Jennifer Ann Loe
Scalable Algorithms
Scalable Algorithms
(505) 844-8137
Sandia National Laboratories, New Mexico
P.O. Box 5800
Albuquerque, NM 87185-1327
Biography
Jennifer Loe is a Senior Member of Technical Staff at Sandia National Laboratories. She completed her Ph.D. in mathematics at Baylor University in December 2019. In January 2020, she became a postdoc in the Scalable Algorithms department at Sandia and converted to full staff in February 2022. Jennifer primarily works in numerical linear algebra, with a focus on Krylov solvers for sparse linear systems. She is a developer of the Belos package for iterative linear solvers in Trilinos and has also contributed to Kokkos Kernels. Her research interests include GMRES, polynomial preconditioning, communication-avoiding solvers, and mixed-pecision solvers. When not at work, she enjoys visiting the zoo and aquarium, speaking in Toastmasters, and volunteering for Big Brothers, Big Sisters.
Education
- Ph.D. Mathematics, Baylor University, 2020
- Advisor: Ron Morgan
- Thesis: Polynomial Preconditioning with the Minimum Residual Polynomial
- M.S. Mathematics, Baylor University, 2018
- B.S. Mathematics, Oklahoma Christian University, 2014
- Minors: Computer Science and International Studies
Publications
Jennifer Loe, Ronald Morgan, (2022). Toward efficient polynomial preconditioning for GMRES Numerical Linear Algebra with Applications https://doi.org/10.1002/nla.2427 Publication ID: 77199
Heliezer Espinoza, Jennifer Loe, Erik Boman, (2022). Randomized Cholesky Preconditioning for Graph Partitioning Applications https://doi.org/10.2172/1843910 Publication ID: 80353
Heliezer Espinoza, Jennifer Loe, Erik Boman, (2022). Randomized Cholesky Preconditioning for Graph Partitioning Applications https://doi.org/10.2172/1840649 Publication ID: 79957
Jennifer Loe, (2021). Mixed Precision Krlyov Slide for ECP Review https://www.osti.gov/servlets/purl/1900570 Publication ID: 76998
Jennifer Loe, Sivasankaran Rajamanickam, (2021). Mixed Precision in Trilinos https://doi.org/10.2172/1900352 Publication ID: 76971
Ahmad Abdelfattah, Hartwig Anzt, Alan Ayala, Erik Boman, Erin Carson, Sebastien Cayrols, Terry Cojean, Jack Dongarra, Rob Falgout, Mark Gates, Thomas Gr\”{u}tzmacher, Nicholas Higham, Scott Kruger, Sherry Li, Neil Lindquist, Yang Liu, Jennifer Loe, Pratik Nayak, Daniel Osei-Kuffuor, Sri Pranesh, Sivasankaran Rajamanickam, Tobias Ribizel, Bryce Smith, Kasia Swirydowicz, Stephen Thomas, Stanimire Tomov, Yaohung M. Tsai, Ichitaro Yamazaki, Urike Yang, (2021). Advances in Mixed Precision Algorithms: 2021 Edition https://doi.org/10.2172/1814447 Publication ID: 75285
Jennifer Loe, (2021). Using Multiple Precisions in the GMRES Linear Solver https://www.osti.gov/servlets/purl/1884904 Publication ID: 75445
Jennifer Loe, (2021). An Introduction to Trilinos https://www.osti.gov/servlets/purl/1884905 Publication ID: 75446
Jennifer Loe, Christian Glusa, Ichitaro Yamazaki, Erik Boman, Sivasankaran Rajamanickam, (2021). Properties of GMRES with Iterative Refinement on GPUs https://doi.org/10.2172/1884157 Publication ID: 79139
Jennifer Loe, Christian Glusa, Ichitaro Yamazaki, Erik Boman, Sivasankaran Rajamanickam, (2021). Experimental Evaluation of Multiprecision Strategies for GMRES on GPUs 2021 IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2021 – In conjunction with IEEE IPDPS 2021 https://doi.org/10.1109/IPDPSW52791.2021.00078 Publication ID: 77887
Jennifer Loe, Christian Glusa, Ichitaro Yamazaki, Erik Boman, Sivasankaran Rajamanickam, (2021). Experimental Evaluation of Multiprecision Strategies for GMRES on GPUs https://doi.org/10.2172/1869548 Publication ID: 78515
Jennifer Loe, Erik Boman, (2021). Polynomial Preconditioned GMRES for GPU Computing https://doi.org/10.2172/1870091 Publication ID: 78580
Jennifer Loe, Erik Boman, (2021). Polynomial Preconditioning in Trilinos https://doi.org/10.2172/1863700 Publication ID: 78096
Erik Boman, Daniel Bielich, Jennifer Loe, Ichitaro Yamazaki, (2021). PEEKS Overview https://www.osti.gov/servlets/purl/1863514 Publication ID: 78060
Jennifer Loe, (2021). Incorporating Multiple Compute Precisions into the GMRES Linear Solver https://www.osti.gov/servlets/purl/1866721 Publication ID: 78333
Hartwig Anzt, Jennifer Loe, Sivasankaran Rajamanickam, (2021). xSDK Focus Effort Developing Multiprecision Numerics https://doi.org/10.2172/1856293 Publication ID: 77691
Jennifer Loe, Christian Glusa, Ichitaro Yamazaki, Erik Boman, Sivasankaran Rajamanickam, (2021). Multiprecision Krylov Solvers in Kokkos and Belos https://doi.org/10.2172/1854310 Publication ID: 77452
MARK EMBREE, Jennifer Loe, RONALD MORGAN, (2021). Polynomial preconditioned arnoldi with stability control SIAM Journal on Scientific Computing https://doi.org/10.1137/19m1302430 Publication ID: 71029
Jennifer Loe, Sivasankaran Rajamanickam, Erik Boman, Hartwig Anzt, (2020). ECP Multiprecision Project Review Slides https://www.osti.gov/servlets/purl/1835661 Publication ID: 72171
Hartwig Antz, Erik Boman, Mark Gates, Scott Kruger, Sherry Li, Jennifer Loe, Daniel Osei-Kuffuor, Stan Tomov, Yaohung Tsai, Ulrike Meier Yang, (2020). Towards Use of Mixed Precision in ECP Math Libraries [Exascale Computing Project] https://doi.org/10.2172/1735694 Publication ID: 72172
Jennifer Loe, Christian Glusa, Ichitaro Yamazaki, Erik Boman, Sivasankaran Rajamanickam, (2020). Mixed-Precision GMRES in Trilinos https://doi.org/10.2172/1833786 Publication ID: 71988
Jennifer Loe, (2020). Linear Solvers and Computing: Behind the Scenes https://www.osti.gov/servlets/purl/1831351 Publication ID: 71733
Jennifer Loe, Christian Glusa, Erik Boman, Ichitaro Yamazaki, Sivasankaran Rajamanickam, (2020). Multiprecision Krylov Solvers in Trilinos https://www.osti.gov/servlets/purl/1829961 Publication ID: 71611
Jennifer Loe, Christian Glusa, Erik Boman, Ichitaro Yamazaki, Sivasankaran Rajamanickam, (2020). Multiprecision GMRES in Trilinos packages Belos and Kokkos https://doi.org/10.2172/1832692 Publication ID: 71889
Jennifer Loe, (2020). Jennifer Loe – Rising Stars Presentation https://doi.org/10.2172/1826444 Publication ID: 71276
Jennifer Loe, Heidi Thornquist, Erik Boman, (2020). Polynomial Preconditioned GMRES in Trilinos: Practical Considerations for High Performance Computing https://doi.org/10.1137/1.9781611976137.4 Publication ID: 72514
Jennifer Loe, Heidi Thornquist, Erik Boman, (2019). Polynomial Preconditioning for Avoiding Communication in GMRES https://www.osti.gov/servlets/purl/1641026 Publication ID: 69529
Showing Results.