Grigori Fursin

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Grigori Fursin
Grigori Fursin (2016).jpg
Alma mater
Known for MILEPOST GCC, cTuning foundation, Collective Knowledge framework, Artifact Evaluation at IEEE/ACM conferences
Awards
  • Test of Time Award (IEEE/ACM International Symposium on Code Generation and Optimization, 2017)[1]
Scientific career
Fields Computer engineering
Machine learning
Institutions
Thesis Iterative Compilation and Performance Prediction for Numerical Applications (2004; 14 years ago (2004))
Website fursin.net/research.html

Grigori Fursin is a British[2] computer scientist and the president of the non-profit CTuning foundation. His research group created open-source machine learning based self-optimizing compiler, MILEPOST GCC, considered to be the first in the world.[3] At the end of the MILEPOST project he established cTuning foundation to crowdsource program optimisation and machine learning across diverse devices provided by volunteers. His foundation also developed Collective Knowledge Framework to support open research. Since 2015 Fursin leads Artifact Evaluation at several ACM and IEEE computer systems conferences. He is also a founding member of the ACM taskforce on Data, Software, and Reproducibility in Publication.[4]

Education[edit]

Fursin received a Master of Science degree in physics and mathematics from the Moscow Institute of Physics and Technology in 1999. He completed his PhD in computer science at the University of Edinburgh in 2005. While in Edinburgh, he worked on foundations of practical program autotuning and performance prediction.[5]

Notable projects[edit]

  • Collective Knowledge – open-source workflow framework with a package manager to help researchers organize and exchange code and data in a form of customisable, portable and reusable components with a unified JSON API, and quickly prototype, crowdsource and reproduce research experiments.
  • MILEPOST GCC – open-source technology to build machine learning based compilers.
  • Interactive Compilation Interface – plugin framework to expose internal features and optimisation decisions of compilers for external auto tuning and learning.
  • Artifact Evaluation – validation of experimental results from published papers at the leading ACM and IEEE computer systems conferences.
  • cTuning foundation – non-profit research organisation developing open-source tools and common methodology for collaborative and reproducible experimentation.

References[edit]

  1. ^ HiPEAC info 50 (page 8) (PDF), April 2017
  2. ^ Companies House profile, June 2015
  3. ^ World's First Intelligent, Open Source Compiler Provides Automated Advice on Software Code Optimization, IBM press-release, June 2009 (link)
  4. ^ "The ACM Task Force on Data, Software, and Reproducibility in Publication". Retrieved 5 December 2017.
  5. ^ Grigori Fursin. "Resume". Retrieved 21 May 2017.