Grigori Fursin

62 papers A* 3A 3B 1C 1Misc 2Journal 31Unranked 18

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Framing AI System Benchmarking as a Learning Task: FlexBench and the Open MLPerf Dataset. CoRR Grigori Fursin, Daniel Altunay
2025	A*	`conf`	MLPerf Power: Benchmarking the Energy Efficiency of Machine Learning Systems from μWatts to MWatts for Sustainable AI. HPCA 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
2024	J	`jnl`	Enabling more efficient and cost-effective AI/ML systems with Collective Mind, virtualized MLOps, MLPerf, Collective Knowledge Playground and reproducible optimization tournaments. CoRR Grigori Fursin
2024	J	`jnl`	MLPerf Power: Benchmarking the Energy Efficiency of Machine Learning Systems from Microwatts to Megawatts for Sustainable AI. CoRR 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
2023	J	`jnl`	Federated benchmarking of medical artificial intelligence with MedPerf. Nat. Mac. Intell. 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
2021	—	`conf`	A Community Roadmap for Scientific Workflows Research and Development. WORKS 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
2021	J	`jnl`	A Community Roadmap for Scientific Workflows Research and Development. CoRR 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
2021	J	`jnl`	MedPerf: Open Benchmarking Platform for Medical Artificial Intelligence using Federated Evaluation. CoRR 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
2021	J	`jnl`	On the Anatomy of Predictive Models for Accelerating GPU Convolution Kernels and Beyond. ACM Trans. Archit. Code Optim. Paolo Sylos Labini, Marco Cianfriglia, Damiano Perri, Osvaldo Gervasi, Grigori Fursin, Anton Lokhmotov, Cedric Nugteren, Bruno Carpentieri, Fabiana Zollo, Flavio Vella
2021	J	`jnl`	Workflows Community Summit: Advancing the State-of-the-art of Scientific Workflows Management Systems Research and Development. CoRR 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
2021	J	`jnl`	Workflows Community Summit: Bringing the Scientific Workflows Community Together. CoRR 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
2020	J	`jnl`	CodeReef: an open platform for portable MLOps, reusable automation actions and reproducible benchmarking. CoRR Grigori Fursin, Hervé Guillou, Nicolas Essayan
2020	J	`jnl`	Collective Knowledge: organizing research projects as a database of reusable components and portable workflows with common APIs. CoRR Grigori Fursin
2020	J	`jnl`	The Collective Knowledge project: making ML models more portable and reproducible with open APIs, reusable best practices and MLOps. CoRR Grigori Fursin
2019	J	`jnl`	SysML'19 demo: customizable and reusable Collective Knowledge pipelines to automate and reproduce machine learning experiments. CoRR Grigori Fursin
2019	J	`jnl`	SysML: The New Frontier of Machine Learning Systems. CoRR 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 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
2018	J	`jnl`	A Collective Knowledge workflow for collaborative research into multi-objective autotuning and machine learning techniques. CoRR Grigori Fursin, Anton Lokhmotov, Dmitry Savenko, Eben Upton
2018	J	`jnl`	A model-driven approach for a new generation of adaptive libraries. CoRR Marco Cianfriglia, Flavio Vella, Cedric Nugteren, Anton Lokhmotov, Grigori Fursin
2018	J	`jnl`	Introducing ReQuEST: an Open Platform for Reproducible and Quality-Efficient Systems-ML Tournaments. CoRR Thierry Moreau, Anton Lokhmotov, Grigori Fursin
2018	—	`conf`	Invited Talk Abstract: Introducing ReQuEST: An Open Platform for Reproducible and Quality-Efficient Systems-ML Tournaments. EMC2@ASPLOS Grigori Fursin
2018	—	`conf`	Multi-objective autotuning of MobileNets across the full software/hardware stack. ReQuEST@ASPLOS Anton Lokhmotov, Nikolay Chunosov, Flavio Vella, Grigori Fursin
2018	—	`conf`	PANEL: Open panel and discussion on tackling complexity, reproducibility and tech transfer challenges in a rapidly evolving AI/ML/systems research. ReQuEST@ASPLOS Grigori Fursin, Thierry Moreau, Hillery C. Hunter, Yiran Chen, Charles Qi, Tianqi Chen
2018	—	`ed.`	Proceedings of the 1st on Reproducible Quality-Efficient Systems Tournament on Co-designing Pareto-efficient Deep Learning, ReQuEST@ASPLOS 2018, Williamsburg, VA, USA, March 24, 2018 ReQuEST@ASPLOS Luis Ceze, Natalie D. Enright Jerger, Babak Falsafi, Grigori Fursin, Anton Lokhmotov, Thierry Moreau, Adrian Sampson, Phillip Stanley-Marbell
2016	—	`conf`	Benchmarking, autotuning and crowdtuning OpenCL programs using the Collective Knowledge framework. IWOCL Anton Lokhmotov, Grigori Fursin
2016	A	`conf`	Collective Knowledge: Towards R&D sustainability. DATE Grigori Fursin, Anton Lokhmotov, Ed Plowman
2016	—	`conf`	Optimizing convolutional neural networks on embedded platforms with OpenCL. IWOCL Anton Lokhmotov, Grigori Fursin
2015	J	`jnl`	Artifact Evaluation for Publications (Dagstuhl Perspectives Workshop 15452). Dagstuhl Reports Bruce R. Childers, Grigori Fursin, Shriram Krishnamurthi, Andreas Zeller
2015	J	`jnl`	Collective Mind, Part II: Towards Performance- and Cost-Aware Software Engineering as a Natural Science. CoRR Grigori Fursin, Abdul Wahid Memon, Christophe Guillon, Anton Lokhmotov
2014	J	`jnl`	Collective Tuning Initiative. CoRR Grigori Fursin
2014	J	`jnl`	Collective mind: Towards practical and collaborative auto-tuning. Sci. Program. Grigori Fursin, Renato Miceli, Anton Lokhmotov, Michael Gerndt, Marc Baboulin, Allen D. Malony, Zbigniew Chamski, Diego Novillo, Davide Del Vento
2014	—	`conf`	Community-driven reviewing and validation of publications. TRUST@PLDI Grigori Fursin, Christophe Dubach
2014	J	`jnl`	Community-driven reviewing and validation of publications. CoRR Grigori Fursin, Christophe Dubach
2014	J	`jnl`	Finding representative sets of optimizations for adaptive multiversioning applications. CoRR Lianjie Luo, Yang Chen, Chengyong Wu, Shun Long, Grigori Fursin
2014	—	`ed.`	Proceedings of the 1st ACM SIGPLAN Workshop on Reproducible Research Methodologies and New Publication Models in Computer Engineering, TRUST 2014, Edinburgh, United Kingdom, June 9-11, 2014 TRUST@PLDI Grigori Fursin, Bruce R. Childers, Alex K. Jones, Daniel Mossé
2014	J	`jnl`	Proceedings of the 5th International Workshop on Adaptive Self-tuning Computing Systems 2015 (ADAPT'15). CoRR Christophe Dubach, Grigori Fursin
2013	J	`jnl`	Collective Mind: cleaning up the research and experimentation mess in computer engineering using crowdsourcing, big data and machine learning. CoRR Grigori Fursin
2013	—	`conf`	Crowdtuning: systematizing auto-tuning using predictive modeling and crowdsourcing. PARCO Abdul Wahid Memon, Grigori Fursin
2012	—	`conf`	Abstract: cTuning.org: Novel Extensible Methodology, Framework and Public Repository to Collaboratively Address Exascale Challenges. SC Companion Grigori Fursin
2012	J	`jnl`	Deconstructing iterative optimization. ACM Trans. Archit. Code Optim. Yang Chen, Shuangde Fang, Yuanjie Huang, Lieven Eeckhout, Grigori Fursin, Olivier Temam, Chengyong Wu
2012	—	`conf`	Poster: Collective Tuning: Novel Extensible Methodology, Framework and Public Repository to Collaboratively Address Exascale Challenges. SC Companion Grigori Fursin
2011	J	`jnl`	Milepost GCC: Machine Learning Enabled Self-tuning Compiler. Int. J. Parallel Program. 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
2010	J	`jnl`	Collective optimization: A practical collaborative approach. ACM Trans. Archit. Code Optim. Grigori Fursin, Olivier Temam
2010	A*	`conf`	Evaluating iterative optimization across 1000 datasets. PLDI Yang Chen, Yuanjie Huang, Lieven Eeckhout, Grigori Fursin, Liang Peng, Olivier Temam, Chengyong Wu
2010	Misc	`conf`	Practical aggregation of semantical program properties for machine learning based optimization. CASES Mircea Namolaru, Albert Cohen, Grigori Fursin, Ayal Zaks, Ari Freund
2009	—	`conf`	Collective Optimization. HiPEAC Grigori Fursin, Olivier Temam
2009	A*	`conf`	Portable compiler optimisation across embedded programs and microarchitectures using machine learning. MICRO Christophe Dubach, Timothy M. Jones, Edwin V. Bonilla, Grigori Fursin, Michael F. P. O'Boyle
2009	—	`conf`	Predictive Runtime Code Scheduling for Heterogeneous Architectures. HiPEAC Víctor J. Jiménez, Lluís Vilanova, Isaac Gelado, Marisa Gil, Grigori Fursin, Nacho Navarro
2009	—	`conf`	Reducing Training Time in a One-Shot Machine Learning-Based Compiler. LCPC John Thomson, Michael F. P. O'Boyle, Grigori Fursin, Björn Franke
2009	J	`jnl`	Systematic search within an optimisation space based on Unified Transformation Framework. Int. J. Comput. Sci. Eng. Shun Long, Grigori Fursin
2007	C	`conf`	A Cost-Aware Parallel Workload Allocation Approach Based on Machine Learning Techniques. NPC Shun Long, Grigori Fursin, Björn Franke
2007	—	`conf`	Fast compiler optimisation evaluation using code-feature based performance prediction. Conf. Computing Frontiers Christophe Dubach, John Cavazos, Björn Franke, Grigori Fursin, Michael F. P. O'Boyle, Olivier Temam
2007	—	`conf`	MiDataSets: Creating the Conditions for a More Realistic Evaluation of Iterative Optimization. HiPEAC Grigori Fursin, John Cavazos, Michael F. P. O'Boyle, Olivier Temam
2007	J	`jnl`	Quick and Practical Run-Time Evaluation of Multiple Program Optimizations. Trans. High Perform. Embed. Archit. Compil. Grigori Fursin, Albert Cohen, Michael F. P. O'Boyle, Olivier Temam
2007	A	`conf`	Rapidly Selecting Good Compiler Optimizations using Performance Counters. CGO John Cavazos, Grigori Fursin, Felix V. Agakov, Edwin V. Bonilla, Michael F. P. O'Boyle, Olivier Temam
2006	Misc	`conf`	Automatic performance model construction for the fast software exploration of new hardware designs. CASES John Cavazos, Christophe Dubach, Felix V. Agakov, Edwin V. Bonilla, Michael F. P. O'Boyle, Grigori Fursin, Olivier Temam
2006	A	`conf`	Using Machine Learning to Focus Iterative Optimization. CGO 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
2005	—	`conf`	A Heuristic Search Algorithm Based on Unified Transformation Framework. ICPP Workshops Shun Long, Grigori Fursin
2005	—	`conf`	A Practical Method for Quickly Evaluating Program Optimizations. HiPEAC Grigori Fursin, Albert Cohen, Michael F. P. O'Boyle, Olivier Temam
2005	B	`conf`	Probabilistic source-level optimisation of embedded programs. LCTES Björn Franke, Michael F. P. O'Boyle, John Thomson, Grigori Fursin
2004	J	`jnl`	A fast and accurate method for determining a lower bound on execution time. Concurr. Comput. Pract. Exp. Grigori Fursin, Michael F. P. O'Boyle, Olivier Temam, G. Watts
2004	—	`—`	Iterative compilation and performance prediction for numerical applications. Grigori Fursin
2002	—	`conf`	Evaluating Iterative Compilation. LCPC Grigori Fursin, Michael F. P. O'Boyle, Peter M. W. Knijnenburg