SIAM PP22 Minisymposium on Scalable Data Analytics on the GPU


Date
Feb 24, 2022 3:20 PM — 5:00 PM
Location
Virtual

Data analytics are an integral part of data science. The introduction of new scalable and high-performance data analytics frameworks, including the use of accelerators such as GPUs, has enabled data scientists to inspect their data and extract insights previously unattainable. In the last decade, the GPU has trailblazed this new exciting field of high-performance data analytics. This session will cover recent developments that have helped scale data analytics on the GPU to new heights. We will focus on analytics in social network analysis, bioinformatics, and cybersecurity, to name a few. We will also focus on other foundational components of scalable data analytics such as communication, data structures, algorithms, and ETL.

Organizers:

Oded Green
NVIDIA and Georgia Institute of Technology, U.S.
David A. Bader
New Jersey Institute of Technology, U.S.

Part I

February 24, 2022

  • 3:20-3:40 Graph Analytics in the Exascale Era
    Mahantesh Halappanavar, Marco Minutoli, and Sayan Ghosh, Pacific Northwest National Laboratory, U.S.; Aydin Buluc, Lawrence Berkeley National Laboratory, U.S.; Erik G. Boman, Sandia National Laboratories, U.S.; Alex Pothen, Purdue University, U.S.
  • 3:45-4:05 Inverse-Deletion BFS - Revisiting Static Graph BFS Traversals with Dynamic Graph Operations
    Oded Green, NVIDIA and Georgia Institute of Technology, U.S.
  • 4:10-4:30 Parallel Graph Algorithms by Blocks for Heterogeneous Systems
    Abdurrahman Yasar, Georgia Institute of Technology, U.S.; Siva Rajamanickam and Jonathan Berry, Sandia National Laboratories, U.S.; Umit V. Catalyurek, Georgia Institute of Technology, U.S.
  • 4:35-4:55 GPU Graph Processing using Modern C++
    Andrew Lumsdaine, University of Washington, U.S.

Part II

February 25, 2022

  • 11:10-11:30 Kernel Specialization for Faster Segmented Sort on GPUs
    Georgii Evtushenko, Nvidia Corporation, U.S.
  • 11:35-11:55 Improving the Speed and Quality of Parallel Graph Coloring
    Ghadeer Alabandi and Martin Burtscher, Texas State University, U.S.
  • 12:00-12:20 Delegate Centric Top-K Computation on GPUs
    Hang Liu, Stevens Institute of Technology, U.S.
  • 12:25-12:45 GPU Accelerated Online Search for Gravitational Waves
    Zhihui Du, New Jersey Institute of Technology, U.S.

https://meetings.siam.org/sess/dsp_programsess.cfm?SESSIONCODE=72775 https://meetings.siam.org/sess/dsp_programsess.cfm?SESSIONCODE=72776

David A. Bader
David A. Bader
Distinguished Professor and Director of the Institute for Data Science

David A. Bader is a Distinguished Professor in the Department of Computer Science at New Jersey Institute of Technology.