Gregory Diamos

ScalarLM Architect at AllyIn.ai

San Francisco Bay Area United States
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Summary

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Gregory Diamos is a systems architect and startup builder with 12+ years advancing high-performance AI infrastructure, currently leading ScalarLM development to train LLMs with superintelligent reasoning capabilities. Based in the San Francisco Bay Area, he blends deep GPU architecture expertise—from inventing Volta’s independent thread scheduling to building LLM systems on AMD MI series hardware—with product instincts honed by founding and exiting an LLM startup. A co-founder of MLCommons and creator of industry-standard MLPerf benchmarks, he has repeatedly moved research into production at scale, including shipping large-scale models at Baidu and prototyping cutting-edge hardware solutions at AMD. Gregory advises multiple AI companies while holding senior roles focused on applying advanced reasoning models to relational data and real-world products. He holds a PhD from Georgia Tech and is known for combining low-level compiler and hardware work with leadership that turns benchmarking and systems research into widely adopted engineering standards. An unusual through-line in his career is his knack for bridging compiler/GPU innovations with practical large-scale LLM deployments, enabling both performance gains and broader industry adoption.
code12 years of coding experience
job10 years of employment as a software developer
bookDoctor of Philosophy (PhD) Electrical and Electronics Engineering, Doctor of Philosophy (PhD) Electrical and Electronics Engineering at Georgia Institute of Technology
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Stackoverflow

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1answer
0questions
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Github Skills (27)

recurrent10
benchmark9
classifier9
hardware9
benchmarking9
keras9
machine-learning8
interoperability8
pytorch7
onnx7
mxnet7
gesture7
tensorflow7
scikit-learn7
deep-learning7

Programming languages (2)

C++Python

Github contributions (5)

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Contributions:100 commits, 2 PRs, 17 pushes in 2 months
pythonmachine-learningrecurrent-networksrecurrent
greg1232/align-speech

Dec 2021 - Jan 2022

Contributions:35 commits in 1 month
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