Publications
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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Fault Tolerance of MPI Applications in Exascale Systems: The ULFM Solution,”
Future Generation Computer Systems, vol. 106, pp. 467-481, May 2020.
DOI: 10.1016/j.future.2020.01.026
(2.06 MB)
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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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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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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 Generic Approach to Scheduling and Checkpointing Workflows,”
Int. Journal of High Performance Computing Applications, vol. 33, no. 6, pp. 1255-1274, 2019.
(555.01 KB)
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A Generic Approach to Scheduling and Checkpointing Workflows,”
International Journal of High Performance Computing Applications, vol. 33, issue 6, pp. 1255-1274, November 2019.
DOI: 10.1177/1094342019866891
(555.01 KB)
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Ginkgo: A High Performance Numerical Linear Algebra Library,”
Journal of Open Source Software, vol. 5, issue 52, August 2020.
DOI: 10.21105/joss.02260
(721.84 KB)
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Ginkgo - A math library designed to accelerate Exascale Computing Project science applications,”
The International Journal of High Performance Computing Applications, August 2024.
DOI: 10.1177/10943420241268323
“Ginkgo: A Modern Linear Operator Algebra Framework for High Performance Computing,”
ACM Transactions on Mathematical Software, vol. 48, issue 12, pp. 1 - 33, March 2022.
DOI: 10.1145/3480935
(4.2 MB)
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Ginkgo—A math library designed for platform portability,”
Parallel Computing, vol. 111, pp. 102902, February 2022.
DOI: 10.1016/j.parco.2022.102902
“GPU algorithms for Efficient Exascale Discretizations,”
Parallel Computing, vol. 108, pp. 102841, 2021.
DOI: 10.1016/j.parco.2021.102841
“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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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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Hardware-Counter Based Automatic Performance Analysis of Parallel Programs,”
Advances in Parallel Computing, vol. 13, Dresden, Germany, Elsevier, pp. 753-760, January 2004, 2003.
DOI: 10.1016/S0927-5452(04)80092-3
“Hierarchical QR Factorization Algorithms for Multi-core Cluster Systems,”
Parallel Computing, vol. 39, issue 4-5, pp. 212-232, May 2013.
(1.43 MB)
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Highly Scalable Self-Healing Algorithms for High Performance Scientific Computing,”
IEEE Transactions on Computers, vol. 58, issue 11, pp. 1512-1524, November 2009.
DOI: 10.1109/TC.2009.42
(1.81 MB)
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High-Performance High-Resolution Semi-Lagrangian Tracer Transport on a Sphere,”
Journal of Computational Physics, vol. 230, issue 17, pp. 6778-6799, July 2011.
DOI: 10.1016/j.jcp.2011.05.008
(1.68 MB)
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HPC Forecast: Cloudy and Uncertain,”
Communications of the ACM, vol. 66, issue 2, pp. 82 - 90, January 2023.
DOI: 10.1145/3552309
“Hybrid Multicore Cholesky Factorization with Multiple GPU Accelerators,”
IEEE Transaction on Parallel and Distributed Systems (submitted), March 2010.
(3.75 MB)
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A Hybridization Methodology for High-Performance Linear Algebra Software for GPUs,”
in GPU Computing Gems, Jade Edition, vol. 2: Elsevier, pp. 473-484, 00 2011.
“The Impact of Multicore on Computational Science Software,”
CTWatch Quarterly, vol. 3, issue 1, February 2007.
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