Grigori Fursin

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

Jan 27, 2020
Grigori Fursin, Herve Guillou, Nicolas Essayan

* Presented at the 1st Workshop on MLOps Systems co-located with the 3rd Conference on Machine Learning and Systems (MLSys'20) in Austin, TX, USA: https://mlops-systems.github.io . A live interactive demo: https://CodeReef.ai/demo

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SysML: The New Frontier of Machine Learning Systems

May 01, 2019
Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Jennifer Chayes, Eric Chung, Bill Dally, Jeff Dean, Inderjit S. Dhillon, Alexandros 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 Hazelwood, Furong Huang, Martin Jaggi, Kevin Jamieson, Michael I. Jordan, Gauri Joshi, Rania Khalaf, Jason Knight, Jakub Konečný, Tim Kraska, Arun Kumar, Anastasios Kyrillidis, Aparna Lakshmiratan, Jing Li, Samuel Madden, H. Brendan McMahan, Erik Meijer, Ioannis Mitliagkas, Rajat Monga, Derek Murray, Kunle Olukotun, Dimitris Papailiopoulos, Gennady Pekhimenko, Theodoros Rekatsinas, Afshin Rostamizadeh, Christopher Ré, Christopher De Sa, Hanie Sedghi, Siddhartha Sen, Virginia Smith, Alex Smola, Dawn Song, Evan Sparks, Ion Stoica, Vivienne Sze, Madeleine Udell, Joaquin Vanschoren, Shivaram Venkataraman, Rashmi Vinayak, Markus Weimer, Andrew Gordon Wilson, Eric Xing, Matei Zaharia, Ce Zhang, Ameet Talwalkar

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

Mar 31, 2019
Grigori Fursin

* Accepted demo at the Conference on Systems and Machine Learning (SysML'19)

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

Jan 19, 2018
Thierry Moreau, Anton Lokhmotov, Grigori Fursin

* ReQuEST tournament website: http://cKnowledge.org/request

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

Jun 20, 2015
Grigori Fursin, Abdul Memon, Christophe Guillon, Anton Lokhmotov

* Presented at the 18th International Workshop on Compilers for Parallel Computing (CPC'15), London, UK

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Finding representative sets of optimizations for adaptive multiversioning applications

Jul 14, 2014
Lianjie Luo, Yang Chen, Chengyong Wu, Shun Long, Grigori Fursin

* 3rd Workshop on Statistical and Machine Learning Approaches Applied to Architectures and Compilation (SMART'09), co-located with HiPEAC'09 conference, Paphos, Cyprus, 2009

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

Aug 11, 2013
Grigori Fursin

* I started drafting this document at the beginning of the development of the 3rd version of plugin-based cTuning infrastructure and repository (aka Collective Mind) to systematize and crowdsource program and architecture auto-tuning; (2013)

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