Carl Pearson

Carl Pearson is Computer Science Research and Development staff in the Scalable Algorithms group at Sandia National Laboratories 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.

Recent Publications

Trilinos: Enabling Scientific Computing Across Diverse Hardware Architectures at Scale
Matthias Mayr, Alexander Heinlein, Christian Glusa, Siva Rajamanickam, Maarten Arnst, Roscoe Bartlett, Luc Berger-Vergiat, Erik Boman, Karen Devine, Graham Harper, Michael Heroux, Mark Hoemmen, Jonathan Hu, Brian Kelley, Kyungjoo Kim, Drew P Kouri, Paul Kuberry, Kim Liegeois, Curtis C Ober, Roger Pawlowski, Carl Pearson, Mauro Perego, Eric Phipps, Denis Ridzal, Nathan V Roberts, Christopher Siefert, Heidi Thornquist, Romin Tomasetti, Christian R Trott, Raymond S Tuminaro, James M Willenbring, Michael M Wolf, Ichitaro Yamazaki
arXiv
03/25
KokkosComm: Communication Layer for Distributed Kokkos Applications
Gabriel Dos Santos, Nicole Avans, Cedric Chevalier, Hugo Taboada, Carl Pearson, Jan Ciesko, Stephen L. Olivier, Marc Perache
in
EuroMPI
09/24
Latency and Bandwidth Microbenchmarks of US Department of Energy Systems in the June 2023 Top 500 List
Christopher M. Siefert, Carl Pearson, Stephen L. Olivier, Andrey Prokopenko, Jonathan J. Hu, Timothy J. Fuller
in
14th IEEE International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems
11/23
Latency and Bandwidth Microbenchmarks of Six US Department of Energy Systems in the Top500
Carl Pearson, Christopher M. Siefert, Stephen L. Olivier, Andrey Prokopenko, Timothy J. Fuller, Jonathan J. Hu
in
IEEE Cluster 2023
11/23
Interconnect Bandwidth Heterogeneity on AMD MI250x and Infinity Fabric
Carl Pearson
arXiv
02/23
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