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Grigori Fursin is a computer scientist, software developer, consultant and entrepreneur with an interdisciplinary background in physics, electronics, computer engineering, and machine learning and with more than 20 years of research and development experience. He is always interested to consult companies and lead highly challenging, innovative and interdisciplinary research and development projects particularly related to development of faster, smaller, cheaper, more power efficient and reliable self-tuning computer systems; collaborative discovery, systematization, sharing and reuse of knowledge; big data; predictive analytics; electronic brain; artificial intelligence; bio-inspired devices; systematization of benchmarking; automation of compiler tuning; robotics; space exploration; semantic web; crowdsourcing using even commodity mobile phones, social networking and collective intelligence.
In 1993, at the age of 16, Grigori joined his first official R&D project as a Research Assistant designing and optimizing semiconductor neural network accelerators for a possible brain-inspired supercomputer computer [M9, M8]. After amateur and tedious attempts to optimize and parallelize his neural network modeling software for several supercomputers, Grigori decided to switch to computer engineering to automate and systematize this process using his interdisciplinary knowledge. Eventually, Grigori was one of the first researchers to radically change ad-hoc, error prone, time consuming and costly process of designing, benchmarking and optimizing the next generation of computer systems across all software and hardware layers into a unified big data problem [P1, M2, P23, P14, P16, P5]. He then started tackling, systematizing and speeding it up using his public cTuning.org and Collective Mind repository of knowledge, common plugin-based auto-tuning infrastructure, statistical analysis, machine learning (classification and predictive analytics), data mining (finding missing features), run-time adaptation with static multi-versioning, adaptive exploration of large optimization spaces, online tuning, differential analysis, brain-inspired self-optimization, crowdsourcing using even commodity mobile phones, social networking and collective intelligence.
Besides publishing in major conferences and journals including PLDI, MICRO, CGO, TACO, IJPP, CASES and HiPEAC, Grigori spends considerable effort to release all his artifacts including tools, benchmarks, data sets and predictive models along with his articles at cTuning.org and c-mind.org/repo to ensure reproducibility. As a side effect, this initiated new open publication model in computer engineering where experimental results and all research artifacts are continuously shared, discussed, reproduced and improved by the community [E1,E2,P2, M1,E9,P5].
This also helped to move Grigori's techniques to mainstream production environments including GCC while validating and extending them in industry with IBM, ARC (Synopsys), Intel, Google, STMicroelectronics and ARM. These techniques enabled practical open-source machine learning based self-tuning compiler (MILEPOST GCC) [M3,R3,R1] considered by IBM to be the first in the world [P22]. They also dramatically reduced development costs of the new embedded reconfigurable devices from ARC (Synopsys) while improving time to market and ROI [X8]. Finally, Grigori's techniques were included in the EU HiPEAC IT research vision for 2012-2020 [X7, X2] In 2008, Grigori established international nonprofit cTuning.org foundation to help academic and industrial partners systematize, automate and speed up design, benchmarking optimization of their computer systems (software and hardware stack) using his open source repository, tools and big data analytics.
Grigori delivered more than 60 regular and invited talks, lectures and keynotes in major international companies and universities in Europe, USA, China, Canada, Russia and Taiwan; founded SMART and ADAPT workshops that ran consecutively for 8 years sponsored by Google, NVidia, Intel and Microsoft; prepared and taught advanced MS course on future self-tuning computer systems in Paris South University. In 2010-2011, he was on industrial leave invited to help establish Intel Exascale Lab in France while preparing long-term research directions and serving as the head of program optimization and characterization group [I1]. In 2012, Grigori rejoined INRIA and received a 4-year fellowship for "making an outstanding contribution to research" [A1]. Grigori hopes his research will help improve our society by boosting innovation in science and technology.
Keywords: Collective Mind, program and architecture crowdtuning, plugin-based auto-tuning, machine learning, data mining, public repository of knowledge, big data, crowdsourcing, compilers, online tuning, run-time adaptation, software and hardware co-design, electronic brain, neural networks, predictive analytics, statistical analysis, feature analysis, decremental analysis, decremental characterization, complexity reduction, reproducible research, crowdsourcing experimentation, cTuning.org, c-mind.org, agile research and development, knowledge systematization, emerging information technologies, knowledge transfer to industry, consulting, startups