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Graph analytics is critical to scientific computing, artificial intelligence (AI), and national-scale data analysis. This BoF gathers the community developing high-performance systems for graph processing to discuss current capabilities, emerging challenges, and integration with graph databases, AI workflows, and scientific applications. We will explore both combinatorial and algebraic approaches, including updates from the GraphBLAS community. A key focus is identifying what capabilities—such as open, scalable graph toolchains and support for irregular workloads—require federal investment beyond what commercial vendors provide. The session will guide future research, software development, and funding priorities through expert discussion and broad community input.
Organizers: Antonino Tumeo (PNNL), José Moreira (IBM), Tim Mattson (Merly.ai), John Feo (Retired), Marco MInutoli (AMD)
| Time | Event |
|---|---|
| 5:15 | Welcome Antonino Tumeo (PNNL), José Moreira (IBM), Tim Mattson (Merly.ai) |
| 5:15 - 5:45 | Applications and HPC Graph Toolkits Scalable Graph Algorithms: A Case for Memory Efficiency S.M. Ferdous (PNNL) Fantastic Graph Dynamics and Where to Find Them: How to Tame Them and When to Tame Them Arindam Khanda (Missouri University of Science and Technology) |
| 5:45 - 6:00 | GraphBLAS Updates Jose Moreira (IBM), Tim Mattson (Merly.ai) |
| 6:00 - 6:45 | The Sparse BLAS and the Sparse Matrix Ecosystem Introduction Hartwig Anzt (TU Munich) Open Discussion with the Audience Discussion leads: José Moreira (IBM) (moderator), Antonino Tumeo (PNNL), Hartwig Anzt (TU Munich), Benjamin Brock (Intel) |
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