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Fast ML UK tutorial
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Europe/London
LT2 (Imperial)
LT2
Imperial
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Description
We are hosting a one-day Fast Machine Learning (Fast ML) tutorial at Imperial College London on 27th March, aimed at UK students and early-career researchers (ECRs) interested in ML for real-time scientific applications. In this tutorial, participants will learn how to convert standard ML algorithms for FPGA synthesis using the hls4ml library, and explore the trade-offs between model accuracy and FPGA resource usage/latency. We will then introduce quantization-aware training techniques that help maintain model performance while minimizing resource consumption.
In the afternoon session, we will explore more complex architectures (e.g. transformers) and demonstrate the practical steps required for FPGA synthesis with the aim to showcase the build process on a real FPGA device. Participation is in-person only, and registration closes on 19th March so that we can finalise numbers for refreshments.
Participants
Ayham Yousif
Bakhtiar Zadeh
Bardia Zadeh
EDWIN GARCIA
Emma Claraso Batllori
Geoffrey Pugsley
Giacomo Fedi
Guhesh Kumaran
Harsh Rathee
Hugh Sparks
James Gibbon
Jonathon Mark Langford
Kai Hong Law
Leo Rozanov
Luke Wivell
Matthew Ward
Nabir Mamnun
Nadia Cooper
Paolo Bassani
Paul Krueper
Rishi Siddani
Ruijie Chen
Ryan Schmitz
Sam Bennett
Shiyu Chen
Thomas Walker
Tim Marley
Vishnu Nair
Wen Song
Yufei Yang
Yuyang Sun