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CLSAC 2022

To the Edge and Back: Ubiquitous Analytics


October 24 - 27, 2022
Graduate Annapolis, Maryland




Theme:

The design space for large scale distributed computing and analytics is increasingly rich, complex, and diverse (e.g. Accelerator technologies, IoT, SmartNICs, Computational Storage, Hybrid-MultiCloud, and HPC).   As scale and distribution grows, so does the impact of where data is moved and computations occur, as well as the need to address resilience, control, privacy, and security.  The build out of the Internet of Things (IoT) and other large-scale, geographically dispersed federated systems (such as smart cities, connected transportation, power grids, and healthcare) presents a multitude of opportunities and challenges when designing large-scale analytics.  Optimally managing up to tens of billions of endpoints capable of collecting new and growing sources of data, and millions of heterogeneous distributed computing elements (e.g., sensors, edge processors, mobile devices, on-premise servers, SmartNICs, Computational Storage, Clouds, HPC systems, etc.) creates significant performance, cost, and software development complexities.  Insightful and pivotal decisions on where to collect, process, and analyze data will be required to achieve acceptable latencies, accurate conclusions, at acceptable costs.


Organizing Committee:
Jim Ang, Pacific Northwest National Laboratory
John Feo, Pacific Northwest National Laboratory
David Haglin, Trovares, Inc.
Ron Oldfield, Sandia National Laboratories
Richard Murphy, Gem State Informatics, Inc.
Almadena Chtchelkanova, National Science Foundation
Brad Spiers, Committee Advisor
Candace Culhane, Los Alamos National Laboratory
Nick Rogers, Department of Defense
TC Tuan, Department of Defense
Steve Pritchard, Committee Advisor


Agenda


Monday, October 24, 2022
7:00 -- 8:30 pm
Welcome Reception (Graduate Atrium)

Tuesday, October 25, 2022
​General Session Location: The Ballroom
7:00 — 8:00 am
Breakfast and Registration (Atrium)
8:00 — 8:30
Welcome
George Cotter Award for Vision and Leadership in the Field of Data Analytics
Jim Ang, PNNL
​Candy Culhane, LANL
8:30 — 9:15 am
Keynote: Moving from Data to Information to Enhance USAF Decision-Making Capabilities
Dr. Qing Wu, Air Force Research Lab.
Session 1: Applications
Moderator: Ron Oldfield
9:15 — 10:00 am
The Confluence of HPC and Experimental and Observational Science
Sudip Dosanjh, LBL/NERSC
10:00 — 10:15 am
Break: (Atrium)
10:15 — 11:00 am
From the Edge to the Supercomputer: Analysis Along the Way
Pete Beckman, ANL
11:00 — 11:45 am
ORCA: Orchestrating Symbiotic Intelligence for Agile and Adaptable, Crisis Response Decision Making
Eric Davis, Galois Inc.
11:45 — 12:30 pm
Panel Discussion
12:30 — 1:45 pm
Lunch (Atrium)
Session 2: Software
Moderator: Nick Rogers
1:45 — 2:30 pm
Primate: Towards the Automatic Generating Soft Processor Overlays and Tooling
Derek Chiou, University of Texas, Austin
2:30 — 3:15 pm
Compilers and Tools for Edge Computing
Richard Lethin, Qualcomm
3:15 — 3:30 pm
Break (Atrium)
3:30 — 4:15 pm
HPC at the Edge: Enabling Real Time Streaming Sensor Analytics
Adam Thompson, NVIDIA
4:15 — 5:00 pm
Panel Discussion

6:00 — 7:30 pm
Dinner (Atrium)
Intelligence is an Algorithm for Understanding; the Human Brain, not so Much
Thomas Sterling, Indiana University
7:30 — 9:30 pm
Reception (Mainsail/Spinnaker)



Wednesday, October 26, 2022
General Session Location: The Ballroom
7:00 — 8:30 am
Breakfast and Registration (Atrium)
8:30 — 9:15 am
Keynote: Dynamic Capability Composition at the Digital Continuum from Edge to HPC
Dr. Ilkay Altintas, SDSC
Session 3: Software
Moderator: John Feo
9:15 — 10:00 am
Massive Dataset Analysis in Arkouda

David Bader, New Jersey Institute of Technology

10:00 — 10:15 am
Break (Atrium)
10:15 — 11:00 am
Using AI to Improve AI Development and Deployment
Vijay Gadepally, MIT
11:00 — 11:45 am
A Scalable, Thread-safe Programming Environment for Streaming Edge Analytics
Vito Castellana, PNNL
11:45 — 12:30 pm
Panel Discussion
12:30 — 6:00 pm
Free time: Lunch and Dinner on your own
Random Access
The Ballroom
6:00 — 7:30 pm
Sign-up sheet will be at the registration table. Talks are limited to 8 minutes.
 Moderator: Steve Pritchard
Reception/Poster Session
(Mainsail/Spinnaker)
7:30 — 9:00 pm
Students
Toward Knowledge-Rich Multimodal Foundation Models for Cybersecurity
Nicholas Botzer, University of Notre Dame
Internet of Things Security Education for Undergraduate Computer Science Students
Priyanka Ranade, University of Maryland
Double-tap to edit.
Bayesian Operator Inference for Parametric Reduce-Order Models
Shane McQuarrie, University of Texas, Austin
Double-tap to edit.
A Real-Time Edge Data Analytics Framework for Air Traffic Control
Sharmistha Chakrabarti, University of Central Florida

Thursday, October 27, 2022
General Session Location: The Ballroom
7:00 — 8:30 am
Breakfast (Atrium)
8:30 — 9:15 am
Keynote: IMPROVE-ing AI for medical applications
Ryan Weil
Session 4: Hardware
Moderator: Rich Murphy
9:15 -- 10:00 am
Fast Cheap and Out of Control: Optimal Networks for Large-Scale Analytics

Fabrizio Petrini, Intel
Laura Monroe, LANL
10:00 — 10:15 am
Break (Atrium)
10:15 — 11:00 am
Enabling The Future of Connected Devices
Harish Arunachalam, Verizon
11:00 — 11:45 am

Challenges in Validating Edge Computing Infrastructure
Johnathan Cree, Pacific Northwest National Laboratory
11:45 — 12:30 pm
Panel Discussion
12:30 — 1:45 pm
Lunch (Atrium)
Session 5: Policy and Ethics
Moderator: Brad Spiers
1:45 -- 2:30 pm
Confidential & Secure AI/ML Cybersecurity at the Edge
Roberta Faux and Hunter Richards, Lorica Cybersecurity
2:30 -- 3:15 pm
Ethical Challenges of Ambient Intelligence and Continuous Monitoring Technologies in Healthcare
Nicole Martinez-Martin, JD, PhD, Stanford School of Medicine’s Center for Biomedical Ethics
3:15 -- 3:30 pm
Break (Atrium)
3:30 -- 4:15 pm
Whose Data Are You Processing at the Edge?

Mark Fagan, Harvard
4:15 -- 5:00 pm
Panel Discussion
5:00 -- 5:15 pm
Closing Remarks and Adjourn
5:00 -- 6:30
Closing Reception
2022 Sponsors
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The CLSAC web site is sponsored by the Association for High-Speed Computing.