Login to the D&D KM-IT.

Not a registered user? click here for U.S. registration or here for international registration.      Forgot your password? Click here

User name:   Password:   Close

Search the D&D KM-IT

Welcome Guest
Try our mobile friendly tool.

Share page:  

printer friendly logo

Tech Talk
Graph Analytics on Exascale Systems
January 21, 2025 @ 2 pm

KM-IT Tech Talk - Graph Analytics on Exascale Systems

Florida International University (FIU) is conducting a series of Tech Talks focusing on D&D topics relevant to the DOE EM Complex. On January 21, 2025, FIU collaborated with Pacific Northwest National Laboratory (PNNL) to feature a Tech Talk from Dr. Mahantesh Halappanavar titled “Graph Analytics on Exascale Systems”. This talk surveyed the algorithmic and software development activities performed under the auspices of ExaGraph.

Abstract

Combinatorial algorithms in general and graph algorithms in particular play a critical enabling role in numerous scientific applications. However, the irregular memory access nature of these algorithms makes them one of the hardest algorithmic kernels to implement on parallel systems. With tens of billions of hardware threads and deep memory hierarchies, the exascale computing systems in particular pose extreme challenges in scaling graph algorithms. The codesign center on combinatorial algorithms, ExaGraph, was established to design and develop methods and techniques for efficient implementation of key combinatorial (graph) algorithms chosen from a diverse set of exascale applications. Algebraic and combinatorial methods have a complementary role in the advancement of computational science and engineering, including playing an enabling role on each other. In this presentation, we survey the algorithmic and software development activities performed under the auspices of ExaGraph and detail experimental results from GPU-accelerated pre-exascale and exascale systems.

Flyer    Presentation    Feedback Form    Newsletter Signup

 

Video Archive


Speaker

Dr. Mahantesh Halappanavar

Dr. Mahantesh Halappanavar


Chief Data Scientist
Data Sciences & Machine Intelligence Group
hala@pnnl.gov

Dr. Halappanavar is a chief data scientist at PNNL, where he also serves as the group leader of the Data Science and Machine Intelligence group. He holds a joint appointment as adjunct faculty in computer science at the School of Electrical Engineering and Computer Science at Washington State University in Pullman. His research has spanned multiple technical foci and includes combinatorial scientific computing, parallel graph algorithms, artificial intelligence and machine learning, and the application of graph theory, game theory and machine learning to solve problems in application domains such as scientific computing, cybersecurity, power grids, and life sciences. He co-authored a book on design of parallel graph algorithms on shared-memory architectures and has authored over 145 technical publications for peer-reviewed journals, conferences, and workshops. He is a member of the Society for Industrial and Applied Mathematics (SIAM), and a senior member of the Association for Computing Machinery (ACM) and the Institute of Electrical and Electronics Engineers (IEEE).


Joining the meeting instructions

This event is being hosted using Microsoft Teams. It is required for every attendee to have this app installed on their desktop or mobile device. You can download this app from the following link or use the links of the sidebar for mobile devices.

https://www.microsoft.com/en-us/microsoft-365/microsoft-teams/download-app

This event is sponsored by The U.S. Department of Energy



Back to Top
More Modules

Download Original    Management of D&D of Oak Ridge Building 3505 | After

Pre cache