Michael Garland
Senior Director Of Research at NVIDIA
Lake Elmo, Minnesota, United States
Summary
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Rockstar🎓
Top SchoolMichael Garland is a senior research leader with 16+ years driving programming systems and applications research at NVIDIA, where he has led efforts to make modern parallel systems more accessible to developers. He combines deep academic roots—a PhD in computer science from Carnegie Mellon and a former faculty role at UIUC—with hands-on systems work ranging from sparse matrix libraries to compiler and portability fixes. His open-source contributions include improving the C++ templated CUSP sparse matrix library, addressing floating-point atomics and cross-compiler compatibility, reflecting a pragmatic focus on robust, portable numerical software. Based in Minnesota, he blends long-term strategic research leadership with concrete engineering contributions that bridge theory and production-scale parallel computing.
16 years of coding experience
11 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Computer Science, Doctor of Philosophy (Ph.D.), Computer Science at Carnegie Mellon University
Github Skills (15)
sparse-matrix10
code-templates10
apptemplates10
c-language10
cpp-templates10
html-template10
cprogramming-language10
python-templates10
linear-algebra10
numerical-methods9
file-handling8
cuda8
file-processing8
fileio8
file-access8
Programming languages (3)
Github contributions (5)
cusplibrary/cusplibrary
Dec 2009 - Nov 2010
CUSP : A C++ Templated Sparse Matrix Library
Role in this project:
Back-end Developer
Back-end DeveloperContributions:16 commits in 11 months
Contributions summary:Michael primarily focused on improving the C++ templated sparse matrix library, CUSP. Their contributions involved fixing potential type-related issues by explicitly tagging numeric literals and refining atomic operations for floating-point numbers. They also refactored the matrix market I/O routines, providing both file and stream-based input/output options. Moreover, the user addressed compiler-specific issues, such as those arising from Microsoft Visual Studio, improving overall compatibility and portability.
cppsparse-matrix
NVlabs/AdaBatch
Dec 2017 - Dec 2017
AdaBatch: Adaptive Batch Sizes for Training Deep Neural Networks
Contributions:2 commits, 1 push, 1 branch in 1 day
batch-sizedeep-neural-networks
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