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Fast Machine Learning for Science Workshop

from Monday 30 November 2020 (09:00) to Thursday 3 December 2020 (16:00)
Southern Methodist University

        : Sessions
    /     : Talks
        : Breaks
30 Nov 2020
1 Dec 2020
2 Dec 2020
3 Dec 2020
AM
10:00 Welcome and Orientation - Allison Mccarn Deiana (Southern Methodist University (US))  
10:05 Welcome from SMU - Dr Karisa Cloward (Southern Methodist University)  
10:10 Overview of Workshop - Nhan Tran (Fermi National Accelerator Lab. (US))  
10:20 Trends in Computer Architectures - Michaela Blott (Xilinx Research)  
11:00 --- Coffee Break ---
11:15 Efficient Neural Network Training and Inference - Amir Gholami  
11:55 --- Lunch ---
10:00 HPC - Robert Kalescky (Southern Methodist University )  
10:40 Health Sensing, Detection, and Monitoring - Sougata Sen (Northwestern University) Nabil Alshurafa (Northwestern University)  
11:20 --- Coffee Break ---
11:35 Beyond CMOS - Dimitri Strukov (UCSB)  
10:00 Accelerator-based Neutrinos - Jeremy Edmund Hewes (University of Cincinnati (US))  
10:40 Neutrino Astrophysics - Kate Scholberg (Duke University) Kate Scholberg (Duke University)  
11:18 Acknowledgments - Philip Coleman Harris (Massachusetts Inst. of Technology (US))  
11:20 --- Coffee Break ---
11:35 Cosmology - Michelle Ntampaka (STSCI)  
09:00
Tutorial Session (until 12:00)
09:00 hls4ml Tutorial - Sioni Paris Summers (CERN)  
PM
12:55 Imaging: Electron Microscopy - Josh Agar (Lehigh University)  
13:35 Large Hadron Collider - Jennifer Ngadiuba (CERN)  
14:15 --- Coffee Break ---
14:30 Quantifying DNA Damage in Comet Assay images using Neural Networks - Selina Dhinsey  
14:40 Autoencoders for anomaly detection in real-time at the LHC - Katya Govorkova (CERN)  
14:48 Design of a reconfigurable autoencoder algorithm for detector front-end ASICs - Giuseppe Di Guglielmo (Columbia University)  
14:58 Large and compressed Convolutional Neural Networks on FPGAs with hls4ml - Vladimir Loncar (CERN)  
15:06 Convolutional Neural Network Fast Inference Deployment on FPGAs - Andrew Harmon Reis (Southern Methodist University (US))  
15:14 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))  
15:22 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))  
15:30 A OneAPI backend of hls4ml to speed up Neural Network inference on CPUs - Vladimir Loncar (CERN)  
15:38 A Quartus backend for hls4ml: deploying low-latency Neural Networks on Intel FPGAs - Hamza Javed (Pakistan Institute of Engin. and (PK))  
12:15 --- Lunch ---
13:15 Deep Learning Acceleration of Progress in Fusion Energy Research - Bill Tang (Princeton University)  
13:55 --- Coffee Break ---
14:10 Making ML easier at CERN with Kubeflow - Dejan Golubovic (CERN)  
14:20 Using an Optical Processing Unit for tracking and calorimetry at the LHC - David Rousseau (IJCLab-Orsay)  
14:28 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))  
14:36 Adversarial mixture density network for particle reconstruction: a case study in collider simulation - Kin Ho Lo (University of Florida (US))  
14:44 Application of a neural network based technique for track identification in Nuclear Track Detectors (NTD) - Dr Kanik Palodhi (University of Calcutta, Kolkata)  
14:52 Ultra Low-latency, Low-area Inference Accelerators using Heterogeneous Deep Quantization with QKeras and hls4ml - Thea Aarrestad (CERN)  
15:02 Matrix Element Regression with Deep Neural Networks -- breaking the CPU barrier - Florian Bury (UCLouvain - CP3)  
15:10 An Early Exploration into the Interplay between Quantization and Pruning of Neural Networks - Mr Benjamin Hawks (Fermi National Accelerator Laboratory)  
15:20 Real-time Artificial Intelligence for Accelerator Control: A Study at the Fermilab Booster - Christian Herwig (Fermi National Accelerator Lab. (US))  
15:28 Building the tools to run large scale machine learning with FPGAs with two new approaches: AIGEAN and FAAST - Naif Tarafdar (University of Toronto)  
15:38 muon detection using deep learning, applied to CONNIE events - Mr Javier Bernal (Facultad De Ingenieria UNA)  
15:46 GPU-accelerated machine learning inference as a service for computing in neutrino experiments - Mike Wang  
12:15 --- Lunch ---
13:15 ASICs and Circuits - Tobi Delbruck (ETH Zurich)  
13:55 Electron-Ion Collider - Markus Diefenthaler (Jefferson Lab)  
14:35 --- Coffee Break ---
14:50 Development of ML FPGA filter for particle identification with transition radiation detector. - Sergey Furletov (Jefferson Lab)  
15:00 AI-assisted Tracking Algorithm - Gagik Gavalian (Jefferson Lab)  
15:10 Anomaly Detection with Spiking Neural Networks on Neuromorphic Chips - Bartlomiej Pawel Borzyszkowski  
15:20 Deep Learning based acceleration of Gravitational Waves - Alec Gunny  
15:30 Accelerating Graph Neural Networks on FPGAs for Particle Track Reconstruction using OpenCL and hls4ml - Aneesh Heintz (Cornell University (US))  
15:40 SONIC: Coprocessors as a service for deep learning inference in high energy physics - Dylan Sheldon Rankin (Massachusetts Inst. of Technology (US))  
12:00 --- Lunch ---
13:00
Tutorial Session (until 16:00)
13:00 hls4ml Tutorial - Sioni Paris Summers (CERN)  
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