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I am the technical lead behind VTA, an open-sourced deep learning acceleration hardware/software stack. I am also involved as a PMC member to Apache TVM, the open end-to-end compiler for deep learning systems.
In 2018 I co-organized with Grigori Fursin the first ACM ReQuEST tournament on reproducible and Pareto-Efficient deep learning systems research co-located at the ASPLOS 2018 conference.
As part of my Master's degree, I developed SNNAP, a co-processor prototype that can improve the energy efficiency of programs by approximating regions of code with neural networks. This work was presented at HPCA 2015.
I am the technical lead behind VTA, an open-sourced deep learning acceleration hardware/software stack. I am also involved as a PMC member to Apache TVM, the open end-to-end compiler for deep learning systems.
In 2018 I co-organized with Grigori Fursin the first ACM ReQuEST tournament on reproducible and Pareto-Efficient deep learning systems research co-located at the ASPLOS 2018 conference.
As part of my Master's degree, I developed SNNAP, a co-processor prototype that can improve the energy efficiency of programs by approximating regions of code with neural networks. This work was presented at HPCA 2015.
Research Interests
Papers共 35 篇Author StatisticsCo-AuthorSimilar Experts
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Stanley-Marbell Phillip, Alaghi Armin, Carbin Michael, Darulova Eva, Dolecek Lara, Gerstlauer Andreas,Gillani Ghayoor, Jevdjic Djordje,Moreau Thierry,Cacciotti Mattia, Daglis Alexandros,Jerger Natalie Enright,
ACM Computing Surveysno. 3 (2020): 1-39
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arXiv: Learning (2019)
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semanticscholar(2019)
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Luis Ceze, Natalie D. Enright Jerger,Babak Falsafi,Grigori Fursin,Anton Lokhmotov,Thierry Moreau,Adrian Sampson,Phillip Stanley-Marbell
dblp(2018)
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