Boston Chapter of the IEEE Computer Society, GBC/ACM and MIT Student Chapter of SIAM (Society for Industrial and Applied Mathematics)
7:00 PM, Thursday, 13 November 2025
MIT Room 32-G449 (Kiva) and online via Zoom
Easy Acceleration with Distributed Arrays on the World’s Largest Interactive AI Supercomputer
Jeremy Kepner
Please register in advance for this seminar even if you plan to attend in person at
https://acm-org.zoom.us/webinar/register/9817607392710/WN_lYs4lxKfSlGkMV... [1]
After registering, you will receive a confirmation email containing information about joining the webinar.
Indicate on the registration form if you plan to attend in person. This will help us determine whether the room is close to reaching capacity. We plan to serve light refreshments (probably pizza) before the talk starting at around 6:30 pm. Letting us know you will come in person will help us determine how much pizza to order.
We may make some auxiliary material such as slides and access to the recording available after the seminar to people who have registered.
Abstract:
High level programming languages and GPU accelerators are powerful enablers for a wide range of applications. Achieving scalable vertical (within a compute node), horizontal (across compute nodes), and temporal (over different generations of hardware) performance while retaining productivity requires effective abstractions. Distributed arrays are one such abstraction that enables high level programming to achieve highly scalable performance. Distributed arrays achieve this performance by deriving parallelism from data locality, which naturally leads to high memory bandwidth efficiency. This talk explores distributed array performance on a variety of hardware. Scalable performance is demonstrated within and across CPU cores, CPU nodes, and GPU nodes. The interactive AI supercomputing hardware used spans decades and allows a direct comparison of hardware improvements over this time range.
Bio:
Dr. Jeremy Kepner is an MIT Lincoln Laboratory Fellow. He founded the Lincoln Laboratory Supercomputing Center and pioneered the establishment of the Massachusetts Green High Performance Computing Center. He has developed novel big data and parallel computing software used by thousands of scientists and engineers worldwide. He has led several embedded computing efforts, which earned him a 2011 R&D 100 Award. Kepner has chaired the SIAM Data Mining conference, the IEEE Big Data conference, and the IEEE High Performance Extreme Computing conference. Kepner is the author of two bestselling books, Parallel MATLAB for Multicore and Multinode Computers, and Graph Algorithms in the Language of Linear Algebra. His peer-reviewed publications include works on abstract algebra, astronomy, astrophysics, cloud computing, cybersecurity, data mining, databases, graph algorithms, health sciences, plasma physics, signal processing, and 3D visualization. In 2014, he received Lincoln Laboratory's Technical Excellence Award.
Kepner holds a BA degree in astrophysics from Pomona College and a PhD degree in astrophysics from Princeton University. He is a fellow of the Society of Industrial Applied Mathematics (SIAM) and is a faculty advisor to the MIT SIAM student group.
Directions to 32-G449 - MIT Stata Center, 32 Vassar Street, Cambridge, MA: Please use the main entrance to the Stata Center at 32 Vassar Street (the entrance closest to Main street) as those doors will be unlocked. Upon entering, proceed to the elevators which will be on the right after passing a large set of stairs and a MITAC kiosk. Take the elevator to the 4th floor and turn right, following the hall to an open area; 32-G449 will be on the left. Location of Stata on campus map
This joint meeting of the Boston Chapter of the IEEE Computer Society and GBC/ACM will be hybrid (in person and online).
