Carl Pearson is a Postdoctoral Appointee at Sandia National Labs and a Research Assistant Professor (LAT) of Computer Science at University of New Mexico. He works on GPU communication for distributed linear algebra, and GPU acceleration of sparse matrix multiplication.

He recieved his Ph.D in Electrical and Computer Engineering from the University of Illinois in 2021, and his B.S. in Engineering from Harvey Mudd College.


SuiteSparse Collection Downloader

One of the resources I use to evaluate sparse-matrix vector multiplication (SpMV) performance at Sandia National Labs is the SuiteSparse Collection.

Interesting Links from November

Here are some interesting things I read this month. Presented without comment or endorsement.

Setting up Python with Pyenv and Poetry on Debian

Setting up a python development environment is annoying. We’d especially like to avoid:

Formatting MacOS Disk on Command Line

What to do when Disk Utility won’t

C3SR Anniversary Celebration

I MC’ed the Center for Cognitive Computing and Systems Research anniversary celebration.

Single-header C++ Matrix Market Reader

GPLv3 single-header C++11 Matrix Market Reader

Tips for Technical Writing in Latex

Accumulated tips for formatting technical writing in Latex

Setting up Photoprism with HTTPS on Google Compute Engine

Set up PhotoPrism on Google Cloud with docker-compose and a LetsEncrypt HTTPS certificate

Improving MPI_Pack performance in CUDA-aware MPI

Improving CUDA-Aware MPI_Pack speed by 300,000x. Code available.

Nsight Systems and Nsight Compute Teaching Resources

I was invited to give a guest lecture for the Spring 2020 ECE 408 GPU programming course at the University of Illinois.