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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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Atlanta, GA | Posted: March 28, 2019
Kristen Perez
Communications Officer
Summary Sentence:
David Bader was recognized as the author of a most impactful paper in the HiPC conference history.
Full Summary:
No summary paragraph submitted.
David Bader Horizontal HeadshotSchool of Computational Science and Engineering Chair David Bader is being recognized as one of the most impactful authors in the history of the IEEE International Conference on High-Performance Computing, Data, and Analytics (HiPC) conference series.
As part of its 25th anniversary celebration, a HiPC committee reviewed all of the top-ranked paper submissions accepted by the conference during the past 25 years. “The committee voted and identified the seven most impactful papers,” said HiPC Steering Chair Viktor Prasanna.
Bader’s winning paper, Design and Implementation of the HPCS Graph Analysis Benchmark on Symmetric Multiprocessors, was published at HiPC in 2005.
In the paper, Bader and Pennsylvania State University Associate Professor Kamesh Madduri, presented the design and implementation of a graph theory application that supports a synthetic benchmark suite dubbed the Scalable Synthetic Compact Applications (SSCA). This seminal paper is often cited as the earliest data science benchmark on scalable graph analysis.
The SSCA suite was developed under the Defense Advanced Research Projects Agency High Productivity Computing Systems (HPCS) program to reassess the way performance, programmability, portability, robustness, and productivity are defined and measured in high-performance computing domains.
“These benchmarks represent important computational and data science kernels in solving real-world problems. This research has stood the test of time and accelerated the design of high-performance computers capable of solving today’s grand challenges in machine learning, healthcare informatics, and national security,” said Bader.
