| Title |
FPGA Architectures for Distributed ML Systems for Real-Time Beam Loss De-Blending |
| Authors |
- M.A. Ibrahim, J.M.S. Arnold, M.R. Austin, J.R. Berlioz, P.M. Hanlet, K.J. Hazelwood, J. Mitrevski, V.P. Nagaslaev, A. Narayanan, D.J. Nicklaus, G. Pradhan, A.L. Saewert, B.A. Schupbach, K. Seiya, R.M. Thurman-Keup, N.V. Tran
Fermilab, Batavia, Illinois, USA
- J.YC. Hu, J. Jiang, H. Liu, S. Memik, R. Shi, A.M. Shuping, M. Thieme, C. Xu
Northwestern University, EVANSTON, USA
|
| Abstract |
The Real-time Edge AI for Distributed Systems (READS) project’s goal is to create a Machine Learning (ML) system for real-time beam loss de-blending within the accelerator enclosure, which houses two accelerators: the Main Injector (MI) and the Recycler (RR). In periods of joint operation, when both machines contain high intensity beam, radiative beam losses from MI and RR overlap on the enclosure¿s beam loss monitoring (BLM) system, making it difficult to attribute those losses to a single machine. Incorrect diagnoses result in unnecessary downtime that incurs both financial and experimental cost. The ML system will automatically disentangle each machine¿s contributions to those measured losses, while not disrupting the existing operations-critical functions of the BLM system. Within this paper, the ML models, used for learning both local and global machine signatures and producing high quality inferences based on raw BLM loss measurements, will only be discussed at a high-level. This paper will focus on the evolution of the architecture, which provided the high-frequency, low-latency collection of synchronized data streams to make real-time inferences.
|
| Footnotes & References |
Performed at Northwestern with support from the Departments of Computer Science and Electrical and Computer Engineering |
| Funding |
Operated by Fermi Research Alliance, LLC under Contract No.DE-AC02-07CH11359 with the United States Department of Energy. Additional funding provided by Grant Award No. LAB 20-2261 [1] |
| Paper |
download TU3C02.PDF [6.258 MB / 4 pages] |
| Slides |
download TU3C02_TALK.PDF [17.830 MB] |
| Cite |
download ※ BibTeX
※ LaTeX
※ Text/Word
※ RIS
※ EndNote |
| Conference |
IBIC2023 |
| Series |
International Beam Instrumentation Conference (12th) |
| Location |
Saskatoon, Canada |
| Date |
10-14 September 2023 |
| Publisher |
JACoW Publishing, Geneva, Switzerland |
| Editorial Board |
Volker R.W. Schaa (GSI, Darmstadt, Germany); Tonia Batten (CLS, Saskatoon, Canada); Michael Bree (CLS, Saskatoon, Canada); Christine Petit-Jean-Genaz (CERN, Geneva, Switzerland); Darren Hunter (CLS, Saskatoon, Canada) |
| Online ISBN |
978-3-95450-236-3 |
| Online ISSN |
2673-5350 |
| Received |
07 September 2023 |
| Revised |
10 September 2023 |
| Accepted |
12 September 2023 |
| Issue Date |
25 September 2023 |
| DOI |
doi:10.18429/JACoW-IBIC2023-TU3C02 |
| Pages |
160-163 |
| Copyright |
 Published by JACoW Publishing under the terms of the Creative Commons Attribution 4.0 International license. Any further distribution of this work must maintain attribution to the author(s), the published article's title, publisher, and DOI. |
|
