Publications | Siva Rajamanickam

Trilinos: Enabling scientific computing across diverse hardware architectures at scale

Matthias Mayr, Alexander Heinlein, Christian Glusa, Sivasankaran Rajamanickam,, Et Al.

ShyLU-node: On-node scalable solvers and preconditioners: Recent progress and current performance

Ichitaro Yamazaki, Nathan Ellingwood, Sivasankaran Rajamanickam

Breaking the mold: Overcoming the time constraints of molecular dynamics on general-purpose hardware

Danny Perez, Aidan Thompson, Stan Moore, Tomas Oppelstrup, Ilya Sharapov, Kylee Santos, Amirali Sharifian, Delyan Z Kalchev, Robert Schreiber, Scott Pakin, Edgar a Leon, James H Laros, Michael James, Sivasankaran Rajamanickam

LAPIS: A Performance Portable, High Productivity Compiler Framework

Brian Kelley, Sivasankaran Rajamanickam

Beyond Exascale: Dataflow Domain Translation on a Cerebras Cluster

Tomas Oppelstrup, Nicholas Giamblanco, Delyan Z Kalchev, Ilya Sharapov, Mark Taylor, Dirk Van Essendelft, Sivasankaran Rajamanickam, Michael James

Distributed Sparse Tensor Computations in MLIR

Miheer Vaidya, Shreya Singh, Devanshu Mantri, Michael Shannon Eydenberg, Brian Michael Kelley, Sivasankaran Rajamanickam, Atanas Rountev, P Sadayappan

A Performance Portable Matrix Free Dense MTTKRP in GenTen

Gabriel Kosmacher, Eric T Phipps, Sivasankaran Rajamanickam

Do AI Models Perform Human-like Abstract Reasoning Across Modalities?

Claas Beger, Ryan Yi, Shuhao Fu, Kaleda Denton, Arseny Moskvichev, Sarah W Tsai, Sivasankaran Rajamanickam, Melanie Mitchell

Materials Learning Algorithms (MALA): Scalable machine learning for electronic structure calculations in large-scale atomistic simulations

Attila Cangi, Lenz Fiedler, Bartosz Brzoza, Karan Shah, Timothy J Callow, Daniel Kotik, Steve Schmerler, Matthew C Barry, James M Goff, Andrew Rohskopf, Dayton J Vogel, Normand Modine, Aidan P Thompson, Sivasankaran Rajamanickam

Performance Portable Gradient Computations Using Source Transformation

Kim Liegeois, Brian Kelley, Eric Phipps, Sivasankaran Rajamanickam, Vassil Vassilev

Cello: Co-Designing Schedule and Hybrid Implicit/Explicit Buffer for Complex Tensor Reuse

Raveesh Garg, Michael Pellauer, Sivasankaran Rajamanickam, Tushar Krishna

Imperfect Recognition: A Study of OCR Limitations in the Context of Scientific Documents

Chinmay Sahasrabudhe, Yang Ho, Nick Winovich, Sivasankaran Rajamanickam

Interface for sparse linear algebra operations

Ahmad Abdelfattah Et Al.

Jet: Multilevel graph partitioning on graphics processing units

Michael Gilbert, Kamesh Madduri, Erik G. Boman, Sivasankaran Rajamanickam

Breaking the Molecular Dynamics Timescale Barrier Using a Wafer-Scale System

Kylee Santos, Stan Moore, Tomas Oppelstrup, Amirali Sharifian, Ilya Sharapov, Aidan Thompson, Delyan Z Kalchev, Danny Perez, Robert Schreiber, Scott Pakin, Edgar a Leon, James H Laros III, Michael James, Sivasankaran Rajamanickam

TenSQL: An SQL Database Built on GraphBLAS

Jon Roose, Miheer Vaidya, Ponnuswamy Sadayappan, Sivasankaran Rajamanickam

Predicting electronic structures at any length scale with machine learning

Lenz Fiedler, Normand Modine, Steve Scmerler, Dayton J Vogel, Gabriel Popoola, Aidan P Thompson, Sivasankaran Rajamanickam, Attila Cangi

An Experimental Study of Two-level Schwarz Domain-Decomposition Preconditioners on GPUs

Ichitaro Yamazaki, Alexander Heinlein, Sivasankaran Rajamanickam

A Comparison of Spectral and Spatial Graph Convolutional Neural Network Kernels Using GraphSAGE-Sparse

Michael Eydenberg, Mark Plagge, Sivasankaran Rajamanickam

Performance Portable Batched Sparse Linear Solvers

Kim Liegeois, Sivasankaran Rajamanickam, Luc Berger-Vergiat

High-Performance GMRES Multi-Precision Benchmark: Design, Performance, and Challenges

Ichitaro Yamazaki, Christian Glusa, Jennifer Loe, Piotr Luszczek, Sivasankaran Rajamanickam, Jack Dongarra

Training-free hyperparameter optimization of neural networks for electronic structures in matter

Lenz Fiedler, Nils Hoffmann, Parvez Mohammed, Gabriel A. Popoola, Tamar Yovell, Vladyslav Oles, J. Austin Ellis, Sivasankaran Rajamanickam, Attila Cangi

Understanding the design-space of sparse/dense multiphase GNN dataflows on spatial accelerators

Raveesh Garg, Eric Qin, Francisco Munoz-Martinez, Robert Guirado, Akshay Jain, Sergi Abadal, Jose Abellan, Manuel Acacio, Eduard Alarcon, Sivasankaran Rajamanickam, Tushar Krishna

Parallel, Portable Algorithms for Distance-2 Maximal Independent Set and Graph Coarsening

Brian Kelley, Sivasankaran Rajamanickam

Concentric Spherical Neural Network for 3D Representation Learning

James Fox, Bo Zhao, Beatriz Gonzalez Del Rio, Sivasankaran Rajamanickam, Rampi Ramprasad, Le Song

Parallel graph coloring algorithms for distributed GPU environments

Ian Bogle, George M Slota, Erik G Boman, Karen Devine, Sivasankaran Rajamanickam

FROSch Preconditioners for Land Ice Simulations of Greenland and Antarctica

Alexander Heinlein, Mauro Perego, Sivasankaran Rajamanickam

Enabling Flexibility for Sparse Tensor Acceleration via Heterogeneity

Eric Qin, Raveesh Garg, Abhimanyu Bambhaniya, Michael Pellauer, Angshuman Parashar, Sivasankaran Rajamanickam, Cong Hao, Tushar Krishna

Evaluating Spatial Accelerator Architectures with Tiled Matrix-Matrix Multiplication

Gordon Moon, Hyoukjun Kwon, Geonhwa Jeong, Prashanth Chatarasi, Sivasankaran Rajamanickam, Tushar Krishna

Experimental evaluation of multiprecision strategies for GMRES on GPUs

Jennifer a Loe, Christian a Glusa, Ichitaro Yamazaki, Erik G Boman, Sivasankaran Rajamanickam

Extending Sparse Tensor Accelerators to Support Multiple Compression Formats

Eric Qin, Geonhwa Jeong, William Won, Sheng-Chun Kao, Hyoukjun Kwon, Sudarshan Srinivasan, Dipankar Das, Gordon E Moon, Sivasankaran Rajamanickam, Tushar Krishna

Union: A unified HW-SW Co-Design ecosystem in MLIR for evaluating tensor operations on spatial accelerators

Geonhwa Jeong, Gokcen Kestor, Prasanth Chatarasi, Angshuman Parashar, Po-an Tsai, Sivasankaran Rajamanickam, Roberto Gioiosa, Tushar Krishna

The Kokkos EcoSystem: Comprehensive Performance Portability For High Performance Computing

Christian R Trott, Luc Berger-Vergiat, David Poliakoff, Sivasankaran Rajamanickam, Damien Lebrun-Grandie, Jonathan Madsen, Nader Al Awar, Milos Gligoric, Galen Shipman, Geoff Womeldorff

Sphynx: A parallel multi-GPU graph partitioner for distributed-memory systems

Seher Acer, Erik G Boman, Christian a Glusa, Sivasankaran Rajamanickam

Performance-portable graph coarsening for efficient multilevel graph analysis

Michael S Gilbert, Seher Acer, Erik G Boman, Kamesh Madduri, Sivasankaran Rajamanickam

Kokkos Kernels: Performance Portable Sparse/Dense Linear Algebra and Graph Kernels

Sivasankaran Rajamanickam, Seher Acer, Luc Berger-Vergiat, Vinh Dang, Nathan Ellingwood, Evan Harvey, Brian Kelley, Christian R Trott, Jeremiah Wilke, Ichitaro Yamazaki

Kokkos 3: Programming model extensions for the exascale era

Christian R Trott, Damien Lebrun-Grandie, Daniel Arndt, Jan Ciesko, Vinh Dang, Nathan Ellingwood, Rahulkumar Gayatri, Evan Harvey, Daisy S Hollman, Dan Ibanez, Others

FROSch Preconditioners for Land Ice Simulations of Greenland and Antarctica

Alexander Heinlein, Mauro Perego, Sivasankaran Rajamanickam

Extending Sparse Tensor Accelerators to Support Multiple Compression Formats

Eric Qin, Geonhwa Jeong, William Won, Sheng-Chun Kao, Hyoukjun Kwon, Sudarshan Srinivasan, Dipankar Das, Gordon E Moon, Sivasankaran Rajamanickam, Tushar Krishna

Experimental Evaluation of Multiprecision Strategies for GMRES on GPUs

Jennifer a Loe, Christian a Glusa, Ichitaro Yamazaki, Erik G Boman, Sivasankaran Rajamanickam

EXAGRAPH: Graph and combinatorial methods for enabling exascale applications

Seher Acer, Ariful Azad, Erik G Boman, Aydın Buluç, Karen D Devine, SM Ferdous, Nitin Gawande, Sayan Ghosh, Mahantesh Halappanavar, Ananth Kalyanaraman, Others

Concentric Spherical GNN for 3D Representation Learning

James Fox, Bo Zhao, Sivasankaran Rajamanickam, Rampi Ramprasad, Le Song

Co-design center for exascale machine learning technologies (ExaLearn)

Francis J Alexander, James Ang, Jenna a Bilbrey, Jan Balewski, Tiernan Casey, Ryan Chard, Jong Choi, Sutanay Choudhury, Bert Debusschere, Anthony M DeGennaro, Others

Accelerating finite-temperature Kohn-Sham density functional theory with deep neural networks

J Austin Ellis, Lenz Fiedler, Gabriel a Popoola, Normand a Modine, J Adam Stephens, Aidan P Thompson, Attila Cangi, Sivasankaran Rajamanickam

A survey of numerical methods utilizing mixed precision arithmetic

Ahmad Abdelfattah, Hartwig Anzt, Erik G Boman, Erin Carson, Terry Cojean, Jack Dongarra, Alyson Fox, Mark Gates, Nicholas J Higham, Xiaoye Li, Others

A Study of Mixed Precision Strategies for GMRES on GPUs

Jennifer a Loe, Christian a Glusa, Ichitaro Yamazaki, Erik G Boman, Sivasankaran Rajamanickam

A Block-Based Triangle Counting Algorithm on Heterogeneous Environments

Abdurrahman Yaşar, Sivasankaran Rajamanickam, Jonathan W Berry, Ümit v Çatalyürek

SPHYNX: Spectral Partitioning for HYbrid aNd aXelerator-enabled systems

Seher Acer, Erik G Boman, Sivasankaran Rajamanickam

Scalable, multi-constraint, complex-objective graph partitioning

George M Slota, Cameron Root, Karen Devine, Kamesh Madduri, Sivasankaran Rajamanickam

Scalable asynchronous domain decomposition solvers

Christian Glusa, Erik G Boman, Edmond Chow, Sivasankaran Rajamanickam, Daniel B Szyld

Preparing sparse solvers for exascale computing

Hartwig Anzt, Erik Boman, Rob Falgout, Pieter Ghysels, Michael Heroux, Xiaoye Li, Lois Curfman McInnes, Richard Tran Mills, Sivasankaran Rajamanickam, Karl Rupp, Others

Performance portable supernode-based sparse triangular solver for manycore architectures

Ichitaro Yamazaki, Sivasankaran Rajamanickam, Nathan Ellingwood

Distributed Memory Graph Coloring Algorithms for Multiple GPUs

Ian Bogle, Erik G Boman, Karen Devine, Sivasankaran Rajamanickam, George M Slota

An algebraic sparsified nested dissection algorithm using low-rank approximations

Léopold Cambier, Chao Chen, Erik G Boman, Sivasankaran Rajamanickam, Raymond S Tuminaro, Eric Darve

ADELUS: A Performance-Portable Dense LU Solver for Distributed-Memory Hardware-Accelerated Systems.

Vinh Q Dang, Joseph D Kotulski, Sivasankaran Rajamanickam

A survey of numerical methods utilizing mixed precision arithmetic

Ahmad Abdelfattah, Hartwig Anzt, Erik G Boman, Erin Carson, Terry Cojean, Jack Dongarra, Mark Gates, Thomas Grützmacher, Nicholas J Higham, Sherry Li, Others

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

Scalable triangle counting on distributed-memory systems

Seher Acer, Abdurrahman Yaşar, Sivasankaran Rajamanickam, Michael Wolf, Ümit v Catalyürek

Scalable inference for sparse deep neural networks using Kokkos kernels

J Austin Ellis, Sivasankaran Rajamanickam

Scalable generation of graphs for benchmarking HPC community-detection algorithms

George M Slota, Jonathan W Berry, Simon D Hammond, Stephen L Olivier, Cynthia a Phillips, Sivasankaran Rajamanickam

Linear algebra-based triangle counting via fine-grained tasking on heterogeneous environments:(Update on static graph challenge)

Abdurrahman Yaşar, Sivasankaran Rajamanickam, Jonathan Berry, Michael Wolf, Jeffrey S Young, Ümit v Çatalyürek

Geometric Mapping of Tasks to Processors on Parallel Computers with Mesh or Torus Networks

Mehmet Deveci, Karen D Devine, Kevin Pedretti, Mark a Taylor, Sivasankaran Rajamanickam, Ümit v Çatalyürek

A robust hierarchical solver for ill-conditioned systems with applications to ice sheet modeling

Chao Chen, Leopold Cambier, Erik G Boman, Sivasankaran Rajamanickam, Raymond S Tuminaro, Eric Darve

A Portable SIMD Primitive Using Kokkos for Heterogeneous Architectures

Damodar Sahasrabudhe, Eric T Phipps, Sivasankaran Rajamanickam, Martin Berzins

A Parallel Graph Algorithm for Detecting Mesh Singularities in Distributed Memory Ice Sheet Simulations

Ian Bogle, Karen Devine, Mauro Perego, Sivasankaran Rajamanickam, George M Slota

Tacho: memory-scalable task parallel sparse Cholesky factorization

Kyungjoo Kim, H Carter Edwards, Sivasankaran Rajamanickam

Multithreaded sparse matrix-matrix multiplication for many-core and GPU architectures

Mehmet Deveci, Christian Trott, Sivasankaran Rajamanickam

Geometric partitioning and ordering strategies for task mapping on parallel computers

Mehmet Deveci, Karen D Devine, Kevin Pedretti, Mark a Taylor, Sivasankaran Rajamanickam, Umit v Catalyurek

FROSch: a fast and robust overlapping Schwarz domain decomposition preconditioner based on Xpetra in Trilinos

Alexander Heinlein, Axel Klawonn, Sivasankaran Rajamanickam, Oliver Rheinbach

Fast triangle counting using cilk

Abdurrahman Yaşar, Sivasankaran Rajamanickam, Michael Wolf, Jonathan Berry, Ümit v Çatalyürek

Experimental design of work chunking for graph algorithms on high bandwidth memory architectures

George M Slota, Siva Rajamanickam

Ensemble grouping strategies for embedded stochastic collocation methods applied to anisotropic diffusion problems

Marta D'Elia, H Carter Edwards, J Hu, E Phipps, Sivasankaran Rajamanickam

Asynchronous one-level and two-level domain decomposition solvers

Christian Glusa, Erik G Boman, Edmond Chow, Sivasankaran Rajamanickam, Paritosh Ramanan

A distributed-memory hierarchical solver for general sparse linear systems

Chao Chen, Hadi Pouransari, Sivasankaran Rajamanickam, Erik G Boman, Eric Darve

Performance-portable sparse matrix-matrix multiplication for many-core architectures

Mehmet Deveci, Christian Trott, Sivasankaran Rajamanickam

Partitioning trillion-edge graphs in minutes

George M Slota, Sivasankaran Rajamanickam, Karen Devine, Kamesh Madduri

Order or shuffle: Empirically evaluating vertex order impact on parallel graph computations

George M Slota, Sivasankaran Rajamanickam, Kamesh Madduri

Fast linear algebra-based triangle counting with kokkoskernels

Michael M Wolf, Mehmet Deveci, Jonathan W Berry, Simon D Hammond, Sivasankaran Rajamanickam

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

Distributed graph layout for scalable small-world network analysis

George M Slota, Sivasankaran Rajamanickam, Kamesh Madduri

Designing vector-friendly compact BLAS and LAPACK kernels

Kyungjoo Kim, Timothy B Costa, Mehmet Deveci, Andrew M Bradley, Simon D Hammond, Murat E Guney, Sarah Knepper, Shane Story, Sivasankaran Rajamanickam

Basker: Parallel sparse LU factorization utilizing hierarchical parallelism and data layouts

Joshua D Booth, Nathan D Ellingwood, Heidi K Thornquist, Sivasankaran Rajamanickam

Parallel graph coloring for manycore architectures

Mehmet Deveci, Erik G Boman, Karen D Devine, Sivasankaran Rajamanickam

Complex network partitioning using label propagation

George M Slota, Kamesh Madduri, Sivasankaran Rajamanickam

Basker: a threaded sparse lu factorization utilizing hierarchical parallelism and data layouts

Joshua Dennis Booth, Sivasankaran Rajamanickam, Heidi Thornquist

A survey of direct methods for sparse linear systems

Timothy a Davis, Sivasankaran Rajamanickam, Wissam M Sid-Lakhdar

A comparison of high-level programming choices for incomplete sparse factorization across different architectures

Joshua Dennis Booth, Kyungjoo Kim, Sivasankaran Rajamanickam

A case study of complex graph analysis in distributed memory: Implementation and optimization

George M Slota, Sivasankaran Rajamanickam, Kamesh Madduri

Multi-jagged: A scalable parallel spatial partitioning algorithm

Mehmet Deveci, Sivasankaran Rajamanickam, Karen D Devine, Ümit v Çatalyürek

High-performance graph analytics on manycore processors

George M Slota, Sivasankaran Rajamanickam, Kamesh Madduri

Building blocks for graph based network analysis

Vladimir Ufimtsev, Sanjukta Bhowmick, Sivasankaran Rajamanickam

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

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

PuLP: Scalable multi-objective multi-constraint partitioning for small-world networks

George M Slota, Kamesh Madduri, Sivasankaran Rajamanickam

Exploiting geometric partitioning in task mapping for parallel computers

Mehmet Deveci, Sivasankaran Rajamanickam, Vitus J Leung, Kevin Pedretti, Stephen L Olivier, David P Bunde, Umit v Catalyürek, Karen Devine

Domain decomposition preconditioners for communication-avoiding Krylov methods on a hybrid CPU/GPU cluster

Ichitaro Yamazaki, Sivasankaran Rajamanickam, Erik G Boman, Mark Hoemmen, Michael a Heroux, Stanimire Tomov

BFS and coloring-based parallel algorithms for strongly connected components and related problems

George M Slota, Sivasankaran Rajamanickam, Kamesh Madduri

A hybrid approach for parallel transistor-level full-chip circuit simulation

Heidi K Thornquist, Sivasankaran Rajamanickam

Scalable matrix computations on large scale-free graphs using 2D graph partitioning

Erik G Boman, Karen D Devine, Sivasankaran Rajamanickam