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A Survey on Compiler Autotuning using Machine Learning

A Survey on Compiler Autotuning using Machine Learning

13 January 2018
Amir H. Ashouri
W. Killian
John Cavazos
G. Palermo
Cristina Silvano
ArXivPDFHTML

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

12 / 12 papers shown
Title
On-line Policy Improvement using Monte-Carlo Search
On-line Policy Improvement using Monte-Carlo Search
Gerald Tesauro
Gregory R. Galperin
122
270
0
09 Jan 2025
FastCHGNet: Training one Universal Interatomic Potential to 1.5 Hours with 32 GPUs
FastCHGNet: Training one Universal Interatomic Potential to 1.5 Hours with 32 GPUs
Yuanchang Zhou
Siyu Hu
Chen Wang
Lin-Wang Wang
Guangming Tan
Weile Jia
AI4CE
GNN
98
0
0
30 Dec 2024
Gap-Dependent Bounds for Q-Learning using Reference-Advantage Decomposition
Gap-Dependent Bounds for Q-Learning using Reference-Advantage Decomposition
Zhong Zheng
Haochen Zhang
Lingzhou Xue
OffRL
111
2
0
10 Oct 2024
CATBench: A Compiler Autotuning Benchmarking Suite for Black-box Optimization
CATBench: A Compiler Autotuning Benchmarking Suite for Black-box Optimization
Jacob O. Tørring
Carl Hvarfner
Luigi Nardi
Magnus Sjalander
80
1
0
24 Jun 2024
A Collective Knowledge workflow for collaborative research into
  multi-objective autotuning and machine learning techniques
A Collective Knowledge workflow for collaborative research into multi-objective autotuning and machine learning techniques
G. Fursin
Anton Lokhmotov
Dmitry Savenko
E. Upton
18
14
0
19 Jan 2018
Introducing ReQuEST: an Open Platform for Reproducible and
  Quality-Efficient Systems-ML Tournaments
Introducing ReQuEST: an Open Platform for Reproducible and Quality-Efficient Systems-ML Tournaments
T. Moreau
Anton Lokhmotov
G. Fursin
31
8
0
19 Jan 2018
Automatically Tuning the GCC Compiler to Optimize the Performance of
  Applications Running on Embedded Systems
Automatically Tuning the GCC Compiler to Optimize the Performance of Applications Running on Embedded Systems
Craig Blackmore
O. Ray
Kerstin Eder
15
6
0
23 Feb 2017
Autotuning OpenCL Workgroup Size for Stencil Patterns
Autotuning OpenCL Workgroup Size for Stencil Patterns
Chris Cummins
Pavlos Petoumenos
Michel Steuwer
Hugh Leather
27
27
0
08 Nov 2015
Collective Mind, Part II: Towards Performance- and Cost-Aware Software
  Engineering as a Natural Science
Collective Mind, Part II: Towards Performance- and Cost-Aware Software Engineering as a Natural Science
G. Fursin
Abdul Wahid Memon
C. Guillon
Anton Lokhmotov
26
14
0
20 Jun 2015
Machine Learning Based Auto-tuning for Enhanced OpenCL Performance
  Portability
Machine Learning Based Auto-tuning for Enhanced OpenCL Performance Portability
Thomas L. Falch
A. Elster
38
55
0
02 Jun 2015
Deep Learning in Neural Networks: An Overview
Deep Learning in Neural Networks: An Overview
Jürgen Schmidhuber
HAI
232
16,336
0
30 Apr 2014
Market-Oriented Cloud Computing: Vision, Hype, and Reality for
  Delivering IT Services as Computing Utilities
Market-Oriented Cloud Computing: Vision, Hype, and Reality for Delivering IT Services as Computing Utilities
Rajkumar Buyya
Chee Shin Yeo
S. Venugopal
VLM
69
1,856
0
26 Aug 2008
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