NeuroVectorizer: End-to-End Vectorization with Deep Reinforcement Learning

20 September 2019

Papers citing "NeuroVectorizer: End-to-End Vectorization with Deep Reinforcement Learning"

40 / 40 papers shown

Title
VecTrans: LLM Transformation Framework for Better Auto-vectorization on High-performance CPU Zhongchun Zheng Long Cheng Lu Li Rodrigo C. O. Rocha Tianyi Liu Wei Wei X. Zhang Yaoqing Gao 34 0 0 25 Mar 2025
Enhancing Deployment-Time Predictive Model Robustness for Code Analysis and Optimization Huanting Wang Patrick Lenihan Zheng Wang 35 0 0 03 Jan 2025
Scheduling Languages: A Past, Present, and Future Taxonomy Mary Hall Cosmin Oancea Anne C. Elster Ari Rasch Sameeran Joshi Amir Mohammad Tavakkoli Richard Schulze 26 1 0 25 Oct 2024
Improving Parallel Program Performance with LLM Optimizers via Agent-System Interface Anjiang Wei Allen Nie Thiago S. F. X. Teixeira Rohan Yadav Wonchan Lee Ke Wang Alex Aiken 21 0 0 21 Oct 2024
A Study of Performance Programming of CPU, GPU accelerated Computers and SIMD Architecture Xinyao Yi 19 1 0 16 Sep 2024
FTuner: A Fast Dynamic Shape Tensors Program Auto-Tuner for Deep Learning Compilers Pengyu Mu Linquan Wei Yi Liu Rui Wang 20 0 0 31 Jul 2024
MIREncoder: Multi-modal IR-based Pretrained Embeddings for Performance Optimizations Akash Dutta Ali Jannesari 30 0 0 02 Jul 2024
LLM-Vectorizer: LLM-based Verified Loop Vectorizer Jubi Taneja Avery Laird Cong Yan Madan Musuvathi Shuvendu K. Lahiri 18 4 0 07 Jun 2024
Compiler generated feedback for Large Language Models Dejan Grubisic Chris Cummins Volker Seeker Hugh Leather 24 5 0 18 Mar 2024
The Next 700 ML-Enabled Compiler Optimizations S. VenkataKeerthy Siddharth Jain Umesh Kalvakuntla Pranav Sai Gorantla R. Chitale E. Brevdo Albert Cohen Mircea Trofin Ramakrishna Upadrasta 11 3 0 17 Nov 2023
YFlows: Systematic Dataflow Exploration and Code Generation for Efficient Neural Network Inference using SIMD Architectures on CPUs Cyrus Zhou Zack Hassman Ruize Xu Dhirpal Shah Vaughn Richard Yanjing Li 29 1 0 01 Oct 2023
Large Language Models for Compiler Optimization Chris Cummins Volker Seeker Dejan Grubisic Mostafa Elhoushi Youwei Liang ... Jonas Gehring Fabian Gloeckle Kim M. Hazelwood Gabriel Synnaeve Hugh Leather 18 47 0 11 Sep 2023
LoopTune: Optimizing Tensor Computations with Reinforcement Learning Dejan Grubisic Bram Wasti Chris Cummins John Mellor-Crummey A. Zlateski 14 0 0 04 Sep 2023
Target-independent XLA optimization using Reinforcement Learning Milan Ganai Haichen Li Theodore Enns Yida Wang Randy Huang 32 0 0 28 Aug 2023
ACC Saturator: Automatic Kernel Optimization for Directive-Based GPU Code Kazuaki Matsumura Simon Garcia De Gonzalo Antonio J. Peña 6 1 0 22 Jun 2023
Performance Optimization using Multimodal Modeling and Heterogeneous GNN Akashnil Dutta J. Alcaraz Ali TehraniJamsaz E. César A. Sikora Ali Jannesari 15 10 0 25 Apr 2023
NPS: A Framework for Accurate Program Sampling Using Graph Neural Network Yuanwei Fang Zihao Liu YanHeng Lu Jiawei Liu Jiajie Li Yingqi Jin Jing Chen Yen-kuang Chen Hongzhong Zheng Yuan Xie MLAU 17 2 0 18 Apr 2023
Power Constrained Autotuning using Graph Neural Networks Akashnil Dutta JeeWhan Choi Ali Jannesari 30 5 0 22 Feb 2023
ML-driven Hardware Cost Model for MLIR Dibyendu Das Sandya Mannarswamy 25 0 0 14 Feb 2023
Learning Compiler Pass Orders using Coreset and Normalized Value Prediction Youwei Liang Kevin R. Stone A. Shameli Chris Cummins Mostafa Elhoushi ... Benoit Steiner Xiaomeng Yang P. Xie Hugh Leather Yuandong Tian 9 9 0 09 Jan 2023
Compiler Optimization for Quantum Computing Using Reinforcement Learning Nils Quetschlich Lukas Burgholzer Robert Wille 16 25 0 08 Dec 2022
POSET-RL: Phase ordering for Optimizing Size and Execution Time using Reinforcement Learning Shalini Jain Yashas Andaluri S. VenkataKeerthy Ramakrishna Upadrasta 11 6 0 27 Jul 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 23 13 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 13 2 0 25 Apr 2022
RL4ReAl: Reinforcement Learning for Register Allocation S. VenkataKeerthy Siddhartha Jain Anilava Kundu Rohit Aggarwal Albert Cohen Ramakrishna Upadrasta OffRL 20 5 0 05 Apr 2022
Learning to Combine Instructions in LLVM Compiler Sandya Mannarswamy Dibyendu Das 8 3 0 22 Feb 2022
Profile Guided Optimization without Profiles: A Machine Learning Approach Nadav Rotem Chris Cummins OffRL 15 7 0 24 Dec 2021
A Highly Configurable Hardware/Software Stack for DNN Inference Acceleration Suvadeep Banerjee Steve Burns P. Cocchini A. Davare Shweta Jain D. Kirkpatrick A. Sorokin Jin Yang Zhenkun Yang 10 9 0 29 Nov 2021
Generating GPU Compiler Heuristics using Reinforcement Learning Ian Colbert Jake Daly Norman Rubin 26 2 0 23 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 23 68 0 17 Sep 2021
Sonic: A Sampling-based Online Controller for Streaming Applications Yan Pei K. Pingali 29 0 0 15 Aug 2021
Customized Monte Carlo Tree Search for LLVM/Polly's Composable Loop Optimization Transformations Jaehoon Koo Prasanna Balaprakash Michael Kruse Xingfu Wu P. Hovland Mary W. Hall 15 7 0 10 May 2021
A Reinforcement Learning Environment for Polyhedral Optimizations Alexander Brauckmann Andrés Goens J. Castrillón 16 6 0 28 Apr 2021
MLGO: a Machine Learning Guided Compiler Optimizations Framework Mircea Trofin Yundi Qian E. Brevdo Zinan Lin K. Choromanski D. Li 36 62 0 13 Jan 2021
Deep Data Flow Analysis Chris Cummins Hugh Leather Zacharias V. Fisches Tal Ben-Nun Torsten Hoefler Michael F. P. O'Boyle 6 4 0 21 Nov 2020
Ansor: Generating High-Performance Tensor Programs for Deep Learning Lianmin Zheng Chengfan Jia Minmin Sun Zhao Wu Cody Hao Yu ... Jun Yang Danyang Zhuo Koushik Sen Joseph E. Gonzalez Ion Stoica 23 378 0 11 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 15 21 0 27 May 2020
ProGraML: Graph-based Deep Learning for Program Optimization and Analysis Chris Cummins Zacharias V. Fisches Tal Ben-Nun Torsten Hoefler Hugh Leather 85 56 0 23 Mar 2020
AutoPhase: Juggling HLS Phase Orderings in Random Forests with Deep Reinforcement Learning Qijing Huang Ameer Haj-Ali William S. Moses J. Xiang Ion Stoica Krste Asanović J. Wawrzynek 8 55 0 02 Mar 2020
Benanza: Automatic $μ$ Benchmark Generation to Compute "Lower-bound" Latency and Inform Optimizations of Deep Learning Models on GPUs Cheng-rong Li Abdul Dakkak Jinjun Xiong Wen-mei W. Hwu 11 10 0 16 Nov 2019