Research.
Proceedings of the IEEE/ACM International Symposium on Code Generation and Optimization, 2022

Automating reinforcement learning architecture design for code optimization.
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.
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.
Proceedings of the International Conference on Parallel Architectures and Compilation Techniques, 2022

Q-gym: An Equality Saturation Framework for DNN Inference Exploiting Weight Repetition.
Proceedings of the International Conference on Parallel Architectures and Compilation Techniques, 2022

2021
Collaborative Heterogeneity-Aware OS Scheduler for Asymmetric Multicore Processors.
IEEE Trans. Parallel Distributed Syst., 2021

Using Graph Neural Networks to model the performance of Deep Neural Networks.
CoRR, 2021

Developer and user-transparent compiler optimization for interactive applications.
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.
Proceedings of the Fourth Conference on Machine Learning and Systems, 2021

HyFM: function merging for free.
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.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Deep Data Flow Analysis.
CoRR, 2020

Value Function Based Performance Optimization of Deep Learning Workloads.
CoRR, 2020

ProGraML: Graph-based Deep Learning for Program Optimization and Analysis.
CoRR, 2020

Effective function merging in the SSA form.
Proceedings of the 41st ACM SIGPLAN International Conference on Programming Language Design and Implementation, 2020

Machine Learning in Compilers: Past, Present and Future.
Proceedings of the Forum for Specification and Design Languages, 2020

COLAB: a collaborative multi-factor scheduler for asymmetric multicore processors.
Proceedings of the CGO '20: 18th ACM/IEEE International Symposium on Code Generation and Optimization, 2020

Vectorization-aware loop unrolling with seed forwarding.
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

Function Merging by Sequence Alignment.
Proceedings of the IEEE/ACM International Symposium on Code Generation and Optimization, 2019

POSTER: A Collaborative Multi-Factor Scheduler for Asymmetric Multicore Processors.
Proceedings of the 28th International Conference on Parallel Architectures and Compilation Techniques, 2019

2018
Compiler fuzzing through deep learning.
Proceedings of the 27th ACM SIGSOFT International Symposium on Software Testing and Analysis, 2018

Right-Sizing Server Capacity Headroom for Global Online Services.
Proceedings of the 38th IEEE International Conference on Distributed Computing Systems, 2018

2017
ALEA: A Fine-Grained Energy Profiling Tool.
ACM Trans. Archit. Code Optim., 2017

Minimizing the cost of iterative compilation with active learning.
Proceedings of the 2017 International Symposium on Code Generation and Optimization, 2017

Synthesizing benchmarks for predictive modeling.
Proceedings of the 2017 International Symposium on Code Generation and Optimization, 2017

End-to-End Deep Learning of Optimization Heuristics.
Proceedings of the 26th International Conference on Parallel Architectures and Compilation Techniques, 2017

2016
Predicting and Optimizing Image Compression.
Proceedings of the 2016 ACM Conference on Multimedia Conference, 2016

On the Inference of User Paths from Anonymized Mobility Data.
Proceedings of the IEEE European Symposium on Security and Privacy, 2016

The Lambda Calculus: Practice and Principle.
Proceedings of the A List of Successes That Can Change the World, 2016

2015
Iterative compilation on mobile devices.
CoRR, 2015

Autotuning OpenCL Workgroup Size for Stencil Patterns.
CoRR, 2015

Application of Domain-aware Binary Fuzzing to Aid Android Virtual Machine Testing.
Proceedings of the 11th ACM SIGPLAN/SIGOPS International Conference on Virtual Execution Environments, 2015

Power Capping: What Works, What Does Not.
Proceedings of the 21st IEEE International Conference on Parallel and Distributed Systems, 2015

2014
Automatic feature generation for machine learning-based optimising compilation.
ACM Trans. Archit. Code Optim., 2014

Fast Automatic Heuristic Construction Using Active Learning.
Proceedings of the Languages and Compilers for Parallel Computing, 2014

Measuring QoE of interactive workloads and characterising frequency governors on mobile devices.
Proceedings of the 2014 IEEE International Symposium on Workload Characterization, 2014

Active learning accelerated automatic heuristic construction for parallel program mapping.
Proceedings of the International Conference on Parallel Architectures and Compilation, 2014

2013
MaSiF: Machine learning guided auto-tuning of parallel skeletons.
Proceedings of the 20th Annual International Conference on High Performance Computing, 2013

2012
Auto-Tuning Parallel Skeletons.
Parallel Process. Lett., 2012

Efficiently parallelizing instruction set simulation of embedded multi-core processors using region-based just-in-time dynamic binary translation.
Proceedings of the SIGPLAN/SIGBED Conference on Languages, 2012

MaSiF: machine learning guided auto-tuning of parallel skeletons.
Proceedings of the International Conference on Parallel Architectures and Compilation Techniques, 2012

2011
Machine learning in compilers.
PhD thesis, 2011

2009
Raced profiles: efficient selection of competing compiler optimizations.
Proceedings of the 2009 ACM SIGPLAN/SIGBED conference on Languages, 2009

Automatic Feature Generation for Machine Learning Based Optimizing Compilation.
Proceedings of the CGO 2009, 2009

2007
Emergency Evacuation using Wireless Sensor Networks.
Proceedings of the 32nd Annual IEEE Conference on Local Computer Networks (LCN 2007), 2007


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