Depaul Miller
Senior Deep Learning Library Performance Software Engineer at NVIDIA
San Jose, California, United States
Summary
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Senior🎓
Top SchoolDepaul Miller is a Senior Deep Learning Library Performance Software Engineer at NVIDIA with nine years of experience specializing in heterogeneous and parallel computing, particularly GPGPU. He designs and ships state-of-the-art CUDA/C++ kernels and contributes to CUTLASS and MLIR-driven performance paths for deep learning and linear algebra. As a PhD candidate at Lehigh, his research bridged GPU computation with data repositories, concurrency control, and novel concurrent data structures—work that informed GPU-accelerated OLTP/HTAP designs and transaction-aware heterogeneous systems. He has a track record of turning research into production-grade optimizations (e.g., warp-specialized and TF32 cooperative kernels in CUTLASS 3.2) and focuses on latency and energy-efficient kernel design. Based in San Jose, he blends academic rigor (4.0 GPA across MS/PhD) with practical engineering across multiple NVIDIA internships and research appointments.
9 years of coding experience
5 years of employment as a software developer
Boston College High SchoolDoctor of Philosophy - PhD, Computer Science, 4.0, Doctor of Philosophy - PhD, Computer Science, 4.0 at Lehigh University
Stackoverflow
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Github Skills (44)
matrix-multiplication10
cluster-computing10
nvidia10
triton10
code-generation10
gpu10
cuda10
cpp10
algebra9
programming-language9
blas9
linear-algebra9
deep-learning9
compiler8
fabric8
Programming languages (7)
Github contributions (5)
depaulmillz/Rfantasyfootball
Jan 2017 - Nov 2018
Contributions:1 release, 2 PRs, 17 pushes in 1 year 10 months
footballrstatspredictivefantasyfantasy-football
depaulmillz/lslab
Nov 2021 - Mar 2023
Implementation of the L-slab hash map introduced in KVCG.
Contributions:1 release, 4 PRs, 46 pushes in 1 year 4 months
gpuhashhashmaphashtablekey-value
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