Author: Nemesure, S.
Paper Title Page
MO1BCO04 EIC Controls System Architecture Status and Plans 19
 
  • J.P. Jamilkowski, S.L. Clark, M.R. Costanzo, T. D’Ottavio, M. Harvey, K. Mernick, S. Nemesure, F. Severino, K. Shroff
    BNL, Upton, New York, USA
  • L.R. Dalesio
    Osprey DCS LLC, Ocean City, USA
  • K. Kulmatycski, C. Montag, V.H. Ranjbar, K.S. Smith
    Brookhaven National Laboratory (BNL), Electron-Ion Collider, Upton, New York, USA
 
  Funding: Contract Number DE-AC02-98CH10886 with the auspices of the US Department of Energy
Preparations are underway to build the Electron Ion Collider (EIC) once Relativistic Heavy Ion Collider (RHIC) beam operations are end in 2025, providing an enhanced probe into the building blocks of nuclear physics for decades into the future. With commissioning of the new facility in mind, Accelerator Controls will require modernization in order to keep up with recent improvements in the field as well as to match the fundamental requirements of the accelerators that will be constructed. We will describe the status of the Controls System architecture that has been developed and prototyped for EIC, as well as plans for future work. Major influences on the requirements will be discussed, including EIC Common Platform applications as well as our expectation that we’ll need to support a hybrid environment covering both the proprietary RHIC Accelerator Device Object (ADO) environment as well as EPICS.
 
slides icon Slides MO1BCO04 [1.458 MB]  
DOI • reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-MO1BCO04  
About • Received ※ 05 October 2023 — Revised ※ 08 October 2023 — Accepted ※ 14 November 2023 — Issued ※ 11 December 2023
Cite • reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)  
 
TUMBCMO15 Enhancing Electronic Logbooks Using Machine Learning 382
 
  • J. Maldonado, S.L. Clark, W. Fu, S. Nemesure
    BNL, Upton, New York, USA
 
  Funding: Work supported by Brookhaven Science Associates, LLC under Contract No. DE-SC0012704
The electronic logbook (elog) system used at Brookhaven National Laboratory’s Collider-Accelerator Department (C-AD) allows users to customize logbook settings, including specification of favorite logbooks. Using machine learning techniques, customizations can be further personalized to provide users with a view of entries that match their specific interests. We will utilize natural language processing (NLP), optical character recognition (OCR), and topic models to augment the elog system. NLP techniques will be used to process and classify text entries. To analyze entries including images with text, such as screenshots of controls system applications, we will apply OCR. Topic models will generate entry recommendations that will be compared to previously tested language processing models. We will develop a command line interface tool to ease automation of NLP tasks in the controls system and create a web interface to test entry recommendations. This technique will create recommendations for each user, providing custom sets of entries and possibly eliminate the need for manual searching.
 
slides icon Slides TUMBCMO15 [0.905 MB]  
poster icon Poster TUMBCMO15 [4.697 MB]  
DOI • reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-TUMBCMO15  
About • Received ※ 04 October 2023 — Revised ※ 12 October 2023 — Accepted ※ 24 November 2023 — Issued ※ 10 December 2023
Cite • reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)  
 
THMBCMO07 Reflective Servers: Seamless Offloading of Resource Intensive Data Delivery 1201
 
  • S.L. Clark, T. D’Ottavio, M. Harvey, J.P. Jamilkowski, J. Morris, S. Nemesure
    BNL, Upton, New York, USA
 
  Funding: Work supported by Brookhaven Science Associates, LLC under Contract No. DE-SC0012704 with the U.S. Department of Energy.
Brookhaven National Laboratory’s Collider-Accelerator Department houses over 550 Front-End Computers (FECs) of varying specifications and resource requirements. These FECs provide operations-critical functions to the complex, and uptime is a concern among the most resource constrained units. Asynchronous data delivery is widely used by applications to provide live feedback of current conditions but contributes significantly towards resource exhaustion of FECs. To provide a balance of performance and efficiency, the Reflective system has been developed to support unrestricted use of asynchronous data delivery with even the most resource constrained FECs in the complex. The Reflective system provides components which work in unison to offload responsibilities typically handled by core controls infrastructure to hosts with the resources necessary to handle heavier workloads. The Reflective system aims to be a drop-in component of the controls system, requiring few modifications and remaining completely transparent to users and applications alike.
 
slides icon Slides THMBCMO07 [0.963 MB]  
poster icon Poster THMBCMO07 [6.670 MB]  
DOI • reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-THMBCMO07  
About • Received ※ 04 October 2023 — Accepted ※ 08 December 2023 — Issued ※ 15 December 2023  
Cite • reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)