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A Survey on Compiler Autotuning using Machine Learning

13 January 2018

Papers citing "A Survey on Compiler Autotuning using Machine Learning"

50 / 56 papers shown

Title
A Deep Learning Model for Predicting Transformation Legality Avani Tiwari Yacine Hakimi Riyadh Baghdadi 64 0 0 08 Nov 2025
Behavioral Embeddings of Programs: A Quasi-Dynamic Approach for Optimization Prediction Haolin Pan Jinyuan Dong Hongbin Zhang Hongyu Lin Mingjie Xing Yanjun Wu 68 0 0 15 Oct 2025
Regression Language Models for Code Yash Akhauri Xingyou Song Arissa Wongpanich Bryan Lewandowski Mohamed S. Abdelfattah 132 1 0 30 Sep 2025
Tuning the Tuner: Introducing Hyperparameter Optimization for Auto-Tuning Floris-Jan Willemsen Rob van Nieuwpoort Ben van Werkhoven 157 1 0 30 Sep 2025
Compiler-R1: Towards Agentic Compiler Auto-tuning with Reinforcement Learning Haolin Pan Hongyu Lin Haoran Luo Yang Liu Kaichun Yao Libo Zhang Mingjie Xing Yanjun Wu OffRL LRM 105 4 0 30 May 2025
Investigating Execution-Aware Language Models for Code OptimizationIEEE International Conference on Program Comprehension (ICPC), 2025 Federico Di Menna Luca Traini Gabriele Bavota Vittorio Cortellessa 228 0 0 11 Mar 2025
$Breaking the $\log(1/\Delta_2)$ Barrier: Better Batched Best Arm Identification with Adaptive Grids$ Breaking the $\log(1/\Delta_2)$ Barrier: Better Batched Best Arm Identification with Adaptive Grids Tianyuan Jin Qin Zhang Dongruo Zhou 228 0 0 29 Jan 2025
On-line Policy Improvement using Monte-Carlo SearchNeural Information Processing Systems (NeurIPS), 1996 Gerald Tesauro Gregory R. Galperin 382 275 0 09 Jan 2025
FastCHGNet: Training one Universal Interatomic Potential to 1.5 Hours with 32 GPUsIEEE International Parallel and Distributed Processing Symposium (IPDPS), 2024 Yuanchang Zhou Siyu Hu Chen Wang Lin-Wang Wang Guangming Tan Weile Jia AI4CE GNN 344 2 0 30 Dec 2024
Scheduling Languages: A Past, Present, and Future Taxonomy Mary Hall Cosmin Oancea Anne C. Elster Ari Rasch Sameeran Joshi Amir Mohammad Tavakkoli Richard Schulze 166 1 0 25 Oct 2024
Gap-Dependent Bounds for Q-Learning using Reference-Advantage DecompositionInternational Conference on Learning Representations (ICLR), 2024 Zhong Zheng Haochen Zhang Lingzhou Xue OffRL 334 8 0 10 Oct 2024
Tadashi: Enabling AI-Based Automated Code Generation With Guaranteed Correctness Emil Vatai Aleksandr Drozd Ivan R. Ivanov João Eduardo Batista Yinghao Ren Mohamed Wahib 197 2 0 04 Oct 2024
CATBench: A Compiler Autotuning Benchmarking Suite for Black-box Optimization Jacob O. Tørring Carl Hvarfner Luigi Nardi Magnus Sjalander 295 2 0 24 Jun 2024
Supersonic: Learning to Generate Source Code Optimizations in C/C++IEEE Transactions on Software Engineering (TSE), 2023 Zimin Chen Sen Fang Monperrus Martin 315 25 0 26 Sep 2023
LoopTune: Optimizing Tensor Computations with Reinforcement Learning Dejan Grubisic Bram Wasti Chris Cummins John Mellor-Crummey A. Zlateski 197 2 0 04 Sep 2023
Target-independent XLA optimization using Reinforcement Learning Milan Ganai Haichen Li Theodore Enns Yida Wang Randy Huang 173 1 0 28 Aug 2023
SEER: Super-Optimization Explorer for HLS using E-graph Rewriting with MLIR Jianyi Cheng Samuel Coward Lorenzo Chelini ra M. Barbalho Theo Drane 48 6 0 15 Aug 2023
ytopt: Autotuning Scientific Applications for Energy Efficiency at Large ScalesConcurrency and Computation (CCPE), 2023 Xingfu Wu Dali Wang Michael Kruse Jaehoon Koo B. Videau P. Hovland V. Taylor B. Geltz Siddhartha Jana Mary W. Hall 151 24 0 28 Mar 2023
Kernel Launcher: C++ Library for Optimal-Performance Portable CUDA Applications Stijn Heldens Ben van Werkhoven 116 4 0 22 Mar 2023
Machine Learning-Driven Adaptive OpenMP For Portable Performance on Heterogeneous Systems Giorgis Georgakoudis K. Parasyris C. Liao D. Beckingsale T. Gamblin B. D. Supinski 98 1 0 15 Mar 2023
Power Constrained Autotuning using Graph Neural NetworksIEEE International Parallel and Distributed Processing Symposium (IPDPS), 2023 Akashnil Dutta JeeWhan Choi Ali Jannesari 144 6 0 22 Feb 2023
Compiler Optimization for Quantum Computing Using Reinforcement LearningDesign Automation Conference (DAC), 2022 Nils Quetschlich Lukas Burgholzer Robert Wille 138 33 0 08 Dec 2022
Going green: optimizing GPUs for energy efficiency through model-steered auto-tuningInternational Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS), 2022 R. Schoonhoven B. Veenboer Ben van Werkhoven K. Batenburg 130 18 0 14 Nov 2022
Benchmarking optimization algorithms for auto-tuning GPU kernelsIEEE Transactions on Evolutionary Computation (TEVC), 2022 R. Schoonhoven Ben van Werkhoven K. Batenburg 111 14 0 04 Oct 2022
Towards making the most of NLP-based device mapping optimization for OpenCL kernels Petros Vavaroutsos Ioannis Oroutzoglou Dimosthenis Masouros Dimitrios Soudris 74 0 0 30 Aug 2022
Finding Reusable Machine Learning Components to Build Programming Language Processing PipelinesEuropean Conference on Software Architecture (ECSA), 2022 Patrick Flynn T. Vanderbruggen C. Liao Pei-Hung Lin M. Emani Xipeng Shen 176 5 0 11 Aug 2022
MAGPIE: Machine Automated General Performance Improvement via Evolution of Software Aymeric Blot J. Petke 101 18 0 04 Aug 2022
MLGOPerf: An ML Guided Inliner to Optimize Performance Amir H. Ashouri Mostafa Elhoushi Yu-Wei Hua Xiang Wang Muhammad Asif Manzoor Bryan Chan Yaoqing Gao 171 15 0 18 Jul 2022
End-to-end Mapping in Heterogeneous Systems Using Graph Representation Learning Yao Xiao Guixiang Ma Nesreen Ahmed Mihai Capota Ted Willke Shahin Nazarian P. Bogdan 165 2 0 25 Apr 2022
Unlocking the Secrets of Software Configuration Landscapes-Ruggedness, Accessibility, Escapability, and Transferability Mingyu Huang Peili Mao Ke Li 142 1 0 05 Jan 2022
Profile Guided Optimization without Profiles: A Machine Learning Approach Nadav Rotem Chris Cummins OffRL 185 10 0 24 Dec 2021
Fine-Tuning Data Structures for Analytical Query Processing Amir Shaikhha Marios Kelepeshis Mahdi Ghorbani 92 1 0 24 Dec 2021
Generating GPU Compiler Heuristics using Reinforcement Learning Ian Colbert Jake Daly Norman Rubin 147 3 0 23 Nov 2021
Constraint-based Diversification of JOP Gadgets R. Tsoupidi Roberto Castañeda Lozano Benoit Baudry 123 4 0 18 Nov 2021
CompilerGym: Robust, Performant Compiler Optimization Environments for AI Research Chris Cummins Bram Wasti Jiadong Guo Brandon Cui Jason Ansel ... Jia-Wei Liu O. Teytaud Benoit Steiner Yuandong Tian Hugh Leather 212 98 0 17 Sep 2021
Using Graph Neural Networks to model the performance of Deep Neural Networks Shikhar Singh Benoit Steiner James Hegarty Hugh Leather GNN 103 4 0 27 Aug 2021
Autotuning PolyBench Benchmarks with LLVM Clang/Polly Loop Optimization Pragmas Using Bayesian Optimization (extended version)International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (SHPCS), 2020 Xingfu Wu Michael Kruse Dali Wang H. Finkel P. Hovland V. Taylor Mary W. Hall 141 38 0 27 Apr 2021
LS-CAT: A Large-Scale CUDA AutoTuning Dataset Lars Bjertnes Jacob O. Tørring A. Elster 124 6 0 26 Mar 2021
MLComp: A Methodology for Machine Learning-based Performance Estimation and Adaptive Selection of Pareto-Optimal Compiler Optimization SequencesDesign, Automation and Test in Europe (DATE), 2020 Alessio Colucci Dávid Juhász Martin Mosbeck Alberto Marchisio Semeen Rehman Manfred Kreutzer Guenther Nadbath A. Jantsch Mohamed Bennai 133 5 0 09 Dec 2020
Deep Data Flow Analysis Chris Cummins Hugh Leather Zacharias V. Fisches Tal Ben-Nun Torsten Hoefler Michael F. P. O'Boyle 117 6 0 21 Nov 2020
Autotuning Search Space for Loop Transformations Michael Kruse H. Finkel Xingfu Wu 93 9 0 13 Oct 2020
OneStopTuner: An End to End Architecture for JVM Tuning of Spark Applications Venktesh V Pooja B Bindal Devesh Singhal A. V. Subramanyam Vivek Kumar 57 3 0 07 Sep 2020
Static Neural Compiler Optimization via Deep Reinforcement Learning Rahim Mammadli Ali Jannesari F. Wolf 209 37 0 20 Aug 2020
MLOS: An Infrastructure for Automated Software Performance Engineering Carlo Curino Neha Godwal Brian Kroth S. Kuryata Greg Lapinski ... Olga Poppe Adam Śmiechowski Ed Thayer Markus Weimer Yiwen Zhu 120 17 0 01 Jun 2020
ProTuner: Tuning Programs with Monte Carlo Tree Search Ameer Haj-Ali Hasan Genç Qijing Huang William S. Moses J. Wawrzynek Krste Asanović Ion Stoica 154 27 0 27 May 2020
A Collaborative Filtering Approach for the Automatic Tuning of Compiler OptimisationsACM SIGPLAN Conference on Languages, Compilers, and Tools for Embedded Systems (LCTES), 2020 Stefano Cereda G. Palermo Paolo Cremonesi Stefano Doni 103 19 0 06 May 2020
ProGraML: Graph-based Deep Learning for Program Optimization and Analysis Chris Cummins Zacharias V. Fisches Tal Ben-Nun Torsten Hoefler Hugh Leather 297 67 0 23 Mar 2020
Benanza: Automatic $μ$ Benchmark Generation to Compute "Lower-bound" Latency and Inform Optimizations of Deep Learning Models on GPUsIEEE International Parallel and Distributed Processing Symposium (IPDPS), 2019 Cheng-rong Li Abdul Dakkak Jinjun Xiong Wen-mei W. Hwu 182 11 0 16 Nov 2019
NeuroVectorizer: End-to-End Vectorization with Deep Reinforcement LearningIEEE/ACM International Symposium on Code Generation and Optimization (CGO), 2019 Ameer Haj-Ali Nesreen Ahmed Theodore L. Willke Sophia Shao Krste Asanović Ion Stoica 218 110 0 20 Sep 2019
A View on Deep Reinforcement Learning in System Optimization Ameer Haj-Ali Nesreen Ahmed Theodore L. Willke Joseph E. Gonzalez Krste Asanović Ion Stoica OffRL 218 8 0 04 Aug 2019