Margaret Myers

Faculty
Dr. Maggie Myers was a lecturer for the Department of Computer Science and now the Department of Statistics and Data Sciences. She taught undergraduate and graduate courses in discrete mathematics, linear algebra, probability and statistics, as well as Bayesian Statistics. Her research activities range from informal learning opportunities in mathematics education to formal derivation of linear algebra algorithms. She was a senior research scientist with the Dana Center. Her partnerships (in marriage and research) with Prof. Robert van de Geijn for decades and survived the development of several MOOCs, including Linear Algebra: Foundations to Frontiers, LAFF-On Programming for Correctness, LAFF- On Programming for High Performance and an upcoming Advanced Linear Algebra for Computation.

Research

Research Interests: 

Dr. Myers expertise, educational, and research interests fall in Informal learning opportunities, Mathematics education and curriculum development, application of Bayesian statistical methods to computer science, formal derivation of algorithms, and high performance computing.

 

Current Research: 

Current research includes applications of probability and statistical methods to scientific computing and performance.
 

Research Labs & Affiliations: 

The Science of High Performance Computing Group (shpc.ices.utexas.edu)

Select Publications

Paolo Bientinesi, John Gunnels, , Maggie Myers, Enrique Quintana-Orti, Tyler Rhodes, Field Van Zee, and Robert van de Geijn. 15 October 2011. “Deriving Linear Algebra Libraries.". Formal Aspects of Computing.

Just completed one but not yet submitted anywhere yet. 

Victor Eijkhout, Margaret Myers, John McCalpin Appearances of the Birthday Paradox in High Performance Computing.  May 2, 2019

Will have another electronic book by the beginning of June and a MOOC scheduled to open June 4. 

Robert A. van de Geijn, Margaret E. Myers, Devangi N. Parikh. LAFF-On Programming for High Performance. Electronic books of notes from Massive Open Online Course. http://ulaff.net, June 2019.

 

More recent Publications:

·      Jeho Oh, Paul Gazzillo, Don Batory and Maggie Myers. Multi-Objective Optimization of Colossal Software Product Lines. ICSE 2019 Submitted.

·      D. Batory, J. Oh, and M. Myers, “Percentile calculations for randomly searching colossal product spaces,” The University of Texas at Austin, Department of Computer Science, Tech. Rep. TR-18-05, 2018.

·      Devangi N. Parikh, Jianyu Huang, Margaret E. Myers and Robert A. van de Geijn. Learning from Optimizing Matrix-Matrix Multiplication.  EduPar-18.

·      Robert A. van de Geijn, Jianyu Huang, Margaret E. Myers, Devangi N. Parikh, Tyler M. Smith Lowering barriers into HPC through Open Education.   EduHPC-17, Nov 13, 2017.

·      J. Oh, D. Batory, M. Myers, and N. Siegmund, “Finding near-optimal configurations in product lines by random sampling,” in Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering.  ACM, 2017, pp. 61–71.

·      Maggie Myers and Robert van de Geijn.  “LAFF-On Programming for Correctness,” Massive Open Online Course.  EdX and UTX. https://www.edx.org/course/laff-programming-correctness-utaustinx-ut-p4c-14-01x. April 2017- July 2017.

·      Maggie Myers, Pierce van de Geijn, and Robert van de Geijn.  “Linear Algebra: Foundations to Frontiers.”  Electronic books of notes from Massive Open Online Course. http://www.ulaff.net/ June 2014.

Paolo Bientinesi, John A. Gunnels, Margaret E. Myers, Enrique Quintana-Orti, and Robert van de Geijn. March 2005. The Science of Deriving Dense Linear Algebra Algorithms. TOM.
Paolo Bientinesi, John Gunnels, Fred Gustavson, Greg Henry, Margaret Myers, Enrique Quintana-Orti, and Robert A. van de Geijn. 2004. Rapid Development of High-Performance Linear Algebra Libraries. PARA.
Maggie Myers, Pierce van de Geijn, and Robert van de Geijn. June 2014. Linear Algebra: Foundations to Frontiers. Electronic books of notes from Massive Open Online Course.

Awards & Honors

2015 - CNS Teaching Award