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SMARTHEP: Synergies between Machine leArning, Real Time analysis and Hybrid architectures for efficient Event Processing and decision making

Deliverables

Website and social media launched

Launch of the website and social media accounts

Network event/schools documentation - year 1

Documentation, reports and feedback for all Network events and schools published on website

Network event/schools documentation - year 2

Documentation, reports and feedback for all Network events and schools published on website

Fellow presentations at network events - year 2

Collection of public presentations from fellows at Network events highlighted on the website

Hybrid architecture whitepaper

Whitepaper on the state of the art on hybrid architectures (CPU+GPU) in RTA in SMARTHEP use cases

Review of triggers in LHC experiments

Review of the state of the art of the triggers of LHC collaborations and best practices

Mid-term report on communication and outreach

Report on commmunication, outreach and SMARTHEP Masterclass/WWDD.

Whitepapers on RTA-based searches in HEP

Whitepapers on the state of the art of fully RTA-based searches and anomaly detection in HEP and best practices

Publications

Baler -- Machine Learning Based Compression of Scientific Data

Author(s): Fritjof Bengtsson, Caterina Doglioni, Per Alexander Ekman, Axel Gallén, Pratik Jawahar, Alma Orucevic-Alagic, Marta Camps Santasmasas, Nicola Skidmore, Oliver Woolland
Published in: Physics > Computational Physics, 2023
Publisher: Arxiv
DOI: 10.48550/arxiv.2305.02283

Applications of Deep Learning to physics workflows

Author(s): Manan Agarwal, Jay Alameda, Jeroen Audenaert, Will Benoit, Damon Beveridge, Meghna Bhattacharya, Chayan Chatterjee, Deep Chatterjee, Andy Chen, Muhammed Saleem Cholayil, Chia-Jui Chou, Sunil Choudhary, Michael Coughlin, Maximilian Dax, Aman Desai, Andrea Di Luca, Javier Mauricio Duarte, Steven Farrell, Yongbin Feng, Pooyan Goodarzi, Ekaterina Govorkova, Matthew Graham, Jonathan Guiang, Alec Gunny,
Published in: High Energy Physics - Experiment, 2023
Publisher: Arxiv
DOI: 10.48550/arxiv.2306.08106

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