Fast Machine Learning for Science Workshop

from Monday, November 30, 2020 (9:00 AM) to Thursday, December 3, 2020 (4:00 PM)
Southern Methodist University

        : Sessions
    /     : Talks
        : Breaks
Nov 30, 2020
Dec 1, 2020
Dec 2, 2020
Dec 3, 2020
AM
10:00 AM Welcome and Orientation - Allison Mccarn Deiana (Southern Methodist University (US))   ()
10:05 AM Welcome from SMU - Dr Karisa Cloward (Southern Methodist University)   ()
10:10 AM Overview of Workshop - Nhan Tran (Fermi National Accelerator Lab. (US))   ()
10:20 AM Trends in Computer Architectures - Michaela Blott (Xilinx Research)   ()
11:00 AM --- Coffee Break ---
11:15 AM Efficient Neural Network Training and Inference - Amir Gholami   ()
11:55 AM --- Lunch ---
10:00 AM HPC - Robert Kalescky (Southern Methodist University )   ()
10:40 AM Health Sensing, Detection, and Monitoring - Sougata Sen (Northwestern University) Nabil Alshurafa (Northwestern University)   ()
11:20 AM --- Coffee Break ---
11:35 AM Beyond CMOS - Dimitri Strukov (UCSB)   ()
10:00 AM Accelerator-based Neutrinos - Jeremy Edmund Hewes (University of Cincinnati (US))   ()
10:40 AM Neutrino Astrophysics - Kate Scholberg (Duke University) Kate Scholberg (Duke University)   ()
11:18 AM Acknowledgments - Philip Coleman Harris (Massachusetts Inst. of Technology (US))   ()
11:20 AM --- Coffee Break ---
11:35 AM Cosmology - Michelle Ntampaka (STSCI)   ()
9:00 AM
Tutorial Session (until 12:00 PM) ()
9:00 AM hls4ml Tutorial - Sioni Paris Summers (CERN)   ()
PM
12:55 PM Imaging: Electron Microscopy - Josh Agar (Lehigh University)   ()
1:35 PM Large Hadron Collider - Jennifer Ngadiuba (CERN)   ()
2:15 PM --- Coffee Break ---
2:30 PM Quantifying DNA Damage in Comet Assay images using Neural Networks - Selina Dhinsey   ()
2:40 PM Autoencoders for anomaly detection in real-time at the LHC - Katya Govorkova (CERN)   ()
2:48 PM Design of a reconfigurable autoencoder algorithm for detector front-end ASICs - Giuseppe Di Guglielmo (Columbia University)   ()
2:58 PM Large and compressed Convolutional Neural Networks on FPGAs with hls4ml - Vladimir Loncar (CERN)   ()
3:06 PM Convolutional Neural Network Fast Inference Deployment on FPGAs - Andrew Harmon Reis (Southern Methodist University (US))   ()
3:14 PM Convolutional Neural Networks for real-time processing of ATLAS Liquid-Argon Calorimeter signals with FPGAs - Anne-Sophie Berthold (Technische Universitaet Dresden (DE)) Nick Fritzsche (Technische Universitaet Dresden (DE))   ()
3:22 PM FastCaloGAN: a tool for fast simulation of the ATLAS calorimeter system with Generative Adversarial Networks - Michele Faucci Giannelli (INFN e Universita Roma Tor Vergata (IT))   ()
3:30 PM A OneAPI backend of hls4ml to speed up Neural Network inference on CPUs - Vladimir Loncar (CERN)   ()
3:38 PM A Quartus backend for hls4ml: deploying low-latency Neural Networks on Intel FPGAs - Hamza Javed (Pakistan Institute of Engin. and (PK))   ()
12:15 PM --- Lunch ---
1:15 PM Deep Learning Acceleration of Progress in Fusion Energy Research - Bill Tang (Princeton University)   ()
1:55 PM --- Coffee Break ---
2:10 PM Making ML easier at CERN with Kubeflow - Dejan Golubovic (CERN)   ()
2:20 PM Using an Optical Processing Unit for tracking and calorimetry at the LHC - David Rousseau (IJCLab-Orsay)   ()
2:28 PM Level 1 trigger track quality machine learning models on FPGAs for the Phase 2 upgrade of the CMS experiment - Claire Savard (University of Colorado Boulder (US))   ()
2:36 PM Adversarial mixture density network for particle reconstruction: a case study in collider simulation - Kin Ho Lo (University of Florida (US))   ()
2:44 PM Application of a neural network based technique for track identification in Nuclear Track Detectors (NTD) - Dr Kanik Palodhi (University of Calcutta, Kolkata)   ()
2:52 PM Ultra Low-latency, Low-area Inference Accelerators using Heterogeneous Deep Quantization with QKeras and hls4ml - Thea Aarrestad (CERN)   ()
3:02 PM Matrix Element Regression with Deep Neural Networks -- breaking the CPU barrier - Florian Bury (UCLouvain - CP3)   ()
3:10 PM An Early Exploration into the Interplay between Quantization and Pruning of Neural Networks - Mr Benjamin Hawks (Fermi National Accelerator Laboratory)   ()
3:20 PM Real-time Artificial Intelligence for Accelerator Control: A Study at the Fermilab Booster - Christian Herwig (Fermi National Accelerator Lab. (US))   ()
3:28 PM Building the tools to run large scale machine learning with FPGAs with two new approaches: AIGEAN and FAAST - Naif Tarafdar (University of Toronto)   ()
3:38 PM muon detection using deep learning, applied to CONNIE events - Mr Javier Bernal (Facultad De Ingenieria UNA)   ()
3:46 PM GPU-accelerated machine learning inference as a service for computing in neutrino experiments - Mike Wang   ()
12:15 PM --- Lunch ---
1:15 PM ASICs and Circuits - Tobi Delbruck (ETH Zurich)   ()
1:55 PM Electron-Ion Collider - Markus Diefenthaler (Jefferson Lab)   ()
2:35 PM --- Coffee Break ---
2:50 PM Development of ML FPGA filter for particle identification with transition radiation detector. - Sergey Furletov (Jefferson Lab)   ()
3:00 PM AI-assisted Tracking Algorithm - Gagik Gavalian (Jefferson Lab)   ()
3:10 PM Anomaly Detection with Spiking Neural Networks on Neuromorphic Chips - Bartlomiej Pawel Borzyszkowski   ()
3:20 PM Deep Learning based acceleration of Gravitational Waves - Alec Gunny   ()
3:30 PM Accelerating Graph Neural Networks on FPGAs for Particle Track Reconstruction using OpenCL and hls4ml - Aneesh Heintz (Cornell University (US))   ()
3:40 PM SONIC: Coprocessors as a service for deep learning inference in high energy physics - Dylan Sheldon Rankin (Massachusetts Inst. of Technology (US))   ()
12:00 PM --- Lunch ---
1:00 PM
Tutorial Session (until 4:00 PM) ()
1:00 PM hls4ml Tutorial - Sioni Paris Summers (CERN)   ()