Grigori Fursin

According to our database, Grigori Fursin authored at least 56 papers between 2002 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

MLPerf Power: Benchmarking the Energy Efficiency of Machine Learning Systems from Microwatts to Megawatts for Sustainable AI.

Arya Tschand, Arun Tejusve Raghunath Rajan, Sachin Idgunji, Anirban Ghosh, Jeremy Holleman, Csaba Király, Pawan Ambalkar, Ritika Borkar, Ramesh Chukka, Trevor Cockrell, Oliver Curtis, Grigori Fursin, Miro Hodak, Hiwot Kassa, Anton Lokhmotov, Dejan Miskovic, Yuechao Pan, Manu Prasad Manmathan, Liz Raymond, Tom St. John, Arjun Suresh, Rowan Taubitz, Sean Zhan, Scott Wasson, David Kanter, Vijay Janapa Reddi

CoRR, 2024

Enabling more efficient and cost-effective AI/ML systems with Collective Mind, virtualized MLOps, MLPerf, Collective Knowledge Playground and reproducible optimization tournaments.

Grigori Fursin

CoRR, 2024

2023

Federated benchmarking of medical artificial intelligence with MedPerf.

Alexandros Karargyris, Renato Umeton, Micah J. Sheller, Alejandro Aristizabal, Johnu George, Anna Wuest, Sarthak Pati, Hasan Kassem, Maximilian Zenk, Ujjwal Baid, Prakash Narayana Moorthy, Alexander Chowdhury, Junyi Guo, Sahil S. Nalawade, Jacob Rosenthal, David Kanter, Maria Xenochristou, Daniel J. Beutel, Verena Chung, Timothy Bergquist, James A. Eddy, Abubakar Abid, Lewis Tunstall, Omar Sanseviero, Dimitrios Dimitriadis, Yiming Qian, Xinxing Xu, Yong Liu, Rick Siow Mong Goh, Srini Bala, Victor Bittorf, Sreekar Reddy Puchala, Biagio Ricciuti, Soujanya Samineni, Eshna Sengupta, Akshay Chaudhari, Cody Coleman, Bala Desinghu, Gregory F. Diamos, Debo Dutta, Diane Feddema, Grigori Fursin, Xinyuan Huang, Satyananda Kashyap, Nicholas D. Lane, Indranil Mallick, Pietro Mascagni, Virendra Mehta, Cassiano Ferro Moraes, Vivek Natarajan, Nikola Nikolov, Nicolas Padoy, Gennady Pekhimenko, Vijay Janapa Reddi, G. Anthony Reina, Pablo Ribalta, Abhishek Singh, Jayaraman J. Thiagarajan, Jacob Albrecht, Thomas Wolf, Geralyn Miller, Huazhu Fu, Prashant Shah, Daguang Xu, Poonam Yadav, David Talby, Mark M. Awad, Jeremy P. Howard, Michael Rosenthal, Luigi Marchionni, Massimo Loda, Jason M. Johnson, Spyridon Bakas, Peter Mattson

Nat. Mac. Intell., July, 2023

2021

On the Anatomy of Predictive Models for Accelerating GPU Convolution Kernels and Beyond.

Paolo Sylos Labini, Marco Cianfriglia, Damiano Perri, Osvaldo Gervasi, Grigori Fursin, Anton Lokhmotov, Cedric Nugteren, Bruno Carpentieri, Fabiana Zollo, Flavio Vella

ACM Trans. Archit. Code Optim., 2021

MedPerf: Open Benchmarking Platform for Medical Artificial Intelligence using Federated Evaluation.

Alexandros Karargyris, Renato Umeton, Micah J. Sheller, Alejandro Aristizabal, Johnu George, Srini Bala, Daniel J. Beutel, Victor Bittorf, Akshay Chaudhari, Alexander Chowdhury, Cody Coleman, Bala Desinghu, Gregory F. Diamos, Debo Dutta, Diane Feddema, Grigori Fursin, Junyi Guo, Xinyuan Huang, David Kanter, Satyananda Kashyap, Nicholas D. Lane, Indranil Mallick, Pietro Mascagni, Virendra Mehta, Vivek Natarajan, Nikola Nikolov, Nicolas Padoy, Gennady Pekhimenko, Vijay Janapa Reddi, G. Anthony Reina, Pablo Ribalta, Jacob Rosenthal, Abhishek Singh, Jayaraman J. Thiagarajan, Anna Wuest, Maria Xenochristou, Daguang Xu, Poonam Yadav, Michael Rosenthal, Massimo Loda, Jason M. Johnson, Peter Mattson

CoRR, 2021

Workflows Community Summit: Advancing the State-of-the-art of Scientific Workflows Management Systems Research and Development.

Rafael Ferreira da Silva, Henri Casanova, Kyle Chard, Tainã Coleman, Dan Laney, Dong H. Ahn, Shantenu Jha, Dorran Howell, Stian Soiland-Reyes, Ilkay Altintas, Douglas Thain, Rosa Filgueira, Yadu N. Babuji, Rosa M. Badia, Bartosz Balis, Silvina Caíno-Lores, Scott Callaghan, Frederik Coppens, Michael R. Crusoe, Kaushik De, Frank Di Natale, Tu Mai Anh Do, Bjoern Enders, Thomas Fahringer, Anne Fouilloux, Grigori Fursin, Alban Gaignard, Alex Ganose, Daniel Garijo, Sandra Gesing, Carole A. Goble, Adil Hasan, Sebastiaan Huber, Daniel S. Katz, Ulf Leser, Douglas Lowe, Bertram Ludäscher, Ketan Maheshwari, Maciej Malawski, Rajiv Mayani, Kshitij Mehta, André Merzky, Todd S. Munson, Jonathan Ozik, Loïc Pottier, Sashko Ristov, Mehdi Roozmeh, Renan Souza, Frédéric Suter, Benjamín Tovar, Matteo Turilli, Karan Vahi, Alvaro Vidal-Torreira, Wendy R. Whitcup, Michael Wilde, Alan R. Williams, Matthew Wolf, Justin M. Wozniak

CoRR, 2021

Workflows Community Summit: Bringing the Scientific Workflows Community Together.

Rafael Ferreira da Silva, Henri Casanova, Kyle Chard, Dan Laney, Dong H. Ahn, Shantenu Jha, Carole A. Goble, Lavanya Ramakrishnan, J. Luc Peterson, Bjoern Enders, Douglas Thain, Ilkay Altintas, Yadu N. Babuji, Rosa M. Badia, Vivien Bonazzi, Tainã Coleman, Michael R. Crusoe, Ewa Deelman, Frank Di Natale, Paolo Di Tommaso, Thomas Fahringer, Rosa Filgueira, Grigori Fursin, Alex Ganose, Björn A. Grüning, Daniel S. Katz, Olga A. Kuchar, Ana Kupresanin, Bertram Ludäscher, Ketan Maheshwari, Marta Mattoso, Kshitij Mehta, Todd S. Munson, Jonathan Ozik, Tom Peterka, Loic Pottier, Tim Randles, Stian Soiland-Reyes, Benjamín Tovar, Matteo Turilli, Thomas D. Uram, Karan Vahi, Michael Wilde, Matthew Wolf, Justin M. Wozniak

CoRR, 2021

A Community Roadmap for Scientific Workflows Research and Development.

Rafael Ferreira da Silva, Henri Casanova, Kyle Chard, Ilkay Altintas, Rosa M. Badia, Bartosz Balis, Tainã Coleman, Frederik Coppens, Frank Di Natale, Bjoern Enders, Thomas Fahringer, Rosa Filgueira, Grigori Fursin, Daniel Garijo, Carole A. Goble, Dorran Howell, Shantenu Jha, Daniel S. Katz, Daniel E. Laney, Ulf Leser, Maciej Malawski, Kshitij Mehta, Loïc Pottier, Jonathan Ozik, J. Luc Peterson, Lavanya Ramakrishnan, Stian Soiland-Reyes, Douglas Thain, Matthew Wolf

Proceedings of the 2021 IEEE Workshop on Workflows in Support of Large-Scale Science (WORKS), 2021

2020

Collective Knowledge: organizing research projects as a database of reusable components and portable workflows with common APIs.

Grigori Fursin

CoRR, 2020

The Collective Knowledge project: making ML models more portable and reproducible with open APIs, reusable best practices and MLOps.

Grigori Fursin

CoRR, 2020

CodeReef: an open platform for portable MLOps, reusable automation actions and reproducible benchmarking.

Grigori Fursin, Hervé Guillou, Nicolas Essayan

CoRR, 2020

2019

SysML: The New Frontier of Machine Learning Systems.

Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Eric S. Chung, Bill Dally, Jeff Dean, Inderjit S. Dhillon, Alexandros G. Dimakis, Pradeep Dubey, Charles Elkan, Grigori Fursin, Gregory R. Ganger, Lise Getoor, Phillip B. Gibbons, Garth A. Gibson, Joseph E. Gonzalez, Justin Gottschlich, Song Han, Kim M. Hazelwood, Furong Huang, Martin Jaggi, Kevin G. Jamieson, Michael I. Jordan, Gauri Joshi, Rania Khalaf, Jason Knight, Jakub Konecný, Tim Kraska, Arun Kumar, Anastasios Kyrillidis, Jing Li, Samuel Madden, H. Brendan McMahan, Erik Meijer, Ioannis Mitliagkas, Rajat Monga, Derek Gordon Murray, Dimitris S. Papailiopoulos, Gennady Pekhimenko, Theodoros Rekatsinas, Afshin Rostamizadeh, Christopher Ré, Christopher De Sa, Hanie Sedghi, Siddhartha Sen, Virginia Smith, Alex Smola, Dawn Song, Evan Randall Sparks, Ion Stoica, Vivienne Sze, Madeleine Udell, Joaquin Vanschoren, Shivaram Venkataraman, Rashmi Vinayak, Markus Weimer, Andrew Gordon Wilson, Eric P. Xing, Matei Zaharia, Ce Zhang, Ameet Talwalkar

CoRR, 2019

SysML'19 demo: customizable and reusable Collective Knowledge pipelines to automate and reproduce machine learning experiments.

Grigori Fursin

CoRR, 2019

2018

A model-driven approach for a new generation of adaptive libraries.

Marco Cianfriglia, Flavio Vella, Cedric Nugteren, Anton Lokhmotov, Grigori Fursin

CoRR, 2018

A Collective Knowledge workflow for collaborative research into multi-objective autotuning and machine learning techniques.

Grigori Fursin, Anton Lokhmotov, Dmitry Savenko, Eben Upton

CoRR, 2018

Introducing ReQuEST: an Open Platform for Reproducible and Quality-Efficient Systems-ML Tournaments.

Thierry Moreau, Anton Lokhmotov, Grigori Fursin

CoRR, 2018

Invited Talk Abstract: Introducing ReQuEST: An Open Platform for Reproducible and Quality-Efficient Systems-ML Tournaments.

Grigori Fursin

Proceedings of the 1st Workshop on Energy Efficient Machine Learning and Cognitive Computing for Embedded Applications, 2018

Multi-objective autotuning of MobileNets across the full software/hardware stack.

Anton Lokhmotov, Nikolay Chunosov, Flavio Vella, Grigori Fursin

Proceedings of the 1st on Reproducible Quality-Efficient Systems Tournament on Co-designing Pareto-efficient Deep Learning, 2018

PANEL: Open panel and discussion on tackling complexity, reproducibility and tech transfer challenges in a rapidly evolving AI/ML/systems research.

Grigori Fursin, Thierry Moreau, Hillery C. Hunter, Yiran Chen, Charles Qi, Tianqi Chen

Proceedings of the 1st on Reproducible Quality-Efficient Systems Tournament on Co-designing Pareto-efficient Deep Learning, 2018

2016

Benchmarking, autotuning and crowdtuning OpenCL programs using the Collective Knowledge framework.

Anton Lokhmotov, Grigori Fursin

Proceedings of the 4th International Workshop on OpenCL, 2016

Optimizing convolutional neural networks on embedded platforms with OpenCL.

Anton Lokhmotov, Grigori Fursin

Proceedings of the 4th International Workshop on OpenCL, 2016

Collective Knowledge: Towards R&D sustainability.

Grigori Fursin, Anton Lokhmotov, Ed Plowman

Proceedings of the 2016 Design, Automation & Test in Europe Conference & Exhibition, 2016

2015

Artifact Evaluation for Publications (Dagstuhl Perspectives Workshop 15452).

Bruce R. Childers, Grigori Fursin, Shriram Krishnamurthi, Andreas Zeller

Dagstuhl Reports, 2015

Collective Mind, Part II: Towards Performance- and Cost-Aware Software Engineering as a Natural Science.

Grigori Fursin, Abdul Wahid Memon, Christophe Guillon, Anton Lokhmotov

CoRR, 2015

2014

Collective mind: Towards practical and collaborative auto-tuning.

Grigori Fursin, Renato Miceli, Anton Lokhmotov, Michael Gerndt, Marc Baboulin, Allen D. Malony, Zbigniew Chamski, Diego Novillo, Davide Del Vento

Sci. Program., 2014

Finding representative sets of optimizations for adaptive multiversioning applications.

Lianjie Luo, Yang Chen, Chengyong Wu, Shun Long, Grigori Fursin

CoRR, 2014

Collective Tuning Initiative.

Grigori Fursin

CoRR, 2014

Proceedings of the 5th International Workshop on Adaptive Self-tuning Computing Systems 2015 (ADAPT'15).

Christophe Dubach, Grigori Fursin

CoRR, 2014

Community-driven reviewing and validation of publications.

Grigori Fursin, Christophe Dubach

Proceedings of the 1st ACM SIGPLAN Workshop on Reproducible Research Methodologies and New Publication Models in Computer Engineering, 2014

2013

Collective Mind: cleaning up the research and experimentation mess in computer engineering using crowdsourcing, big data and machine learning.

Grigori Fursin

CoRR, 2013

Crowdtuning: systematizing auto-tuning using predictive modeling and crowdsourcing.

Abdul Wahid Memon, Grigori Fursin

Proceedings of the Parallel Computing: Accelerating Computational Science and Engineering (CSE), 2013

2012

Deconstructing iterative optimization.

Yang Chen, Shuangde Fang, Yuanjie Huang, Lieven Eeckhout, Grigori Fursin, Olivier Temam, Chengyong Wu

ACM Trans. Archit. Code Optim., 2012

Poster: Collective Tuning: Novel Extensible Methodology, Framework and Public Repository to Collaboratively Address Exascale Challenges.

Grigori Fursin

Proceedings of the 2012 SC Companion: High Performance Computing, 2012

Abstract: cTuning.org: Novel Extensible Methodology, Framework and Public Repository to Collaboratively Address Exascale Challenges.

Grigori Fursin

Proceedings of the 2012 SC Companion: High Performance Computing, 2012

2011

Milepost GCC: Machine Learning Enabled Self-tuning Compiler.

Grigori Fursin, Yuriy Kashnikov, Abdul Wahid Memon, Zbigniew Chamski, Olivier Temam, Mircea Namolaru, Elad Yom-Tov, Bilha Mendelson, Ayal Zaks, Eric Courtois, François Bodin, Phil Barnard, Elton Ashton, Edwin V. Bonilla, John Thomson, Christopher K. I. Williams, Michael F. P. O'Boyle

Int. J. Parallel Program., 2011

2010

Collective optimization: A practical collaborative approach.

Grigori Fursin, Olivier Temam

ACM Trans. Archit. Code Optim., 2010

Evaluating iterative optimization across 1000 datasets.

Yang Chen, Yuanjie Huang, Lieven Eeckhout, Grigori Fursin, Liang Peng, Olivier Temam, Chengyong Wu

Proceedings of the 2010 ACM SIGPLAN Conference on Programming Language Design and Implementation, 2010

Practical aggregation of semantical program properties for machine learning based optimization.

Mircea Namolaru, Albert Cohen, Grigori Fursin, Ayal Zaks, Ari Freund

Proceedings of the 2010 International Conference on Compilers, 2010

2009

Systematic search within an optimisation space based on Unified Transformation Framework.

Shun Long, Grigori Fursin

Int. J. Comput. Sci. Eng., 2009

Portable compiler optimisation across embedded programs and microarchitectures using machine learning.

Christophe Dubach, Timothy M. Jones, Edwin V. Bonilla, Grigori Fursin, Michael F. P. O'Boyle

Proceedings of the 42st Annual IEEE/ACM International Symposium on Microarchitecture (MICRO-42 2009), 2009

Reducing Training Time in a One-Shot Machine Learning-Based Compiler.

John Thomson, Michael F. P. O'Boyle, Grigori Fursin, Björn Franke

Proceedings of the Languages and Compilers for Parallel Computing, 2009

Predictive Runtime Code Scheduling for Heterogeneous Architectures.

Víctor J. Jiménez, Lluís Vilanova, Isaac Gelado, Marisa Gil, Grigori Fursin, Nacho Navarro

Proceedings of the High Performance Embedded Architectures and Compilers, 2009

Collective Optimization.

Grigori Fursin, Olivier Temam

Proceedings of the High Performance Embedded Architectures and Compilers, 2009

2007

Quick and Practical Run-Time Evaluation of Multiple Program Optimizations.

Grigori Fursin, Albert Cohen, Michael F. P. O'Boyle, Olivier Temam

Trans. High Perform. Embed. Archit. Compil., 2007

A Cost-Aware Parallel Workload Allocation Approach Based on Machine Learning Techniques.

Shun Long, Grigori Fursin, Björn Franke

Proceedings of the Network and Parallel Computing, IFIP International Conference, 2007

MiDataSets: Creating the Conditions for a More Realistic Evaluation of Iterative Optimization.

Grigori Fursin, John Cavazos, Michael F. P. O'Boyle, Olivier Temam

Proceedings of the High Performance Embedded Architectures and Compilers, 2007

Rapidly Selecting Good Compiler Optimizations using Performance Counters.

John Cavazos, Grigori Fursin, Felix V. Agakov, Edwin V. Bonilla, Michael F. P. O'Boyle, Olivier Temam

Proceedings of the Fifth International Symposium on Code Generation and Optimization (CGO 2007), 2007

Fast compiler optimisation evaluation using code-feature based performance prediction.

Christophe Dubach, John Cavazos, Björn Franke, Grigori Fursin, Michael F. P. O'Boyle, Olivier Temam

Proceedings of the 4th Conference on Computing Frontiers, 2007

2006

Using Machine Learning to Focus Iterative Optimization.

Felix V. Agakov, Edwin V. Bonilla, John Cavazos, Björn Franke, Grigori Fursin, Michael F. P. O'Boyle, John Thomson, Marc Toussaint, Christopher K. I. Williams

Proceedings of the Fourth IEEE/ACM International Symposium on Code Generation and Optimization (CGO 2006), 2006

Automatic performance model construction for the fast software exploration of new hardware designs.

John Cavazos, Christophe Dubach, Felix V. Agakov, Edwin V. Bonilla, Michael F. P. O'Boyle, Grigori Fursin, Olivier Temam

Proceedings of the 2006 International Conference on Compilers, 2006

2005

Probabilistic source-level optimisation of embedded programs.

Björn Franke, Michael F. P. O'Boyle, John Thomson, Grigori Fursin

Proceedings of the 2005 ACM SIGPLAN/SIGBED Conference on Languages, 2005

A Heuristic Search Algorithm Based on Unified Transformation Framework.

Shun Long, Grigori Fursin

Proceedings of the 34th International Conference on Parallel Processing Workshops (ICPP 2005 Workshops), 2005

A Practical Method for Quickly Evaluating Program Optimizations.

Grigori Fursin, Albert Cohen, Michael F. P. O'Boyle, Olivier Temam

Proceedings of the High Performance Embedded Architectures and Compilers, 2005

2004

Iterative compilation and performance prediction for numerical applications.

Grigori Fursin

PhD thesis, 2004

A fast and accurate method for determining a lower bound on execution time.

Grigori Fursin, Michael F. P. O'Boyle, Olivier Temam, G. Watts

Concurr. Comput. Pract. Exp., 2004

2002

Evaluating Iterative Compilation.

Grigori Fursin, Michael F. P. O'Boyle, Peter M. W. Knijnenburg

Proceedings of the Languages and Compilers for Parallel Computing, 15th Workshop, 2002