Informal DOE Briefing : USCMS/FNAL Computing Innovation towards HL-LHC

Contribution List

0. Introduction, Goals for the Meeting

Dr Lothar Bauerdick (Fermilab), Prof. Maria Spiropulu (Caltech)

13/06/2019, 12:00

1. Innovation and Engineering for HL-LHC Computing Infrastructure

Dr Lothar Bauerdick (Fermilab), Dr Oliver Gutsche (Fermi National Accelerator Laboratory)

13/06/2019, 12:10

Computing HL-LHC challenges and the envisioned computation ecosystem to address them

8. "on-chip" computation (FPGA-based framework)

Javier Duarte (Fermilab), Michail Bachtis

13/06/2019, 12:35

Innovation & Engineering (I)

14. Advanced Methods for Data Processing and Reconstruction

Allison Reinsvold Hall, Lindsey Gray (Fermilab), Nhan Tran (FNAL)

13/06/2019, 12:55

Innovation & Engineering (I)

5. Advanced Data Analysis and Simulation Methods

Joosep Pata (Caltech), Kevin Pedro (Fermilab), Nicholas Smith (Fermilab)

13/06/2019, 13:25

Innovation & Engineering (I)

11. Data Organization, Management, and Access

Brian Bockelman

13/06/2019, 14:00

Innovation & Engineering (II)

10. Software Framework and HPC

Matti Kortelainen

13/06/2019, 14:15

Innovation & Engineering (II)

9. Machine Learning Ecosystem

Dr Jean-Roch Vlimant (California Institute of Technology)

13/06/2019, 14:30

Innovation & Engineering (II)

12. Mapping Computing Innovation onto HL-LHC Needs

Markus Klute (MIT)

13/06/2019, 14:45

Innovation & Engineering (II)

2. Strategy towards HL-LHC Computing, Next Steps

Dr Lothar Bauerdick (Fermilab), Prof. Maria Spiropulu (Caltech), Dr Oliver Gutsche (Fermi National Accelerator Laboratory)

13/06/2019, 15:00

3. Executive Session/Adjourn

13/06/2019, 15:20

7. Accelerating Higgs-->bb Analysis with Coffea: Nick Smith

13. Accelerating Higgs-->µµ and optimizing computational Kernels: Joosep Pata

4. Graph Neural Networks for Next Generation Detector Reconstruction: Lindsey Gray

6. Machine Learning on FPGAs: Nhan Tran

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