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.
Here are some interesting things I’ve read. Presented without comment or endorsement.
I’m a panelist on the “Composable Systems Opportunities and Challenges” panel at SC'22, with my colleagues Christian Pinto and Kaotar El Maghraoui from IBM Research, the CEO and founder of H3 systems Brian Pan and my Ph.
I’m not much of a Twitter afficionado, which is probably why I prefer to use the following search string:
Roll your own integer linear programming (ILP) solver using Scipy.
C++ is hard; make it a bit easier.
Design of a static site with GNU Makefiles and pandoc
One of the resources I use to evaluate sparse-matrix vector multiplication (SpMV) performance at Sandia National Labs is the SuiteSparse Collection.
Setting up a python development environment is annoying. We’d especially like to avoid:
What to do when Disk Utility won’t
I MC’ed the Center for Cognitive Computing and Systems Research anniversary celebration.