Ayub Gubran
AI Accelerators Architecture
San Francisco Bay Area United States
Summary
👤
Senior🎓
Top SchoolAyub Gubran is an ASIC and SoC architect with nine years of experience designing and modeling high-performance AI accelerators, currently advancing Meta's MTIA efforts after contributing to Google's Tensor SoC. He holds a PhD focused on GPU and full-system performance modeling and is the author of the Emerald GPU/full-system model and a contributor to GPGPU-Sim, work that is publicly available and used by the research community. Ayub blends deep academic rigor with hands-on product engineering, having built software for a commercial bioprinter and modeled GPU hardware at Samsung and Google. His expertise spans microarchitectural design, performance analysis, and system-level simulation, enabling practical trade-offs between silicon complexity and application performance. Based in the San Francisco Bay Area, he bridges research and production teams to accelerate ML compute innovation. Colleagues rely on him for measurable performance insight grounded in open-source modeling artifacts.
9 years of coding experience
8 years of employment as a software developer
Study Abroad Program[me] Computer Science, Study Abroad Program[me] Computer Science at The University of ManchesterDoctor of Philosophy (PhD) Computer Engineering, Doctor of Philosophy (PhD) Computer Engineering at The University of British ColumbiaJordan University of Science and Technology
Github Skills (3)
mesa3
opengl1
3d-graphics1
Github contributions (5)
gem5-graphics/gem5-graphics
Aug 2016 - Jun 2020
Contributions:285 commits, 138 pushes, 1 branch in 3 years 10 months
gem5-graphics/mesa
Mar 2018 - May 2019
Contributions:11 pushes, 1 branch in 1 year 2 months
graphics-libraryopenglmesapull-requests3d-graphics
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