ACAT2021 has put together a spectacular program of plenary talks! Abstracts may be submitted until September 12, 2021 and registration will be open shortly.
The 20th International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2021) will take place between Monday, November 29 and Friday, December 3 2021 as a combined virtual and physical event at IBS Science Culture Center in Daejeon, South Korea. Abstract submission is currently open and will close on September 12, 2021!
Virtual participation in the conference is free of charge but there will be a small fee of USD 70 for those able to attend in person. Detailed information will be available on the registration webpage soon.
ACAT promises to showcase an excellent set of plenary speakers, and highlights include Joseph Lykken (Fermilab, on Quantum Computing), Lenka Zdeborova (EPFL, on a Theory of Deep Learning), Barry C. Sanders (University of Calgary, on Quantum Machine Learning), Michael Spannowsky (Durham University, on Unsupervised Machine Learning for New Physics Searches), and Julia Fitzner (WHO, on WHO's Data Analysis Challenges during COVID-19 Pandemic).
To complement the plenary program, we invite you to submit abstracts for parallel talks and posters. The poster sessions will be provided through a virtual platform, allowing for a more convenient and exciting conference experience. Please forward this news to anyone you know who might be interested. ACAT's success is based on its many high quality contributions and the technical expertise of its attendees.
We look forward to seeing you in November, either in a virtual conference room or in Daejeon!
The 20th edition of ACAT will — once again — bring together computational experts from a wide range of disciplines, including particle-, nuclear-, astro-, and accelerator-physics as well as high performance computing. Through this unique forum, we will explore the areas where these disciplines overlap with computer science, fostering the exchange of ideas related to cutting-edge computing, data-analysis, and theoretical-calculation technologies.
AI Decoded: Towards Sustainable, Diverse, Performant and Effective Scientific Computing
ACAT 2021’s theme will be about the frontiers and limits of AI and explore how we can develop sustainable techniques that can be widely used on a diverse range of computing architectures, in particular the exploitation of co-processors and High Performance Computing (HPC) facilities, to optimise the processing and analysis of scientific data. We are ready to accept abstracts on this theme and on topics in areas of the three parallel tracks outlined below.
ACAT Workshops have plenary and parallel sessions during the five-day conference. The parallel sessions cover the following areas:
- Track 1: Computing Technology for Physics Research, including languages, paradigms, architectures, virtualization, networking and online computing.
- Track 2: Data Analysis - Algorithms and Tools, including machine learning, analysis techniques, simulation, reconstruction and visualization methods, and future ideas such as quantum computing.
- Track 3: Computations in Theoretical Physics: Techniques and Methods, including automatic systems, higher order calculations, computer algebra techniques, and theoretical and simulation aspects of computational physics.
This edition of ACAT will emphasize Machine Learning, although as at the previous ACAT's we hope that a wide variety of experimental and theoretical topics will be discussed.
If you have been forwarded this email and would like to make sure you don't miss-out when registration opens, please subscribe to our mailing list, acat-info @ cern.ch, by sending an email email@example.com!
Local Committee chairs
Soonwook Hwang, KISTI
Doris Yangsoo Kim, Soongsil University