Carl Pearson is an LTE in the Scalable Algorithms group at Sandia National Labs and a Research Assistant Professor (LAT) of Computer Science at University of New Mexico. He works on future architectures for scientific computing, GPU communication for distributed linear algebra, and GPU acceleration of irregular operations.
He received his Ph.D in Electrical and Computer Engineering from the University of Illinois, and his B.S. in Engineering from Harvey Mudd College.
GPLv3 single-header C++11 Matrix Market Reader
Accumulated tips for formatting technical writing in Latex
Set up PhotoPrism on Google Cloud with docker-compose and a LetsEncrypt HTTPS certificate
Improving CUDA-Aware MPI_Pack speed by 300,000x. Code available.
I was invited to give a guest lecture for the Spring 2020 ECE 408 GPU programming course at the University of Illinois.
TA at PUMPS+AI 2019
Host your own GPU continuous integration pipeline with a bit of Python, Docker, and Azure Pipelines
Best research track paper at ICPE
Received the UIUC ECE Department’s E. A. Reid Fellowship
A short biography of Carl Pearson for general use