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Grigori Fursin
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2020 – today
- 2024
- [i20]Grigori Fursin:
Enabling more efficient and cost-effective AI/ML systems with Collective Mind, virtualized MLOps, MLPerf, Collective Knowledge Playground and reproducible optimization tournaments. CoRR abs/2406.16791 (2024) - 2023
- [j9]Alexandros Karargyris
, Renato Umeton
Federated benchmarking of medical artificial intelligence with MedPerf. Nat. Mac. Intell. 5(7): 799-810 (2023) - 2021
- [j8]Paolo Sylos Labini, Marco Cianfriglia, Damiano Perri
On the Anatomy of Predictive Models for Accelerating GPU Convolution Kernels and Beyond. ACM Trans. Archit. Code Optim. 18(1): 16:1-16:24 (2021) - [c27]Rafael Ferreira da Silva
A Community Roadmap for Scientific Workflows Research and Development. WORKS 2021: 81-90 - [i19]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
Workflows Community Summit: Bringing the Scientific Workflows Community Together. CoRR abs/2103.09181 (2021) - [i18]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
Workflows Community Summit: Advancing the State-of-the-art of Scientific Workflows Management Systems Research and Development. CoRR abs/2106.05177 (2021) - [i17]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
MedPerf: Open Benchmarking Platform for Medical Artificial Intelligence using Federated Evaluation. CoRR abs/2110.01406 (2021) - [i16]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:
A Community Roadmap for Scientific Workflows Research and Development. CoRR abs/2110.02168 (2021) - 2020
- [i15]Grigori Fursin, Hervé Guillou, Nicolas Essayan:
CodeReef: an open platform for portable MLOps, reusable automation actions and reproducible benchmarking. CoRR abs/2001.07935 (2020) - [i14]Grigori Fursin:
The Collective Knowledge project: making ML models more portable and reproducible with open APIs, reusable best practices and MLOps. CoRR abs/2006.07161 (2020) - [i13]Grigori Fursin:
Collective Knowledge: organizing research projects as a database of reusable components and portable workflows with common APIs. CoRR abs/2011.01149 (2020)
2010 – 2019
- 2019
- [i12]Grigori Fursin:
SysML'19 demo: customizable and reusable Collective Knowledge pipelines to automate and reproduce machine learning experiments. CoRR abs/1904.00324 (2019) - [i11]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
SysML: The New Frontier of Machine Learning Systems. CoRR abs/1904.03257 (2019) - 2018
- [c26]Anton Lokhmotov, Nikolay Chunosov, Flavio Vella
Multi-objective autotuning of MobileNets across the full software/hardware stack. ReQuEST@ASPLOS 2018: 6 - [c25]Grigori Fursin, Thierry Moreau, Hillery C. Hunter, Yiran Chen, Charles Qi, Tianqi Chen:
PANEL: Open panel and discussion on tackling complexity, reproducibility and tech transfer challenges in a rapidly evolving AI/ML/systems research. ReQuEST@ASPLOS 2018: 7 - [c24]Grigori Fursin:
Invited Talk Abstract: Introducing ReQuEST: An Open Platform for Reproducible and Quality-Efficient Systems-ML Tournaments. EMC2@ASPLOS 2018: 3 - [e2]Luis Ceze, Natalie D. Enright Jerger, Babak Falsafi, Grigori Fursin, Anton Lokhmotov, Thierry Moreau, Adrian Sampson, Phillip Stanley-Marbell:
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. ACM 2018 [contents] - [i10]Thierry Moreau, Anton Lokhmotov, Grigori Fursin:
Introducing ReQuEST: an Open Platform for Reproducible and Quality-Efficient Systems-ML Tournaments. CoRR abs/1801.06378 (2018) - [i9]Grigori Fursin, Anton Lokhmotov, Dmitry Savenko, Eben Upton:
A Collective Knowledge workflow for collaborative research into multi-objective autotuning and machine learning techniques. CoRR abs/1801.08024 (2018) - [i8]Marco Cianfriglia, Flavio Vella, Cedric Nugteren, Anton Lokhmotov, Grigori Fursin:
A model-driven approach for a new generation of adaptive libraries. CoRR abs/1806.07060 (2018) - 2016
- [c23]Grigori Fursin, Anton Lokhmotov, Ed Plowman:
Collective Knowledge: Towards R&D sustainability. DATE 2016: 864-869 - [c22]Anton Lokhmotov, Grigori Fursin:
Optimizing convolutional neural networks on embedded platforms with OpenCL. IWOCL 2016: 10:1-10:4 - [c21]Anton Lokhmotov, Grigori Fursin:
Benchmarking, autotuning and crowdtuning OpenCL programs using the Collective Knowledge framework. IWOCL 2016: 20:1-20:2 - 2015
- [i7]Grigori Fursin, Abdul Wahid Memon, Christophe Guillon, Anton Lokhmotov:
Collective Mind, Part II: Towards Performance- and Cost-Aware Software Engineering as a Natural Science. CoRR abs/1506.06256 (2015) - [i6]Bruce R. Childers, Grigori Fursin, Shriram Krishnamurthi, Andreas Zeller:
Artifact Evaluation for Publications (Dagstuhl Perspectives Workshop 15452). Dagstuhl Reports 5(11): 29-35 (2015) - 2014
- [j7]Grigori Fursin, Renato Miceli, Anton Lokhmotov, Michael Gerndt, Marc Baboulin, Allen D. Malony, Zbigniew Chamski, Diego Novillo, Davide Del Vento:
Collective mind: Towards practical and collaborative auto-tuning. Sci. Program. 22(4): 309-329 (2014) - [c20]Grigori Fursin, Christophe Dubach:
Community-driven reviewing and validation of publications. TRUST@PLDI 2014: 5:1-5:4 - [e1]Grigori Fursin, Bruce R. Childers, Alex K. Jones, Daniel Mossé:
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. ACM 2014, ISBN 978-1-4503-2951-4 [contents] - [i5]Grigori Fursin, Christophe Dubach:
Community-driven reviewing and validation of publications. CoRR abs/1406.4020 (2014) - [i4]Grigori Fursin:
Collective Tuning Initiative. CoRR abs/1407.3487 (2014) - [i3]Lianjie Luo, Yang Chen, Chengyong Wu, Shun Long, Grigori Fursin:
Finding representative sets of optimizations for adaptive multiversioning applications. CoRR abs/1407.4075 (2014) - [i2]Christophe Dubach, Grigori Fursin:
Proceedings of the 5th International Workshop on Adaptive Self-tuning Computing Systems 2015 (ADAPT'15). CoRR abs/1412.2347 (2014) - 2013
- [c19]Abdul Wahid Memon, Grigori Fursin:
Crowdtuning: systematizing auto-tuning using predictive modeling and crowdsourcing. PARCO 2013: 656-667 - [i1]Grigori Fursin:
Collective Mind: cleaning up the research and experimentation mess in computer engineering using crowdsourcing, big data and machine learning. CoRR abs/1308.2410 (2013) - 2012
- [j6]Yang Chen, Shuangde Fang, Yuanjie Huang, Lieven Eeckhout, Grigori Fursin, Olivier Temam, Chengyong Wu:
Deconstructing iterative optimization. ACM Trans. Archit. Code Optim. 9(3): 21:1-21:30 (2012) - [c18]Grigori Fursin:
Abstract: cTuning.org: Novel Extensible Methodology, Framework and Public Repository to Collaboratively Address Exascale Challenges. SC Companion 2012: 1401-1402 - [c17]Grigori Fursin:
Poster: Collective Tuning: Novel Extensible Methodology, Framework and Public Repository to Collaboratively Address Exascale Challenges. SC Companion 2012: 1403 - 2011
- [j5]Grigori Fursin, Yuriy Kashnikov, Abdul Wahid Memon, Zbigniew Chamski, Olivier Temam, Mircea Namolaru, Elad Yom-Tov
Milepost GCC: Machine Learning Enabled Self-tuning Compiler. Int. J. Parallel Program. 39(3): 296-327 (2011) - 2010
- [j4]Grigori Fursin, Olivier Temam:
Collective optimization: A practical collaborative approach. ACM Trans. Archit. Code Optim. 7(4): 20:1-20:29 (2010) - [c16]Mircea Namolaru, Albert Cohen, Grigori Fursin, Ayal Zaks, Ari Freund:
Practical aggregation of semantical program properties for machine learning based optimization. CASES 2010: 197-206 - [c15]Yang Chen, Yuanjie Huang, Lieven Eeckhout, Grigori Fursin, Liang Peng, Olivier Temam, Chengyong Wu:
Evaluating iterative optimization across 1000 datasets. PLDI 2010: 448-459
2000 – 2009
- 2009
- [j3]Shun Long, Grigori Fursin:
Systematic search within an optimisation space based on Unified Transformation Framework. Int. J. Comput. Sci. Eng. 4(2): 102-111 (2009) - [c14]Víctor J. Jiménez, Lluís Vilanova
Predictive Runtime Code Scheduling for Heterogeneous Architectures. HiPEAC 2009: 19-33 - [c13]Grigori Fursin, Olivier Temam:
Collective Optimization. HiPEAC 2009: 34-49 - [c12]John Thomson, Michael F. P. O'Boyle, Grigori Fursin, Björn Franke
Reducing Training Time in a One-Shot Machine Learning-Based Compiler. LCPC 2009: 399-407 - [c11]Christophe Dubach, Timothy M. Jones
Portable compiler optimisation across embedded programs and microarchitectures using machine learning. MICRO 2009: 78-88 - 2007
- [j2]Grigori Fursin, Albert Cohen, Michael F. P. O'Boyle, Olivier Temam:
Quick and Practical Run-Time Evaluation of Multiple Program Optimizations. Trans. High Perform. Embed. Archit. Compil. 1: 34-53 (2007) - [c10]Christophe Dubach, John Cavazos, Björn Franke
Fast compiler optimisation evaluation using code-feature based performance prediction. Conf. Computing Frontiers 2007: 131-142 - [c9]John Cavazos, Grigori Fursin, Felix V. Agakov, Edwin V. Bonilla, Michael F. P. O'Boyle, Olivier Temam:
Rapidly Selecting Good Compiler Optimizations using Performance Counters. CGO 2007: 185-197 - [c8]Grigori Fursin, John Cavazos, Michael F. P. O'Boyle, Olivier Temam:
MiDataSets: Creating the Conditions for a More Realistic Evaluation of Iterative Optimization. HiPEAC 2007: 245-260 - [c7]Shun Long, Grigori Fursin, Björn Franke
A Cost-Aware Parallel Workload Allocation Approach Based on Machine Learning Techniques. NPC 2007: 506-515 - 2006
- [c6]John Cavazos, Christophe Dubach, Felix V. Agakov, Edwin V. Bonilla, Michael F. P. O'Boyle, Grigori Fursin, Olivier Temam:
Automatic performance model construction for the fast software exploration of new hardware designs. CASES 2006: 24-34 - [c5]Felix V. Agakov, Edwin V. Bonilla, John Cavazos, Björn Franke
Using Machine Learning to Focus Iterative Optimization. CGO 2006: 295-305 - 2005
- [c4]Grigori Fursin, Albert Cohen, Michael F. P. O'Boyle, Olivier Temam:
A Practical Method for Quickly Evaluating Program Optimizations. HiPEAC 2005: 29-46 - [c3]Shun Long, Grigori Fursin:
A Heuristic Search Algorithm Based on Unified Transformation Framework. ICPP Workshops 2005: 137-144 - [c2]Björn Franke
Probabilistic source-level optimisation of embedded programs. LCTES 2005: 78-86 - 2004
- [b1]Grigori Fursin:
Iterative compilation and performance prediction for numerical applications. University of Edinburgh, UK, 2004 - [j1]Grigori Fursin, Michael F. P. O'Boyle, Olivier Temam, G. Watts:
A fast and accurate method for determining a lower bound on execution time. Concurr. Comput. Pract. Exp. 16(2-3): 271-292 (2004) - 2002
- [c1]Grigori Fursin, Michael F. P. O'Boyle, Peter M. W. Knijnenburg:
Evaluating Iterative Compilation. LCPC 2002: 362-376
Coauthor Index
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