Algorithm 887: CHOLMOD, Supernodal Sparse Cholesky Factorization and Update/Downdate. - Yanqing Chen; Timothy A. Davis 001; William W. Hager; Sivasankaran Rajamanickam (ACM Trans. Math. Softw., 2008)

Enabling Next-Generation Parallel Circuit Simulation with Trilinos. - Chris G. Baker; Erik G. Boman; Michael A. Heroux; Eric R. Keiter; Sivasankaran Rajamanickam; Rich Schiek; Heidi Thornquist (Euro-Par Workshops (1), 2011)

Poster: a hybrid-hybrid solver for manycore platforms. - Sivasankaran Rajamanickam; Erik G. Boman; Michael A. Heroux (SC Companion, 2011)

Parallel partitioning with Zoltan: Is hypergraph partitioning worth it? - Sivasankaran Rajamanickam; Erik G. Boman (Graph Partitioning and Graph Clustering, 2012)

Multithreaded Algorithms for Maxmum Matching in Bipartite Graphs. - Ariful Azad; Mahantesh Halappanavar; Sivasankaran Rajamanickam; Erik G. Boman; Arif M. Khan; Alex Pothen (IPDPS, 2012)

ShyLU: A Hybrid-Hybrid Solver for Multicore Platforms. - Sivasankaran Rajamanickam; Erik G. Boman; Michael A. Heroux (IPDPS, 2012)

Amesos2 and Belos: Direct and iterative solvers for large sparse linear systems. - Eric Bavier; Mark Hoemmen; Sivasankaran Rajamanickam; Heidi Thornquist (Sci. Program., 2012)

Scalable matrix computations on large scale-free graphs using 2D graph partitioning. - Erik G. Boman; Karen D. Devine; Sivasankaran Rajamanickam (SC, 2013)

Electrical modeling and simulation for stockpile stewardship. - Heidi Thornquist; Eric R. Keiter; Sivasankaran Rajamanickam (XRDS, 2013)

PuLP: Scalable multi-objective multi-constraint partitioning for small-world networks. - George M. Slota; Kamesh Madduri; Sivasankaran Rajamanickam (IEEE BigData, 2014)

Building blocks for graph based network analysis. - Vladimir Ufimtsev; Sanjukta Bhowmick; Sivasankaran Rajamanickam (HPEC, 2014)

Exploiting Geometric Partitioning in Task Mapping for Parallel Computers. - Mehmet Deveci; Sivasankaran Rajamanickam; Vitus J. Leung; Kevin T. Pedretti; Stephen L. Olivier; David P. Bunde; Ümit V. Çatalyürek; Karen D. Devine (IPDPS, 2014)

Towards Extreme-Scale Simulations with Next-Generation Trilinos: A Low Mach Fluid Application Case Study. - Paul T. Lin; Matthew T. Bettencourt; Stefan Domino; Travis Fisher; Mark Hoemmen; Jonathan J. Hu; Eric T. Phipps; Andrey Prokopenko; Sivasankaran Rajamanickam; Christopher M. Siefert; Eric C. Cyr; Stephen Kennon (IPDPS Workshops, 2014)

BFS and Coloring-Based Parallel Algorithms for Strongly Connected Components and Related Problems. - George M. Slota; Sivasankaran Rajamanickam; Kamesh Madduri (IPDPS, 2014)

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 (SC, 2014)

A Hybrid Approach for Parallel Transistor-Level Full-Chip Circuit Simulation. - Heidi K. Thornquist; Sivasankaran Rajamanickam (VECPAR, 2014)

Towards Extreme-Scale Simulations for Low Mach Fluids with Second-Generation Trilinos. - Paul T. Lin; Matthew T. Bettencourt; Stefan Domino; Travis Fisher; Mark Hoemmen; Jonathan J. Hu; Eric T. Phipps; Andrey Prokopenko; Sivasankaran Rajamanickam; Christopher M. Siefert; Stephen Kennon (Parallel Process. Lett., 2014)

High-Performance Graph Analytics on Manycore Processors. - George M. Slota; Sivasankaran Rajamanickam; Kamesh Madduri (IPDPS, 2015)

A Comparison of High-Level Programming Choices for Incomplete Sparse Factorization Across Different Architectures. - Joshua Dennis Booth; Kyungjoo Kim; Sivasankaran Rajamanickam (IPDPS Workshops, 2016)

Basker: A Threaded Sparse LU Factorization Utilizing Hierarchical Parallelism and Data Layouts. - Joshua Dennis Booth; Sivasankaran Rajamanickam; Heidi Thornquist (IPDPS Workshops, 2016)

Parallel Graph Coloring for Manycore Architectures. - Mehmet Deveci; Erik G. Boman; Karen D. Devine; Sivasankaran Rajamanickam (IPDPS, 2016)

A Case Study of Complex Graph Analysis in Distributed Memory: Implementation and Optimization. - George M. Slota; Sivasankaran Rajamanickam; Kamesh Madduri (IPDPS, 2016)

A survey of direct methods for sparse linear systems. - Timothy A. Davis 001; Sivasankaran Rajamanickam; Wissam M. Sid-Lakhdar (Acta Numer., 2016)

Task Parallel Incomplete Cholesky Factorization using 2D Partitioned-Block Layout. - Kyungjoo Kim; Sivasankaran Rajamanickam; George Stelle; H. Carter Edwards; Stephen L. Olivier (CoRR, 2016)

Complex Network Partitioning Using Label Propagation. - George M. Slota; Kamesh Madduri; Sivasankaran Rajamanickam (SIAM J. Sci. Comput., 2016)

Multi-Jagged: A Scalable Parallel Spatial Partitioning Algorithm. - Mehmet Deveci; Sivasankaran Rajamanickam; Karen D. Devine; Ümit V. Çatalyürek (IEEE Trans. Parallel Distributed Syst., 2016)

Fast linear algebra-based triangle counting with KokkosKernels. - Michael M. Wolf; Mehmet Deveci; Jonathan W. Berry; Simon D. Hammond; Sivasankaran Rajamanickam (HPEC, 2017)

Performance-Portable Sparse Matrix-Matrix Multiplication for Many-Core Architectures. - Mehmet Deveci; Christian Trott; Sivasankaran Rajamanickam (IPDPS Workshops, 2017)

Partitioning Trillion-Edge Graphs in Minutes. - George M. Slota; Sivasankaran Rajamanickam; Karen D. Devine; Kamesh Madduri (IPDPS, 2017)

Order or Shuffle: Empirically Evaluating Vertex Order Impact on Parallel Graph Computations. - George M. Slota; Sivasankaran Rajamanickam; Kamesh Madduri (IPDPS Workshops, 2017)

Designing vector-friendly compact BLAS and LAPACK kernels. - Kyungjoo Kim; Timothy B. Costa; Mehmet Deveci; Andrew M. Bradley; Simon D. Hammond; Murat Efe Guney; Sarah Knepper; Shane Story; Sivasankaran Rajamanickam (SC, 2017)

Distributed Graph Layout for Scalable Small-world Network Analysis. - George M. Slota; Sivasankaran Rajamanickam; Kamesh Madduri (CoRR, 2017)

Basker: Parallel sparse LU factorization utilizing hierarchical parallelism and data layouts. - Joshua Dennis Booth; Nathan D. Ellingwood; Heidi K. Thornquist; Sivasankaran Rajamanickam (Parallel Comput., 2017)

Embedded Ensemble Propagation for Improving Performance, Portability, and Scalability of Uncertainty Quantification on Emerging Computational Architectures. - Eric T. Phipps; Marta D'Elia; H. Carter Edwards; Mark Hoemmen; Jonathan J. Hu; Sivasankaran Rajamanickam (SIAM J. Sci. Comput., 2017)

Fast Triangle Counting Using Cilk. - Abdurrahman Yasar; Sivasankaran Rajamanickam; Michael M. Wolf; Jonathan W. Berry; Ümit V. Çatalyürek (HPEC, 2018)

Tacho: Memory-Scalable Task Parallel Sparse Cholesky Factorization. - Kyungjoo Kim; H. Carter Edwards; Sivasankaran Rajamanickam (IPDPS Workshops, 2018)

Experimental Design of Work Chunking for Graph Algorithms on High Bandwidth Memory Architectures. - George M. Slota; Sivasankaran Rajamanickam (IPDPS, 2018)

Multi-threaded Sparse Matrix-Matrix Multiplication for Many-Core and GPU Architectures. - Mehmet Deveci; Christian Trott; Sivasankaran Rajamanickam (CoRR, 2018)

Sparse Matrix-Matrix Multiplication on Multilevel Memory Architectures : Algorithms and Experiments. - Mehmet Deveci; Simon D. Hammond; Michael M. Wolf; Sivasankaran Rajamanickam (CoRR, 2018)

Geometric Partitioning and Ordering Strategies for Task Mapping on Parallel Computers. - Mehmet Deveci; Karen D. Devine; Kevin T. Pedretti; Mark A. Taylor; Sivasankaran Rajamanickam; Ümit V. Çatalyürek (CoRR, 2018)

Asynchronous One-Level and Two-Level Domain Decomposition Solvers. - Christian A. Glusa; Paritosh Ramanan; Erik G. Boman; Edmond Chow; Sivasankaran Rajamanickam (CoRR, 2018)

Ensemble Grouping Strategies for Embedded Stochastic Collocation Methods Applied to Anisotropic Diffusion Problems. - Marta D'Elia; H. Carter Edwards; Jonathan J. Hu; Eric T. Phipps; Sivasankaran Rajamanickam (SIAM/ASA J. Uncertain. Quantification, 2018)

A distributed-memory hierarchical solver for general sparse linear systems. - Chao Chen 008; Hadi Pouransari; Sivasankaran Rajamanickam; Erik G. Boman; Eric Darve (Parallel Comput., 2018)

Multithreaded sparse matrix-matrix multiplication for many-core and GPU architectures. - Mehmet Deveci; Christian Trott; Sivasankaran Rajamanickam (Parallel Comput., 2018)

Scalable Triangle Counting on Distributed-Memory Systems. - Seher Acer; Abdurrahman Yasar; Sivasankaran Rajamanickam; Michael M. Wolf; Ümit V. Çatalyürek (HPEC, 2019)

Scalable Inference for Sparse Deep Neural Networks using Kokkos Kernels. - J. Austin Ellis; Sivasankaran Rajamanickam (HPEC, 2019)

Linear Algebra-Based Triangle Counting via Fine-Grained Tasking on Heterogeneous Environments : (Update on Static Graph Challenge). - Abdurrahman Yasar; Sivasankaran Rajamanickam; Jonathan W. Berry; Michael M. Wolf; Jeffrey S. Young 001; Ümit V. Çatalyürek (HPEC, 2019)

A Parallel Graph Algorithm for Detecting Mesh Singularities in Distributed Memory Ice Sheet Simulations. - Ian Bogle; Karen D. Devine; Mauro Perego; Sivasankaran Rajamanickam; George M. Slota (ICPP, 2019)

A Portable SIMD Primitive Using Kokkos for Heterogeneous Architectures. - Damodar Sahasrabudhe; Eric T. Phipps; Sivasankaran Rajamanickam; Martin Berzins (WACCPD@SC, 2019)

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 (SC, 2019)

How Robust Are Graph Neural Networks to Structural Noise? - James Fox; Sivasankaran Rajamanickam (CoRR, 2019)

A robust hierarchical solver for ill-conditioned systems with applications to ice sheet modeling. - Chao Chen 008; Léopold Cambier; Erik G. Boman; Sivasankaran Rajamanickam; Raymond S. Tuminaro; Eric Darve (J. Comput. Phys., 2019)

Geometric Mapping of Tasks to Processors on Parallel Computers with Mesh or Torus Networks. - Mehmet Deveci; Karen D. Devine; Kevin T. Pedretti; Mark A. Taylor; Sivasankaran Rajamanickam; Ümit V. Çatalyürek (IEEE Trans. Parallel Distributed Syst., 2019)

Performance Portable Supernode-based Sparse Triangular Solver for Manycore Architectures. - Ichitaro Yamazaki; Sivasankaran Rajamanickam; Nathan D. Ellingwood (ICPP, 2020)

SPHYNX: Spectral Partitioning for HYbrid aNd aXelerator-enabled systems. - Seher Acer; Erik G. Boman; Sivasankaran Rajamanickam (IPDPS Workshops, 2020)

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 (SC, 2020)

Distributed Memory Graph Coloring Algorithms for Multiple GPUs. - Ian Bogle; Erik G. Boman; Karen D. Devine; Sivasankaran Rajamanickam; George M. Slota (IA3@SC, 2020)

ADELUS: A Performance-Portable Dense LU Solver for Distributed-Memory Hardware-Accelerated Systems. - Vinh Q. Dang; Joseph D. Kotulski; Sivasankaran Rajamanickam (WACCPD@SC, 2020)

A Survey of Numerical Methods Utilizing Mixed Precision Arithmetic. - Ahmad Abdelfattah; Hartwig Anzt; Erik G. Boman; Erin C. Carson; Terry Cojean; Jack J. Dongarra; Mark Gates; Thomas Grützmacher; Nicholas J. Higham; Xiaoye Sherry Li; Neil Lindquist; Yang Liu 179; et al. (CoRR, 2020)

Accelerating Finite-temperature Kohn-Sham Density Functional Theory with Deep Neural Networks. - J. Austin Ellis; Attila Cangi; Normand A. Modine; J. Adam Stephens; Aidan P. Thompson; Sivasankaran Rajamanickam (CoRR, 2020)

An Algebraic Sparsified Nested Dissection Algorithm Using Low-Rank Approximations. - Léopold Cambier; Chao Chen 008; Erik G. Boman; Sivasankaran Rajamanickam; Raymond S. Tuminaro; Eric Darve (SIAM J. Matrix Anal. Appl., 2020)

Scalable Asynchronous Domain Decomposition Solvers. - Christian Glusa; Erik G. Boman; Edmond Chow; Sivasankaran Rajamanickam; Daniel B. Szyld (SIAM J. Sci. Comput., 2020)

Scalable, Multi-Constraint, Complex-Objective Graph Partitioning. - George M. Slota; Cameron Root; Karen D. Devine; Kamesh Madduri; Sivasankaran Rajamanickam (IEEE Trans. Parallel Distributed Syst., 2020)

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 (PACT, 2021)

Extending Sparse Tensor Accelerators to Support Multiple Compression Formats. - Eric Qin 001; Geonhwa Jeong; William Won; Sheng-Chun Kao; Hyoukjun Kwon; Sudarshan Srinivasan; Dipankar Das 002; Gordon Euhyun Moon; Sivasankaran Rajamanickam; Tushar Krishna (IPDPS, 2021)

Performance-Portable Graph Coarsening for Efficient Multilevel Graph Analysis. - Michael S. Gilbert; Seher Acer; Erik G. Boman; Kamesh Madduri; Sivasankaran Rajamanickam (IPDPS, 2021)

Experimental Evaluation of Multiprecision Strategies for GMRES on GPUs. - Jennifer A. Loe; Christian A. Glusa; Ichitaro Yamazaki; Erik G. Boman; Sivasankaran Rajamanickam (IPDPS Workshops, 2021)

A Taxonomy for Classification and Comparison of Dataflows for GNN Accelerators. - Raveesh Garg; Eric Qin 001; Francisco Muñoz-Martínez; Robert Guirado; Akshay Jain 001; Sergi Abadal; José L. Abellán; Manuel E. Acacio; Eduard Alarcón; Sivasankaran Rajamanickam; Tushar Krishna (CoRR, 2021)

Concentric Spherical GNN for 3D Representation Learning. - James Fox; Bo Zhao 028; Sivasankaran Rajamanickam; Rampi Ramprasad; Le Song (CoRR, 2021)

Kokkos Kernels: Performance Portable Sparse/Dense Linear Algebra and Graph Kernels. - Sivasankaran Rajamanickam; Seher Acer; Luc Berger-Vergiat; Vinh Q. Dang; Nathan D. Ellingwood; Evan Harvey; Brian Kelley; Christian R. Trott; Jeremiah J. Wilke; Ichitaro Yamazaki (CoRR, 2021)

Two-Stage Gauss-Seidel Preconditioners and Smoothers for Krylov Solvers on a GPU cluster. - Luc Berger-Vergiat; Brian Kelley; Sivasankaran Rajamanickam; Jonathan J. Hu; Katarzyna Swirydowicz; Paul Mullowney; Stephen J. Thomas; Ichitaro Yamazaki (CoRR, 2021)

A Study of Mixed Precision Strategies for GMRES on GPUs. - Jennifer A. Loe; Christian A. Glusa; Ichitaro Yamazaki; Erik G. Boman; Sivasankaran Rajamanickam (CoRR, 2021)

The Kokkos EcoSystem: Comprehensive Performance Portability for High Performance Computing. - Christian Trott; Luc Berger-Vergiat; David Poliakoff; Sivasankaran Rajamanickam; Damien Lebrun-Grandié; Jonathan R. Madsen; Nader Al Awar; Milos Gligoric 001; Galen M. Shipman; Geoff Womeldorff (Comput. Sci. Eng., 2021)

A survey of numerical linear algebra methods utilizing mixed-precision arithmetic. - Ahmad Abdelfattah; Hartwig Anzt; Erik G. Boman; Erin C. Carson; Terry Cojean; Jack J. Dongarra; Alyson Fox; Mark Gates; Nicholas J. Higham; Xiaoye S. Li; Jennifer A. Loe; Piotr Luszczek; et al. (Int. J. High Perform. Comput. Appl., 2021)

EXAGRAPH: Graph and combinatorial methods for enabling exascale applications. - Seher Acer; Ariful Azad; Erik G. Boman; Aydin Buluç; Karen D. Devine; S. M. Ferdous; Nitin Gawande; Sayan Ghosh; Mahantesh Halappanavar; Ananth Kalyanaraman; Arif Khan 005; Marco Minutoli; et al. (Int. J. High Perform. Comput. Appl., 2021)

Co-design Center for Exascale Machine Learning Technologies (ExaLearn). - Francis J. Alexander; James A. Ang; Jenna A. Bilbrey; Jan Balewski; Tiernan Casey; Ryan Chard; Jong Choi 001; Sutanay Choudhury; Bert J. Debusschere; Anthony M. DeGennaro; Nikoli Dryden; J. Austin Ellis; et al. (Int. J. High Perform. Comput. Appl., 2021)

Sphynx: A parallel multi-GPU graph partitioner for distributed-memory systems. - Seher Acer; Erik G. Boman; Christian A. Glusa; Sivasankaran Rajamanickam (Parallel Comput., 2021)

Partitioning Trillion-Edge Graphs. - George M. Slota; Karen D. Devine; Kamesh Madduri; Sivasankaran Rajamanickam (Massive Graph Analytics, 2022)

Multicore Algorithms for Graph Connectivity Problems. - George M. Slota; Sivasankaran Rajamanickam; Kamesh Madduri (Massive Graph Analytics, 2022)

Half-Precision Scalar Support in Kokkos and Kokkos Kernels: An Engineering Study and Experience Report. - Evan Harvey; Reed Milewicz; Christian Trott; Luc Berger-Vergiat; Siva Rajamanickam (e-Science, 2022)

Concentric Spherical Neural Network for 3D Representation Learning. - James Fox; Bo Zhao 028; Beatriz Gonzalez del Rio; Sivasankaran Rajamanickam; Rampi Ramprasad; Le Song (IJCNN, 2022)

Understanding the Design-Space of Sparse/Dense Multiphase GNN dataflows on Spatial Accelerators. - Raveesh Garg; Eric Qin 001; Francisco Muñoz-Martínez; Robert Guirado; Akshay Jain 001; Sergi Abadal; José L. Abellán; Manuel E. Acacio; Eduard Alarcón; Sivasankaran Rajamanickam; Tushar Krishna (IPDPS, 2022)

Parallel, Portable Algorithms for Distance-2 Maximal Independent Set and Graph Coarsening. - Brian Kelley; Sivasankaran Rajamanickam (IPDPS, 2022)

High-Performance GMRES Multi-Precision Benchmark: Design, Performance, and Challenges. - Ichitaro Yamazaki; Christian Glusa; Jennifer A. Loe; Piotr Luszczek; Sivasankaran Rajamanickam; Jack J. Dongarra (PMBS@SC, 2022)

Enabling Flexibility for Sparse Tensor Acceleration via Heterogeneity. - Eric Qin 001; Raveesh Garg; Abhimanyu Bambhaniya; Michael Pellauer; Angshuman Parashar; Sivasankaran Rajamanickam; Cong Hao; Tushar Krishna (CoRR, 2022)

PGAbB: A Block-Based Graph Processing Framework for Heterogeneous Platforms. - Abdurrahman Yasar; Sivasankaran Rajamanickam; Jonathan W. Berry; Ümit V. Çatalyürek (CoRR, 2022)

Parallel graph coloring algorithms for distributed GPU environments. - Ian Bogle; George M. Slota; Erik G. Boman; Karen D. Devine; Sivasankaran Rajamanickam (Parallel Comput., 2022)

FROSch Preconditioners for Land Ice Simulations of Greenland and Antarctica. - Alexander Heinlein; Mauro Perego; Sivasankaran Rajamanickam (SIAM J. Sci. Comput., 2022)

Evaluating Spatial Accelerator Architectures with Tiled Matrix-Matrix Multiplication. - Gordon Euhyun Moon; Hyoukjun Kwon; Geonhwa Jeong; Prasanth Chatarasi; Sivasankaran Rajamanickam; Tushar Krishna (IEEE Trans. Parallel Distributed Syst., 2022)

Kokkos 3: Programming Model Extensions for the Exascale Era. - Christian R. Trott; Damien Lebrun-Grandié; Daniel Arndt 003; Jan Ciesko; Vinh Q. Dang; Nathan D. Ellingwood; Rahulkumar Gayatri; Evan Harvey; Daisy S. Hollman; Dan Ibanez; Nevin Liber; Jonathan R. Madsen; et al. (IEEE Trans. Parallel Distributed Syst., 2022)

A Block-Based Triangle Counting Algorithm on Heterogeneous Environments. - Abdurrahman Yasar; Sivasankaran Rajamanickam; Jonathan W. Berry; Ümit V. Çatalyürek (IEEE Trans. Parallel Distributed Syst., 2022)

Scripts and Models for "Predicting electronic structures at any length scale with machine learning". - Lenz Fiedler; Steve Schmerler; Normand A. Modine; Dayton J. Vogel; Gabriel A. Popoola; Aidan P. Thompson; Sivasankaran Rajamanickam; Attila Cangi (RODARE, 2022)

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 (Mach. Learn. Sci. Technol., 2022)

TenSQL: An SQL Database Built on GraphBLAS. - Jon Roose; Miheer Vaidya; Ponnuswamy Sadayappan; Sivasankaran Rajamanickam (HPEC, 2023)

A Comparison of Spectral and Spatial Graph Convolutional Neural Network Kernels Using GraphSAGE-Sparse. - Michael Eydenberg; Mark Plagge; Siva Rajamanickam (IPDPS Workshops, 2023)

An Experimental Study of Two-level Schwarz Domain-Decomposition Preconditioners on GPUs. - Ichitaro Yamazaki; Alexander Heinlein; Sivasankaran Rajamanickam (IPDPS, 2023)

Exploiting Inter-Operation Data Reuse in Scientific Applications using GOGETA. - Raveesh Garg; Michael Pellauer; Sivasankaran Rajamanickam; Tushar Krishna (CoRR, 2023)

Jet: Multilevel Graph Partitioning on GPUs. - Michael S. Gilbert; Kamesh Madduri; Erik G. Boman; Sivasankaran Rajamanickam (CoRR, 2023)

Performance Portable Batched Sparse Linear Solvers. - Kim Liegeois; Sivasankaran Rajamanickam; Luc Berger-Vergiat (IEEE Trans. Parallel Distributed Syst., 2023)

Breaking the Molecular Dynamics Timescale Barrier Using a Wafer-Scale System. - Kylee Santos; Stan G. Moore; Tomas Oppelstrup; Amirali Sharifian; Ilya Sharapov; Aidan P. Thompson; Delyan Z. Kalchev; Danny Perez; Robert Schreiber; Scott Pakin; Edgar A. Leon; James H. Laros III; et al. (SC, 2024)

Breaking the mold: overcoming the time constraints of molecular dynamics on general-purpose hardware. - Danny Perez; Aidan P. Thompson; Stan G. Moore; Tomas Oppelstrup; Ilya Sharapov; Kylee Santos; Amirali Sharifian; Delyan Z. Kalchev; Robert Schreiber; Scott Pakin; Edgar A. Leon; James H. Laros III; et al. (CoRR, 2024)

Interface for Sparse Linear Algebra Operations. - Ahmad Abdelfattah; Willow Ahrens; Hartwig Anzt; Chris Armstrong; Ben Brock; Aydin Buluç; Federico Busato; Terry Cojean; Timothy A. Davis 001; Jim Demmel; Grace Dinh; David Gardener; et al. (CoRR, 2024)

Jet: Multilevel Graph Partitioning on Graphics Processing Units. - Michael S. Gilbert; Kamesh Madduri; Erik G. Boman; Siva Rajamanickam (SIAM J. Sci. Comput., 2024)

Cello: Co-Designing Schedule and Hybrid Implicit/Explicit Buffer for Complex Tensor Reuse. - Raveesh Garg; Michael Pellauer; Sivasankaran Rajamanickam; Tushar Krishna (IPDPS, 2025)

Imperfect Recognition: A Study of OCR Limitations in the Context of Scientific Documents. - Chinmay Sahasrabudhe; Yang Ho; Nick Winovich; Sivasankaran Rajamanickam (IPDPS (Workshops), 2025)

Materials Learning Algorithms (MALA): Scalable machine learning for electronic structure calculations in large-scale atomistic simulations. - Attila Cangi; Lenz Fiedler; Bartosz Brzoza; Karan Shah 001; Timothy J. Callow; Daniel Kotik; Steve Schmerler; Matthew C. Barry; James M. Goff; Andrew Rohskopf; Dayton J. Vogel; Normand A. Modine; et al. (Comput. Phys. Commun., 2025)

Trilinos: Enabling Scientific Computing Across Diverse Hardware Architectures at Scale. - Matthias Mayr; Alexander Heinlein; Christian A. Glusa; Siva Rajamanickam; Maarten Arnst; Roscoe A. Bartlett; Luc Berger-Vergiat; Erik G. Boman; Karen D. Devine; Graham Harper; Michael A. Heroux; Mark Hoemmen; et al. (CoRR, 2025)

ShyLU node: On-node Scalable Solvers and Preconditioners Recent Progresses and Current Performance. - Ichitaro Yamazaki; Nathan D. Ellingwood; Sivasankaran Rajamanickam (CoRR, 2025)

Performance Portable Gradient Computations Using Source Transformation. - Kim Liegeois; Brian Kelley; Eric T. Phipps; Sivasankaran Rajamanickam; Vassil Vassilev (CoRR, 2025)