The award was announced at the 2021 International Conference for High Performance Computing, Networking, Storage and Analysis (SC21) in St. Louis, Missouri on Nov. 16.
Over the course of her career, Taylor has developed and used models to analyze and improve the performance of many parallel scientific applications, including molecular dynamics, cosmology, earthquake simulations, ocean modeling, and magnetic fusion. She is well known for her development of Prophesy, one of the first tools to include a database for the archival of application execution information combined with model generation. With Prophesy, users can easily analyze application performance across multiple architectures and predict performance on new architectures. Taylor also leveraged this work to lead the design of another infrastructure, called MuMMI, which explores the trade-offs of performance and power requirements of large-scale, parallel applications.
Taylor received her Ph.D. in electrical engineering and computer science from the University of California, Berkeley, in 1991. She then joined the Electrical Engineering and Computer Science department at Northwestern University, where she was a member of the faculty for 11 years. In 2003 she joined Texas A&M, where she served as head of the computer science and engineering department and senior associate dean of academic affairs in the College of Engineering and was a Regents Professor and the Royce E. Wisenbaker Professor in the Department of Computer Science. In 2017 she joined Argonne as director of the MCS division. Taylor is an Argonne Distinguished Fellow and a Fellow of both the Institute of Electrical and Electronics Engineers and the Association for Computing Machinery.
“I am honored to receive this award from HPCwire,” said Taylor. “I have been fortunate to work with a superb community of computer scientists, applied mathematicians, computational scientists, and domain scientists as we have sought – and continue to seek – ways to exploit the capabilities of high-performance computing to solve important scientific problems. I look forward future HPC systems to advance the use of automation as well as AI/ML for scientific discovery.”
The HPCwire Readers’ and Editors’ Choice Awards are determined by a nomination and voting process involving the global HPCwire reader community. The annual awards recognize outstanding individuals, organizations, products and technologies in the high-performance computing field. For this year’s winners, see the HPCwire website: https://www.hpcwire.com/off-the-wire/hpcwire-reveals-winners-of-the-202…