Publications
A Guide for Achieving High Performance with Very Small Matrices on GPUs: A Case Study of Batched LU and Cholesky Factorizations,”
IEEE Transactions on Parallel and Distributed Systems, vol. 29, issue 5, pp. 973–984, May 2018.
DOI: 10.1109/TPDS.2017.2783929
(832.92 KB)
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GPU-Accelerated Asynchronous Error Correction for Mixed Precision Iterative Refinement,”
EuroPar 2012 (also LAWN 260), Rhodes Island, Greece, August 2012.
(662.98 KB)
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From CUDA to OpenCL: Towards a Performance-portable Solution for Multi-platform GPU Programming,”
Parallel Computing, vol. 38, no. 8, pp. 391-407, August 2012.
(1.64 MB)
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A Framework for Out of Memory SVD Algorithms,”
ISC High Performance 2017, pp. 158–178, June 2017.
DOI: 10.1007/978-3-319-58667-0_9
(393.22 KB)
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Fine-grained Bit-Flip Protection for Relaxation Methods,”
Journal of Computational Science, November 2016.
DOI: 10.1016/j.jocs.2016.11.013
(1.47 MB)
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Fast Cholesky Factorization on GPUs for Batch and Native Modes in MAGMA,”
Journal of Computational Science, vol. 20, pp. 85–93, May 2017.
DOI: 10.1016/j.jocs.2016.12.009
(3.6 MB)
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A Failure Detector for HPC Platforms,”
The International Journal of High Performance Computing Applications, vol. 32, issue 1, pp. 139–158, January 2018.
DOI: 10.1177/1094342017711505
(1.04 MB)
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Factorization and Inversion of a Million Matrices using GPUs: Challenges and Countermeasures,”
Procedia Computer Science, vol. 108, pp. 606–615, June 2017.
DOI: 10.1016/j.procs.2017.05.250
(643.44 KB)
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Exploiting Block Structures of KKT Matrices for Efficient Solution of Convex Optimization Problems,”
IEEE Access, 2021.
DOI: 10.1109/ACCESS.2021.3106054
(1.35 MB)
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Evaluation of Directive-Based Performance Portable Programming Models,”
International Journal of High Performance Computing and Networking, vol. 14, issue 2, pp. 165-182.
DOI: http://dx.doi.org/10.1504/IJHPCN.2017.10009064
(1.12 MB)
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Evaluation of Dataflow Programming Models for Electronic Structure Theory,”
Concurrency and Computation: Practice and Experience: Special Issue on Parallel and Distributed Algorithms, vol. 2018, issue e4490, pp. 1–20, May 2018.
DOI: 10.1002/cpe.4490
(1.69 MB)
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Evaluating Data Redistribution in PaRSEC,”
IEEE Transactions on Parallel and Distributed Systems, vol. 33, no. 8, pp. 1856-1872, August 2022.
DOI: 10.1109/TPDS.2021.3131657
(3.19 MB)
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Enhancing Parallelism of Tile QR Factorization for Multicore Architectures,”
Submitted to Transaction on Parallel and Distributed Systems, December 2009.
(464.23 KB)
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Efficient exascale discretizations: High-order finite element methods,”
The International Journal of High Performance Computing Applications, pp. 10943420211020803, 2021.
DOI: 10.1177/10943420211020803
“An Efficient Distributed Randomized Algorithm for Solving Large Dense Symmetric Indefinite Linear Systems,”
Parallel Computing, vol. 40, issue 7, pp. 213-223, July 2014.
DOI: 10.1016/j.parco.2013.12.003
(1.42 MB)
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Divide & Conquer on Hybrid GPU-Accelerated Multicore Systems,”
SIAM Journal on Scientific Computing (submitted), August 2010.
“Divide and Conquer on Hybrid GPU-Accelerated Multicore Systems,”
SIAM Journal on Scientific Computing, vol. 34(2), pp. C70-C82, April 2012.
“Distributed-Memory Lattice H-Matrix Factorization,”
The International Journal of High Performance Computing Applications, vol. 33, issue 5, pp. 1046–1063, August 2019.
DOI: 10.1177/1094342019861139
(1.14 MB)
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Design and Implementation of the PULSAR Programming System for Large Scale Computing,”
Supercomputing Frontiers and Innovations, vol. 4, issue 1, 2017.
DOI: 10.14529/jsfi170101
(764.96 KB)
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Dense Linear Algebra on Distributed Heterogeneous Hardware with a Symbolic DAG Approach,”
Scalable Computing and Communications: Theory and Practice: John Wiley & Sons, pp. 699-735, March 2013.
(1.01 MB)
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DAGuE: A generic distributed DAG Engine for High Performance Computing.,”
Parallel Computing, vol. 38, no. 1-2: Elsevier, pp. 27-51, 00 2012.
(830.85 KB)
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