L
Li Tan
Researcher at Brookhaven National Laboratory
Publications - 34
Citations - 278
Li Tan is an academic researcher from Brookhaven National Laboratory. The author has contributed to research in topics: Efficient energy use & Frequency scaling. The author has an hindex of 9, co-authored 34 publications receiving 216 citations. Previous affiliations of Li Tan include Los Alamos National Laboratory & University of California, Riverside.
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Journal ArticleDOI
A survey of power and energy efficient techniques for high performance numerical linear algebra operations
TL;DR: This paper surveys the research on saving power and energy for numerical linear algebra algorithms in high performance scientific computing on supercomputers around the world and summarizes state-of-the-art techniques for achieving power andEnergy efficiency in each category individually.
Proceedings ArticleDOI
Investigating the Interplay between Energy Efficiency and Resilience in High Performance Computing
TL;DR: This work presents an energy saving undervaluing approach that leverages the mainstream resilience techniques to tolerate the increased failures caused byUndervaluing, and demonstrates that this approach can save up to 12.1% energy compared to the baseline, and conserve up to 9.1%" more energy than a state-of-the-art DVFS solution.
Proceedings ArticleDOI
Design, Use and Evaluation of P-FSEFI: A Parallel Soft Error Fault Injection Framework for Emulating Soft Errors in Parallel Applications
Qiang Guan,Nathan BeBardeleben,Panruo Wu,Stephan Eidenbenz,Sean Blanchard,Laura Monroe,Elisabeth Baseman,Li Tan +7 more
TL;DR: A sufficiently sophisticated software fault injection framework, an application can be studied to see how it would handle many of the errors that manifest at the application level, and a developer can progressively improve the resilience at targeted locations they believe are important for their target hardware.
Posted Content
IMPECCABLE: Integrated Modeling PipelinE for COVID Cure by Assessing Better LEads
Aymen Al Saadi,Dario Alfè,Yadu Babuji,Agastya P. Bhati,Ben Blaiszik,Thomas Brettin,Kyle Chard,Ryan Chard,Peter V. Coveney,Anda Trifan,Alex Brace,Austin Clyde,Ian Foster,Tom Gibbs,Shantenu Jha,Kristopher Keipert,Thorsten Kurth,Dieter Kranzlmüller,Hyungro Lee,Zhuozhao Li,Heng Ma,Andre Merzky,Gerald Mathias,Alexander Partin,Junqi Yin,Arvind Ramanathan,Ashka Shah,Abraham C. Stern,Rick Stevens,Li Tan,Mikhail Titov,A. Tsaris,Matteo Turilli,Hubertus J. J. van Dam,Shunzhou Wan,David Wifling +35 more
TL;DR: Development and deployment of computational infrastructure at scale integrates multiple artificial intelligence and simulation-based approaches to overcome this fundamental limitation of the drug discovery process.
Posted ContentDOI
High Throughput Virtual Screening and Validation of a SARS-CoV-2 Main Protease Non-Covalent Inhibitor
Austin Clyde,Austin Clyde,Austin Clyde,Stephanie Galanie,Stephanie Galanie,Daniel W. Kneller,Daniel W. Kneller,Heng Ma,Heng Ma,Yadu Babuji,Yadu Babuji,Yadu Babuji,Ben Blaiszik,Ben Blaiszik,Ben Blaiszik,Alexander Brace,Alexander Brace,Thomas Brettin,Thomas Brettin,Kyle Chard,Ryan Chard,Ryan Chard,Ryan Chard,Leighton Coates,Leighton Coates,Ian Foster,Ian Foster,Ian Foster,Darin Hauner,Darin Hauner,Vilmos Kertesz,Vilmos Kertesz,Neeraj Kumar,Neeraj Kumar,Hyungro Lee,Hyungro Lee,Zhuozhao Li,Zhuozhao Li,Zhuozhao Li,Andre Merzky,Andre Merzky,Jurgen G. Schmidt,Jurgen G. Schmidt,Li Tan,Li Tan,Mikhail Titov,Mikhail Titov,Anda Trifan,Anda Trifan,Anda Trifan,Matteo Turilli,Matteo Turilli,Hubertus Van Dam,Hubertus Van Dam,Srinivas C. Chennubhotla,Shantenu Jha,Shantenu Jha,Shantenu Jha,Andrey Kovalevsky,Andrey Kovalevsky,Arvind Ramanathan,Arvind Ramanathan,Arvind Ramanathan,Martha S Head,Martha S Head,Rick Stevens,Rick Stevens,Rick Stevens +67 more
TL;DR: In this paper, a novel non-covalent small-molecule inhibitor, MCULE-5948770040, that binds to and inhibits the SARS-Cov-2 main protease (Mpro) by employing a scalable high throughput virtual screening (HTVS) framework and a targeted compound library of over 6.5 million molecules that could be readily ordered and purchased.