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Sivasankaran Rajamanickam
Siva Rajamanickam
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2020 – today
- 2024
- [j30]Michael S. Gilbert, Kamesh Madduri, Erik G. Boman, Siva Rajamanickam:
Jet: Multilevel Graph Partitioning on Graphics Processing Units. SIAM J. Sci. Comput. 46(5): 700- (2024) - [i32]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, Michael James, Sivasankaran Rajamanickam:
Breaking the Molecular Dynamics Timescale Barrier Using a Wafer-Scale System. CoRR abs/2405.07898 (2024) - 2023
- [j29]Kim Liegeois, Sivasankaran Rajamanickam, Luc Berger-Vergiat:
Performance Portable Batched Sparse Linear Solvers. IEEE Trans. Parallel Distributed Syst. 34(5): 1524-1535 (2023) - [c49]Jon Roose, Miheer Vaidya, Ponnuswamy Sadayappan, Sivasankaran Rajamanickam:
TenSQL: An SQL Database Built on GraphBLAS. HPEC 2023: 1-8 - [c48]Michael Eydenberg, Mark Plagge, Siva Rajamanickam:
A Comparison of Spectral and Spatial Graph Convolutional Neural Network Kernels Using GraphSAGE-Sparse. IPDPS Workshops 2023: 189-198 - [c47]Ichitaro Yamazaki, Alexander Heinlein, Sivasankaran Rajamanickam:
An Experimental Study of Two-level Schwarz Domain-Decomposition Preconditioners on GPUs. IPDPS 2023: 680-689 - [i31]Raveesh Garg, Michael Pellauer, Sivasankaran Rajamanickam, Tushar Krishna:
Exploiting Inter-Operation Data Reuse in Scientific Applications using GOGETA. CoRR abs/2303.11499 (2023) - [i30]Ichitaro Yamazaki, Alexander Heinlein, Sivasankaran Rajamanickam:
An Experimental Study of Two-Level Schwarz Domain Decomposition Preconditioners on GPUs. CoRR abs/2304.04876 (2023) - [i29]Michael S. Gilbert, Kamesh Madduri, Erik G. Boman, Sivasankaran Rajamanickam:
Jet: Multilevel Graph Partitioning on GPUs. CoRR abs/2304.13194 (2023) - 2022
- [j28]Lenz Fiedler, Nils Hoffmann, Parvez Mohammed, Gabriel A. Popoola, Tamar Yovell, Vladyslav Oles, J. Austin Ellis, Sivasankaran Rajamanickam, Attila Cangi:
Training-free hyperparameter optimization of neural networks for electronic structures in matter. Mach. Learn. Sci. Technol. 3(4): 45008 (2022) - [j27]Ian Bogle, George M. Slota, Erik G. Boman, Karen D. Devine, Sivasankaran Rajamanickam:
Parallel graph coloring algorithms for distributed GPU environments. Parallel Comput. 110: 102896 (2022) - [j26]Alexander Heinlein, Mauro Perego, Sivasankaran Rajamanickam:
FROSch Preconditioners for Land Ice Simulations of Greenland and Antarctica. SIAM J. Sci. Comput. 44(2): 339- (2022) - [j25]Abdurrahman Yasar, Sivasankaran Rajamanickam, Jonathan W. Berry, Ümit V. Çatalyürek:
A Block-Based Triangle Counting Algorithm on Heterogeneous Environments. IEEE Trans. Parallel Distributed Syst. 33(2): 444-458 (2022) - [j24]Christian R. Trott, Damien Lebrun-Grandié, Daniel Arndt, Jan Ciesko, Vinh Q. Dang, Nathan D. Ellingwood, Rahulkumar Gayatri, Evan Harvey, Daisy S. Hollman, Dan Ibanez, Nevin Liber, Jonathan R. Madsen, Jeff Miles, David Poliakoff, Amy Powell, Sivasankaran Rajamanickam, Mikael Simberg, Dan Sunderland, Bruno Turcksin, Jeremiah J. Wilke:
Kokkos 3: Programming Model Extensions for the Exascale Era. IEEE Trans. Parallel Distributed Syst. 33(4): 805-817 (2022) - [j23]Gordon Euhyun Moon, Hyoukjun Kwon, Geonhwa Jeong, Prasanth Chatarasi, Sivasankaran Rajamanickam, Tushar Krishna:
Evaluating Spatial Accelerator Architectures with Tiled Matrix-Matrix Multiplication. IEEE Trans. Parallel Distributed Syst. 33(4): 1002-1014 (2022) - [c46]Evan Harvey, Reed Milewicz, Christian Trott, Luc Berger-Vergiat, Siva Rajamanickam:
Half-Precision Scalar Support in Kokkos and Kokkos Kernels: An Engineering Study and Experience Report. e-Science 2022: 551-560 - [c45]James Fox, Bo Zhao, Beatriz Gonzalez del Rio, Sivasankaran Rajamanickam, Rampi Ramprasad, Le Song:
Concentric Spherical Neural Network for 3D Representation Learning. IJCNN 2022: 1-8 - [c44]Brian Kelley, Sivasankaran Rajamanickam:
Parallel, Portable Algorithms for Distance-2 Maximal Independent Set and Graph Coarsening. IPDPS 2022: 280-290 - [c43]Raveesh Garg, Eric Qin, Francisco Muñoz-Martínez, Robert Guirado, Akshay Jain, Sergi Abadal, José L. Abellán, Manuel E. Acacio, Eduard Alarcón, Sivasankaran Rajamanickam, Tushar Krishna:
Understanding the Design-Space of Sparse/Dense Multiphase GNN dataflows on Spatial Accelerators. IPDPS 2022: 571-582 - [c42]Ichitaro Yamazaki, Christian Glusa, Jennifer A. Loe, Piotr Luszczek, Sivasankaran Rajamanickam, Jack J. Dongarra:
High-Performance GMRES Multi-Precision Benchmark: Design, Performance, and Challenges. PMBS@SC 2022: 112-122 - [p2]George M. Slota, Sivasankaran Rajamanickam, Kamesh Madduri:
Multicore Algorithms for Graph Connectivity Problems. Massive Graph Analytics 2022: 63-84 - [p1]George M. Slota, Karen D. Devine, Kamesh Madduri, Sivasankaran Rajamanickam:
Partitioning Trillion-Edge Graphs. Massive Graph Analytics 2022: 223-240 - [i28]Eric Qin, Raveesh Garg, Abhimanyu Bambhaniya, Michael Pellauer, Angshuman Parashar, Sivasankaran Rajamanickam, Cong Hao, Tushar Krishna:
Enabling Flexibility for Sparse Tensor Acceleration via Heterogeneity. CoRR abs/2201.08916 (2022) - [i27]Brian Kelley, Sivasankaran Rajamanickam:
Parallel, Portable Algorithms for Distance-2 Maximal Independent Set and Graph Coarsening. CoRR abs/2204.02934 (2022) - [i26]Abdurrahman Yasar, Sivasankaran Rajamanickam, Jonathan W. Berry, Ümit V. Çatalyürek:
PGAbB: A Block-Based Graph Processing Framework for Heterogeneous Platforms. CoRR abs/2209.04541 (2022) - 2021
- [j22]Christian Trott, Luc Berger-Vergiat, David Poliakoff, Sivasankaran Rajamanickam, Damien Lebrun-Grandié, Jonathan R. Madsen, Nader Al Awar, Milos Gligoric, Galen M. Shipman, Geoff Womeldorff:
The Kokkos EcoSystem: Comprehensive Performance Portability for High Performance Computing. Comput. Sci. Eng. 23(5): 10-18 (2021) - [j21]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, Srikara Pranesh, Siva Rajamanickam, Tobias Ribizel, Barry F. Smith, Kasia Swirydowicz, Stephen J. Thomas, Stanimire Tomov, Yaohung M. Tsai, Ulrike Meier Yang:
A survey of numerical linear algebra methods utilizing mixed-precision arithmetic. Int. J. High Perform. Comput. Appl. 35(4) (2021) - [j20]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, Marco Minutoli, Alex Pothen, Sivasankaran Rajamanickam, Oguz Selvitopi, Nathan R. Tallent, Antonino Tumeo:
EXAGRAPH: Graph and combinatorial methods for enabling exascale applications. Int. J. High Perform. Comput. Appl. 35(6): 553-571 (2021) - [j19]Francis J. Alexander, James A. Ang, Jenna A. Bilbrey, Jan Balewski, Tiernan Casey, Ryan Chard, Jong Choi, Sutanay Choudhury, Bert J. Debusschere, Anthony M. DeGennaro, Nikoli Dryden, J. Austin Ellis, Ian T. Foster, Cristina Garcia-Cardona, Sayan Ghosh, Peter Harrington, Yunzhi Huang, Shantenu Jha, Travis Johnston, Ai Kagawa, Ramakrishnan Kannan, Neeraj Kumar, Zhengchun Liu, Naoya Maruyama, Satoshi Matsuoka, Erin McCarthy, Jamaludin Mohd-Yusof, Peter Nugent, Yosuke Oyama, Thomas Proffen, David Pugmire, Sivasankaran Rajamanickam, Vinay Ramakrishnaiah, Malachi Schram, Sudip K. Seal, Ganesh Sivaraman, Christine Sweeney, Li Tan, Rajeev Thakur, Brian Van Essen, Logan T. Ward, Paul M. Welch, Michael Wolf, Sotiris S. Xantheas, Kevin G. Yager, Shinjae Yoo, Byung-Jun Yoon:
Co-design Center for Exascale Machine Learning Technologies (ExaLearn). Int. J. High Perform. Comput. Appl. 35(6): 598-616 (2021) - [j18]Seher Acer, Erik G. Boman, Christian A. Glusa, Sivasankaran Rajamanickam:
Sphynx: A parallel multi-GPU graph partitioner for distributed-memory systems. Parallel Comput. 106: 102769 (2021) - [c41]Geonhwa Jeong, Gokcen Kestor, Prasanth Chatarasi, Angshuman Parashar, Po-An Tsai, Sivasankaran Rajamanickam, Roberto Gioiosa, Tushar Krishna:
Union: A Unified HW-SW Co-Design Ecosystem in MLIR for Evaluating Tensor Operations on Spatial Accelerators. PACT 2021: 30-44 - [c40]Michael S. Gilbert, Seher Acer, Erik G. Boman, Kamesh Madduri, Sivasankaran Rajamanickam:
Performance-Portable Graph Coarsening for Efficient Multilevel Graph Analysis. IPDPS 2021: 213-222 - [c39]Jennifer A. Loe, Christian A. Glusa, Ichitaro Yamazaki, Erik G. Boman, Sivasankaran Rajamanickam:
Experimental Evaluation of Multiprecision Strategies for GMRES on GPUs. IPDPS Workshops 2021: 469-478 - [c38]Eric Qin, Geonhwa Jeong, William Won, Sheng-Chun Kao, Hyoukjun Kwon, Sudarshan Srinivasan, Dipankar Das, Gordon Euhyun Moon, Sivasankaran Rajamanickam, Tushar Krishna:
Extending Sparse Tensor Accelerators to Support Multiple Compression Formats. IPDPS 2021: 1014-1024 - [i25]Raveesh Garg, Eric Qin, Francisco Muñoz-Martínez, Robert Guirado, Akshay Jain, Sergi Abadal, José L. Abellán, Manuel E. Acacio, Eduard Alarcón, Sivasankaran Rajamanickam, Tushar Krishna:
A Taxonomy for Classification and Comparison of Dataflows for GNN Accelerators. CoRR abs/2103.07977 (2021) - [i24]Eric Qin, Geonhwa Jeong, William Won, Sheng-Chun Kao, Hyoukjun Kwon, Sudarshan Srinivasan, Dipankar Das, Gordon Euhyun Moon, Sivasankaran Rajamanickam, Tushar Krishna:
Extending Sparse Tensor Accelerators to Support Multiple Compression Formats. CoRR abs/2103.10452 (2021) - [i23]James Fox, Bo Zhao, Sivasankaran Rajamanickam, Rampi Ramprasad, Le Song:
Concentric Spherical GNN for 3D Representation Learning. CoRR abs/2103.10484 (2021) - [i22]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:
Kokkos Kernels: Performance Portable Sparse/Dense Linear Algebra and Graph Kernels. CoRR abs/2103.11991 (2021) - [i21]Luc Berger-Vergiat, Brian Kelley, Sivasankaran Rajamanickam, Jonathan J. Hu, Katarzyna Swirydowicz, Paul Mullowney, Stephen J. Thomas, Ichitaro Yamazaki:
Two-Stage Gauss-Seidel Preconditioners and Smoothers for Krylov Solvers on a GPU cluster. CoRR abs/2104.01196 (2021) - [i20]Seher Acer, Erik G. Boman, Christian A. Glusa, Sivasankaran Rajamanickam:
Sphynx: a parallel multi-GPU graph partitioner for distributed-memory systems. CoRR abs/2105.00578 (2021) - [i19]Jennifer A. Loe, Christian A. Glusa, Ichitaro Yamazaki, Erik G. Boman, Sivasankaran Rajamanickam:
Experimental Evaluation of Multiprecision Strategies for GMRES on GPUs. CoRR abs/2105.07544 (2021) - [i18]Gordon Euhyun Moon, Hyoukjun Kwon, Geonhwa Jeong, Prasanth Chatarasi, Sivasankaran Rajamanickam, Tushar Krishna:
Evaluating Spatial Accelerator Architectures with Tiled Matrix-Matrix Multiplication. CoRR abs/2106.10499 (2021) - [i17]Ian Bogle, Erik G. Boman, Karen D. Devine, Sivasankaran Rajamanickam, George M. Slota:
Parallel Graph Coloring Algorithms for Distributed GPU Environments. CoRR abs/2107.00075 (2021) - [i16]Jennifer A. Loe, Christian A. Glusa, Ichitaro Yamazaki, Erik G. Boman, Sivasankaran Rajamanickam:
A Study of Mixed Precision Strategies for GMRES on GPUs. CoRR abs/2109.01232 (2021) - [i15]Geonhwa Jeong, Gokcen Kestor, Prasanth Chatarasi, Angshuman Parashar, Po-An Tsai, Sivasankaran Rajamanickam, Roberto Gioiosa, Tushar Krishna:
Union: A Unified HW-SW Co-Design Ecosystem in MLIR for Evaluating Tensor Operations on Spatial Accelerators. CoRR abs/2109.07419 (2021) - 2020
- [j17]Léopold Cambier, Chao Chen, Erik G. Boman, Sivasankaran Rajamanickam, Raymond S. Tuminaro, Eric Darve:
An Algebraic Sparsified Nested Dissection Algorithm Using Low-Rank Approximations. SIAM J. Matrix Anal. Appl. 41(2): 715-746 (2020) - [j16]Christian Glusa, Erik G. Boman, Edmond Chow, Sivasankaran Rajamanickam, Daniel B. Szyld:
Scalable Asynchronous Domain Decomposition Solvers. SIAM J. Sci. Comput. 42(6): C384-C409 (2020) - [j15]George M. Slota, Cameron Root, Karen D. Devine, Kamesh Madduri, Sivasankaran Rajamanickam:
Scalable, Multi-Constraint, Complex-Objective Graph Partitioning. IEEE Trans. Parallel Distributed Syst. 31(12): 2789-2801 (2020) - [c37]Ichitaro Yamazaki, Sivasankaran Rajamanickam, Nathan D. Ellingwood:
Performance Portable Supernode-based Sparse Triangular Solver for Manycore Architectures. ICPP 2020: 70:1-70:11 - [c36]Seher Acer, Erik G. Boman, Sivasankaran Rajamanickam:
SPHYNX: Spectral Partitioning for HYbrid aNd aXelerator-enabled systems. IPDPS Workshops 2020: 440-449 - [c35]Ian Bogle, Erik G. Boman, Karen D. Devine, Sivasankaran Rajamanickam, George M. Slota:
Distributed Memory Graph Coloring Algorithms for Multiple GPUs. IA3@SC 2020: 54-62 - [c34]Vinh Q. Dang, Joseph D. Kotulski, Sivasankaran Rajamanickam:
ADELUS: A Performance-Portable Dense LU Solver for Distributed-Memory Hardware-Accelerated Systems. WACCPD@SC 2020: 80-101 - [c33]Luca Bertagna, Oksana Guba, Mark A. Taylor, James G. Foucar, Jeff Larkin, Andrew M. Bradley, Sivasankaran Rajamanickam, Andrew G. Salinger:
A performance-portable nonhydrostatic atmospheric dycore for the energy exascale earth system model running at cloud-resolving resolutions. SC 2020: 92 - [e1]H. Martin Bücker, Xiaoye Sherry Li, Sivasankaran Rajamanickam:
Proceedings of the SIAM Workshop on Combinatorial Scientific Computing, CSC 2020, Seattle, USA, February 11-13, 2020. SIAM 2020, ISBN 978-1-61197-622-9 [contents] - [i14]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, Jennifer A. Loe, Piotr Luszczek, Pratik Nayak, Srikara Pranesh, Sivasankaran Rajamanickam, Tobias Ribizel, Barry Smith, Kasia Swirydowicz, Stephen J. Thomas, Stanimire Tomov, Yaohung M. Tsai, Ichitaro Yamazaki, Ulrike Meier Yang:
A Survey of Numerical Methods Utilizing Mixed Precision Arithmetic. CoRR abs/2007.06674 (2020) - [i13]Abdurrahman Yasar, Sivasankaran Rajamanickam, Jonathan W. Berry, Ümit V. Çatalyürek:
A Block-Based Triangle Counting Algorithm on Heterogeneous Environments. CoRR abs/2009.12457 (2020) - [i12]J. Austin Ellis, Attila Cangi, Normand A. Modine, J. Adam Stephens, Aidan P. Thompson, Sivasankaran Rajamanickam:
Accelerating Finite-temperature Kohn-Sham Density Functional Theory with Deep Neural Networks. CoRR abs/2010.04905 (2020)
2010 – 2019
- 2019
- [j14]Chao Chen, Léopold Cambier, Erik G. Boman, Sivasankaran Rajamanickam, Raymond S. Tuminaro, Eric Darve:
A robust hierarchical solver for ill-conditioned systems with applications to ice sheet modeling. J. Comput. Phys. 396: 819-836 (2019) - [j13]Mehmet Deveci, Karen D. Devine, Kevin T. Pedretti, Mark A. Taylor, Sivasankaran Rajamanickam, Ümit V. Çatalyürek:
Geometric Mapping of Tasks to Processors on Parallel Computers with Mesh or Torus Networks. IEEE Trans. Parallel Distributed Syst. 30(9): 2018-2032 (2019) - [c32]Seher Acer, Abdurrahman Yasar, Sivasankaran Rajamanickam, Michael M. Wolf, Ümit V. Çatalyürek:
Scalable Triangle Counting on Distributed-Memory Systems. HPEC 2019: 1-5 - [c31]J. Austin Ellis, Sivasankaran Rajamanickam:
Scalable Inference for Sparse Deep Neural Networks using Kokkos Kernels. HPEC 2019: 1-7 - [c30]Abdurrahman Yasar, Sivasankaran Rajamanickam, Jonathan W. Berry, Michael M. Wolf, Jeffrey S. Young, Ümit V. Çatalyürek:
Linear Algebra-Based Triangle Counting via Fine-Grained Tasking on Heterogeneous Environments : (Update on Static Graph Challenge). HPEC 2019: 1-4 - [c29]Ian Bogle, Karen D. Devine, Mauro Perego, Sivasankaran Rajamanickam, George M. Slota:
A Parallel Graph Algorithm for Detecting Mesh Singularities in Distributed Memory Ice Sheet Simulations. ICPP 2019: 1:1-1:10 - [c28]George M. Slota, Jonathan W. Berry, Simon D. Hammond, Stephen L. Olivier, Cynthia A. Phillips, Sivasankaran Rajamanickam:
Scalable generation of graphs for benchmarking HPC community-detection algorithms. SC 2019: 73:1-73:14 - [c27]Damodar Sahasrabudhe, Eric T. Phipps, Sivasankaran Rajamanickam, Martin Berzins:
A Portable SIMD Primitive Using Kokkos for Heterogeneous Architectures. WACCPD@SC 2019: 140-163 - [i11]James Fox, Sivasankaran Rajamanickam:
How Robust Are Graph Neural Networks to Structural Noise? CoRR abs/1912.10206 (2019) - 2018
- [j12]Marta D'Elia, H. Carter Edwards, Jonathan J. Hu, Eric T. Phipps, Sivasankaran Rajamanickam:
Ensemble Grouping Strategies for Embedded Stochastic Collocation Methods Applied to Anisotropic Diffusion Problems. SIAM/ASA J. Uncertain. Quantification 6(1): 87-117 (2018) - [j11]Chao Chen, Hadi Pouransari, Sivasankaran Rajamanickam, Erik G. Boman, Eric Darve:
A distributed-memory hierarchical solver for general sparse linear systems. Parallel Comput. 74: 49-64 (2018) - [j10]Mehmet Deveci, Christian Trott, Sivasankaran Rajamanickam:
Multithreaded sparse matrix-matrix multiplication for many-core and GPU architectures. Parallel Comput. 78: 33-46 (2018) - [c26]Abdurrahman Yasar, Sivasankaran Rajamanickam, Michael M. Wolf, Jonathan W. Berry, Ümit V. Çatalyürek:
Fast Triangle Counting Using Cilk. HPEC 2018: 1-7 - [c25]Kyungjoo Kim, H. Carter Edwards, Sivasankaran Rajamanickam:
Tacho: Memory-Scalable Task Parallel Sparse Cholesky Factorization. IPDPS Workshops 2018: 550-559 - [c24]George M. Slota, Sivasankaran Rajamanickam:
Experimental Design of Work Chunking for Graph Algorithms on High Bandwidth Memory Architectures. IPDPS 2018: 875-884 - [i10]Mehmet Deveci, Christian Trott, Sivasankaran Rajamanickam:
Multi-threaded Sparse Matrix-Matrix Multiplication for Many-Core and GPU Architectures. CoRR abs/1801.03065 (2018) - [i9]Mehmet Deveci, Simon D. Hammond, Michael M. Wolf, Sivasankaran Rajamanickam:
Sparse Matrix-Matrix Multiplication on Multilevel Memory Architectures : Algorithms and Experiments. CoRR abs/1804.00695 (2018) - [i8]Mehmet Deveci, Karen D. Devine, Kevin T. Pedretti, Mark A. Taylor, Sivasankaran Rajamanickam, Ümit V. Çatalyürek:
Geometric Partitioning and Ordering Strategies for Task Mapping on Parallel Computers. CoRR abs/1804.09798 (2018) - [i7]Christian A. Glusa, Paritosh Ramanan, Erik G. Boman, Edmond Chow, Sivasankaran Rajamanickam:
Asynchronous One-Level and Two-Level Domain Decomposition Solvers. CoRR abs/1808.08172 (2018) - 2017
- [j9]Joshua Dennis Booth, Nathan D. Ellingwood, Heidi K. Thornquist, Sivasankaran Rajamanickam:
Basker: Parallel sparse LU factorization utilizing hierarchical parallelism and data layouts. Parallel Comput. 68: 17-31 (2017) - [j8]Eric T. Phipps, Marta D'Elia, H. Carter Edwards, Mark Hoemmen, Jonathan J. Hu, Sivasankaran Rajamanickam:
Embedded Ensemble Propagation for Improving Performance, Portability, and Scalability of Uncertainty Quantification on Emerging Computational Architectures. SIAM J. Sci. Comput. 39(2) (2017) - [c23]Michael M. Wolf, Mehmet Deveci, Jonathan W. Berry, Simon D. Hammond, Sivasankaran Rajamanickam:
Fast linear algebra-based triangle counting with KokkosKernels. HPEC 2017: 1-7 - [c22]George M. Slota, Sivasankaran Rajamanickam, Kamesh Madduri:
Order or Shuffle: Empirically Evaluating Vertex Order Impact on Parallel Graph Computations. IPDPS Workshops 2017: 588-597 - [c21]George M. Slota, Sivasankaran Rajamanickam, Karen D. Devine, Kamesh Madduri:
Partitioning Trillion-Edge Graphs in Minutes. IPDPS 2017: 646-655 - [c20]Mehmet Deveci, Christian Trott, Sivasankaran Rajamanickam:
Performance-Portable Sparse Matrix-Matrix Multiplication for Many-Core Architectures. IPDPS Workshops 2017: 693-702 - [c19]Kyungjoo Kim, Timothy B. Costa, Mehmet Deveci, Andrew M. Bradley, Simon D. Hammond, Murat Efe Guney, Sarah Knepper, Shane Story, Sivasankaran Rajamanickam:
Designing vector-friendly compact BLAS and LAPACK kernels. SC 2017: 55 - [i6]George M. Slota, Sivasankaran Rajamanickam, Kamesh Madduri:
Distributed Graph Layout for Scalable Small-world Network Analysis. CoRR abs/1701.00503 (2017) - [i5]Chao Chen, Hadi Pouransari, Sivasankaran Rajamanickam, Erik G. Boman, Eric Darve:
A distributed-memory hierarchical solver for general sparse linear systems. CoRR abs/1712.07297 (2017) - 2016
- [j7]Timothy A. Davis, Sivasankaran Rajamanickam, Wissam M. Sid-Lakhdar:
A survey of direct methods for sparse linear systems. Acta Numer. 25: 383-566 (2016) - [j6]George M. Slota, Kamesh Madduri, Sivasankaran Rajamanickam:
Complex Network Partitioning Using Label Propagation. SIAM J. Sci. Comput. 38(5) (2016) - [j5]Mehmet Deveci, Sivasankaran Rajamanickam, Karen D. Devine, Ümit V. Çatalyürek:
Multi-Jagged: A Scalable Parallel Spatial Partitioning Algorithm. IEEE Trans. Parallel Distributed Syst. 27(3): 803-817 (2016) - [c18]George M. Slota, Sivasankaran Rajamanickam, Kamesh Madduri:
A Case Study of Complex Graph Analysis in Distributed Memory: Implementation and Optimization. IPDPS 2016: 293-302 - [c17]Joshua Dennis Booth, Kyungjoo Kim, Sivasankaran Rajamanickam:
A Comparison of High-Level Programming Choices for Incomplete Sparse Factorization Across Different Architectures. IPDPS Workshops 2016: 397-406 - [c16]Joshua Dennis Booth, Sivasankaran Rajamanickam, Heidi Thornquist:
Basker: A Threaded Sparse LU Factorization Utilizing Hierarchical Parallelism and Data Layouts. IPDPS Workshops 2016: 673-682 - [c15]Mehmet Deveci, Erik G. Boman, Karen D. Devine, Sivasankaran Rajamanickam:
Parallel Graph Coloring for Manycore Architectures. IPDPS 2016: 892-901 - [i4]Joshua Dennis Booth, Sivasankaran Rajamanickam, Heidi K. Thornquist:
Basker: A Threaded Sparse LU Factorization Utilizing Hierarchical Parallelism and Data Layouts. CoRR abs/1601.05725 (2016) - [i3]Kyungjoo Kim, Sivasankaran Rajamanickam, George Stelle, H. Carter Edwards, Stephen L. Olivier:
Task Parallel Incomplete Cholesky Factorization using 2D Partitioned-Block Layout. CoRR abs/1601.05871 (2016) - [i2]George M. Slota, Sivasankaran Rajamanickam, Karen D. Devine, Kamesh Madduri:
Partitioning Trillion-edge Graphs in Minutes. CoRR abs/1610.07220 (2016) - 2015
- [c14]George M. Slota, Sivasankaran Rajamanickam, Kamesh Madduri:
High-Performance Graph Analytics on Manycore Processors. IPDPS 2015: 17-27 - [i1]Eric T. Phipps, Marta D'Elia, H. Carter Edwards, Mark Hoemmen, Jonathan J. Hu, Sivasankaran Rajamanickam:
Embedded Ensemble Propagation for Improving Performance, Portability and Scalability of Uncertainty Quantification on Emerging Computational Architectures. CoRR abs/1511.03703 (2015) - 2014
- [j4]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:
Towards Extreme-Scale Simulations for Low Mach Fluids with Second-Generation Trilinos. Parallel Process. Lett. 24(4) (2014) - [c13]George M. Slota, Kamesh Madduri, Sivasankaran Rajamanickam:
PuLP: Scalable multi-objective multi-constraint partitioning for small-world networks. IEEE BigData 2014: 481-490 - [c12]Vladimir Ufimtsev, Sanjukta Bhowmick, Sivasankaran Rajamanickam:
Building blocks for graph based network analysis. HPEC 2014: 1-6 - [c11]Mehmet Deveci, Sivasankaran Rajamanickam, Vitus J. Leung, Kevin T. Pedretti, Stephen L. Olivier, David P. Bunde, Ümit V. Çatalyürek, Karen D. Devine:
Exploiting Geometric Partitioning in Task Mapping for Parallel Computers. IPDPS 2014: 27-36 - [c10]George M. Slota, Sivasankaran Rajamanickam, Kamesh Madduri:
BFS and Coloring-Based Parallel Algorithms for Strongly Connected Components and Related Problems. IPDPS 2014: 550-559 - [c9]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:
Towards Extreme-Scale Simulations with Next-Generation Trilinos: A Low Mach Fluid Application Case Study. IPDPS Workshops 2014: 1485-1494 - [c8]Ichitaro Yamazaki, Sivasankaran Rajamanickam, Erik G. Boman, Mark Hoemmen, Michael A. Heroux, Stanimire Tomov:
Domain Decomposition Preconditioners for Communication-Avoiding Krylov Methods on a Hybrid CPU/GPU Cluster. SC 2014: 933-944 - [c7]Heidi K. Thornquist, Sivasankaran Rajamanickam:
A Hybrid Approach for Parallel Transistor-Level Full-Chip Circuit Simulation. VECPAR 2014: 102-111 - 2013
- [j3]Heidi Thornquist, Eric R. Keiter, Sivasankaran Rajamanickam:
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