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Our achievements

Since 2009 we successfully bring together academia, industry and end-users to implement customizable and sustainable research software, crowdsource and reproduce experiments similar to SETI@home, and develop a radically new, holistic, interdisciplinary and scientific research methodology for computer engineering and artificial intelligence similar to physics, biology and other sciences.

Thanks to our partners and sponsors we managed to develop a novel open-source Collective Knowledge framework and repository to share artifacts and experimental workflows, crowdsource multi-objective autotuning and SW/HW co-design, combine it with machine learning, data mining and run-time adaptation, and enable efficient, self-optimizing and self-learning computer systems [ DATE'16, CPC'15, Scientific Programming'14, TRUST@PLDI'14 ].

Our collaborative and reproducible computer engineering methodology combined with predictive analytics helped enable world's first machine learning based self-tuning compiler (MILEPOST GCC), start crowdsourcing optimization and machine learning, and eventually initiate artifact evaluation at PPoPP, CGO, PACT and ADAPT and other conferences backed up by ACM to validate published results.

Our open-source techniques were published in PLDI, MICRO, CGO, ACM TACO, CASES, DATE and other major conferences and journals, included to mainline GCC (one of the most used compilers in the world), received various international awards, and used by ARM (p.17), Fujitsu, General Motors, IBM and other companies and universities.

We helped various international projects (MILEPOST, CARP, PAMELA) to develop customizable and sustainable research software powered by CK which surives even after these projects end or leading researchers leave!

Testimonials and awards


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