A3D3 Kick-off meeting

Name: A3D3 Kick-off meeting
Start: 2021-11-08T11:00:00-08:00
End: 2021-11-10T13:10:00-08:00
Location: No location set

8–10 Nov 2021

US/Pacific timezone

Contribution List

1. Introduction

Shih-Chieh Hsu (University of Washington Seattle (US))

08/11/2021, 11:00

28. Logo and Website

Miaoyuan Liu (Purdue University (US)), Philip Coleman Harris (Massachusetts Inst. of Technology (US))

08/11/2021, 11:10

19. HEP

Miaoyuan Liu (Purdue University (US))

08/11/2021, 11:25

Lightning talks

20. MMA

Michael Coughlin (University of Minnesota)

08/11/2021, 11:30

Lightning talks

21. Neuros

Amy Orsborn

08/11/2021, 11:35

Lightning talks

22. HAC

Pan Li, Pan Li

08/11/2021, 11:40

Lightning talks

24. Targeted & Heterogenous Systems

Eli Shlizerman, Javier Mauricio Duarte (Univ. of California San Diego (US))

08/11/2021, 11:45

Lightning talks

25. Engagement

Mark Neubauer (Univ. Illinois at Urbana Champaign (US)), Mark Stephen Neubauer (Univ. Illinois at Urbana-Champaign)

08/11/2021, 11:50

Lightning talks

26. Education

Matthew Graham (California Institute of Technology), Matthew Graham

08/11/2021, 11:55

Lightning talks

27. Equity and Career

Javier Mauricio Duarte (Univ. of California San Diego (US)), Miaoyuan Liu (Purdue University (US))

08/11/2021, 12:00

Lightning talks

45. Graph neural networks in HEP

Yongbin Feng (Fermi National Accelerator Lab. (US))

08/11/2021, 12:20

HEP

10 mins talk + 5 mins discussion

41. intro to neuro data

Prof. Maria Dadarlat (Purdue)

08/11/2021, 12:20

Neuroscience

overview of signal types, properties

42. auto-encoders for neural signal prediction

MICHAEL NOLAN

08/11/2021, 12:32

Neuroscience

46. Anomaly detection in HEP

Sang Eon Park (Massachusetts Inst. of Technology (US))

08/11/2021, 12:35

HEP

10 mins talk + 5 mins discussion

43. approaches to analyze behavior

JINGYUAN LI

08/11/2021, 12:44

Neuroscience

47. SPVCNN applications in HEP

Alexander Joseph Schuy (University of Washington (US))

08/11/2021, 12:50

HEP

10 mins talk + 5 mins discussion

44. discussion time

08/11/2021, 12:56

Neuroscience

40. Intro

Pan Li (Purdue)

08/11/2021, 13:10

HAC

HAC (Hardware and Algorithm co-development) is one main research direction of A3D3, where the goal is to study the state-of-the-art AI hardware and algorithms for scientific applications. In this session, we have four talks that include AI algorithm/hardware design for physical applications, and efficient compilation tools for AI hardware automatic design.

29. Point cloud methods for science

Zhijian Liu (MIT)

08/11/2021, 13:12

HAC

30. GNN-for-Science

Siqi Miao (Purdue)

08/11/2021, 13:24

HAC

32. ScaleHLS

Hanchen Ye (UIUC)

08/11/2021, 13:36

HAC

33. HLS4ML

Dylan Rankin (MIT)

08/11/2021, 13:48

HAC

38. Intro

Eli Shlizerman, Javier Mauricio Duarte (Univ. of California San Diego (US))

09/11/2021, 11:00

Targeted and heterogeneous systems

Targeted systems: hardware-based, edge devices, on-sensor, including FPGA, ASIC, or other technology used for monitoring, instrument control, data selection, or data processing often in real-time or with very low latency.

Heterogenous systems: CPUs + coprocessors, high-throughput data processing, may include HPCs, cloud resources, asynchronous communication, as-a-service.

This section...

35. HEP: Level-1 trigger (FPGA) + On-detector readout (ASIC)

Daniel Diaz (Univ. of California San Diego (US))

09/11/2021, 11:05

Targeted and heterogeneous systems

39. HEP: Services for Optimized Network Inference on Coprocessors (SONIC)

Jeffrey Krupa (Massachusetts Institute of Technology)

09/11/2021, 11:25

Targeted and heterogeneous systems

37. MMA: Gravitational Wave Inference as a Service

Alec Gunny, Alec Gunny (Massachusetts Institute of Technology)

09/11/2021, 11:45