Performance Portability

An Experimental Study of Two-level Schwarz Domain-Decomposition Preconditioners on GPUs
Ichitaro Yamazaki, Alexander Heinlein, Sivasankaran Rajamanickam
Batched Linear Solvers in Kokkos Kernels
Mar 2, 2023 12:00 AM Amsterdam, Netherlands.
Performance Portable Batched Sparse Linear Solvers
Kim Liegeois, Sivasankaran Rajamanickam, Luc Berger-Vergiat
Kokkos Kernels: Then and Now
Jan 19, 2023 12:00 AM Houston
Parallel, Portable Algorithms for Distance-2 Maximal Independent Set and Graph Coarsening
Brian Kelley, Sivasankaran Rajamanickam
Performance Portability
Computational science applications that I work with represent diverse science needs from climate, circuit simulations, mechanics and fluid simulations, electromagnetics simulations. Computational science applications that I work with are expected to run on the top 500 supercomputers in the world and on capacity clusters.
Kokkos Kernels
See Kokkos Kernels Website for more details.
Jan 8, 2022
Trilinos
Trilinos is large framework that serves as the foundation for several computational science applications. It provides capabilities for building portable, high performance, parallel science codes. The basic functionality provided include distributed linear algebra, portable sparse/dense linear algebra kernels, load balancing utilites, sparse linear solvers, non-linear solvers, discretization and meshing utilities.
Jan 8, 2022
Enabling Science Simulations with Scalable Computational Frameworks for Scientific Computing
Oct 19, 2021 10:00 AM — 11:00 AM Google X.
Experimental evaluation of multiprecision strategies for GMRES on GPUs
Jennifer A Loe, Christian A Glusa, Ichitaro Yamazaki, Erik G Boman, Sivasankaran Rajamanickam
A Study of Mixed Precision Strategies for GMRES on GPUs
Jennifer A Loe, Christian A Glusa, Ichitaro Yamazaki, Erik G Boman, Sivasankaran Rajamanickam
Experimental Evaluation of Multiprecision Strategies for GMRES on GPUs
Jennifer A Loe, Christian A Glusa, Ichitaro Yamazaki, Erik G Boman, Sivasankaran Rajamanickam
Performance-portable graph coarsening for efficient multilevel graph analysis
Michael S Gilbert, Seher Acer, Erik G Boman, Kamesh Madduri, Sivasankaran Rajamanickam
Sphynx: A parallel multi-GPU graph partitioner for distributed-memory systems
Seher Acer, Erik G Boman, Christian A Glusa, Sivasankaran Rajamanickam
Towards simulations on the Exascale hardware and beyond
Dec 3, 2020 3:30 PM — 5:00 PM University of Texas, Austin.
A Performance-Portable Nonhydrostatic Atmospheric Dycore for the Energy Exascale Earth System Model Running at Cloud-Resolving Resolutions.
Luca Bertagna, Oksana Guba, Mark A Taylor, James G Foucar, Jeff Larkin, Andrew M Bradley, Sivasankaran Rajamanickam, Andrew G Salinger
Performance portable supernode-based sparse triangular solver for manycore architectures
Ichitaro Yamazaki, Sivasankaran Rajamanickam, Nathan Ellingwood
SPHYNX: Spectral Partitioning for HYbrid aNd aXelerator-enabled systems
Seher Acer, Erik G Boman, Sivasankaran Rajamanickam
Scalable inference for sparse deep neural networks using Kokkos kernels
J Austin Ellis, Sivasankaran Rajamanickam
Scalable triangle counting on distributed-memory systems
Seher Acer, Abdurrahman Yaşar, Sivasankaran Rajamanickam, Michael Wolf, Ümit V Catalyürek
Embedded ensemble propagation for improving performance, portability, and scalability of uncertainty quantification on emerging computational architectures
Eric Phipps, Marta D'Elia, H Carter Edwards, Mark Hoemmen, Jonathan Hu, Sivasankaran Rajamanickam
Fast linear algebra-based triangle counting with kokkoskernels
Michael M Wolf, Mehmet Deveci, Jonathan W Berry, Simon D Hammond, Sivasankaran Rajamanickam
Parallel graph coloring for manycore architectures
Mehmet Deveci, Erik G Boman, Karen D Devine, Sivasankaran Rajamanickam
Towards extreme-scale simulations for low mach fluids with second-generation Trilinos
Paul Lin, Matthew Bettencourt, Stefan Domino, Travis Fisher, Mark Hoemmen, Jonathan Hu, Eric Phipps, Andrey Prokopenko, Sivasankaran Rajamanickam, Christopher Siefert, others
Towards extreme-scale simulations with next-generation Trilinos: a low Mach fluid application case study
Paul Lin, Matthew Bettencourt, Stefan Domino, Travis Fisher, Mark Hoemmen, Jonathan Hu, Eric Phipps, Andrey Prokopenko, Sivasankaran Rajamanickam, Christopher Siefert, others