BEGIN:VCALENDAR VERSION:2.0 PRODID:Linklings LLC BEGIN:VTIMEZONE TZID:America/Denver X-LIC-LOCATION:America/Denver BEGIN:DAYLIGHT TZOFFSETFROM:-0700 TZOFFSETTO:-0600 TZNAME:MDT DTSTART:19700308T020000 RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0600 TZOFFSETTO:-0700 TZNAME:MST DTSTART:19701101T020000 RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20260422T000611Z LOCATION:708 DTSTART;TZID=America/Denver:20231112T090000 DTEND;TZID=America/Denver:20231112T123000 UID:submissions.supercomputing.org_SC23_sess425@linklings.com SUMMARY:XLOOP 2023: The 5th Annual Workshop on Extreme-Scale Experiment-in -the-Loop Computing DESCRIPTION:Cross-Facility Orchestration of Electrochemistry Experiments a nd Computations\n\nInstrument-computing ecosystems that support automated electrochemical workflows typically require the integration of disparate i nstruments such as syringe pump, fraction collector, and potentiostat, al l connected to an electrochemical cell. These specialized instruments wit h custom software and i...\n\n\nAnees Al-Najjar, Nageswara Rao, Craig Brid ges, and Sheng Dai (Oak Ridge National Laboratory (ORNL))\n--------------- ------\nXLOOP 2023: The 5th Annual Workshop on Extreme-Scale Experiment-i n-the-Loop Computing\n\nAdvancement in computational power and high-speed networking is enabling a new model of scientific experiment, experiment-in -the-loop computing (EILC). In this model, simulation and/or learning mod ules are run as data is collected from observational and experimental sour ces. Presently, the amount ...\n\n\nJustin Wozniak (Argonne National Labo ratory (ANL), University of Chicago) and Nicholas Schwarz (Argonne Nationa l Laboratory (ANL))\n---------------------\nDevOps Approaches for Intercon nected Science Ecosystems\n\nMarshall McDonnell (Oak Ridge National Labora tory (ORNL))\n---------------------\nXLOOP – Introduction\n\nJustin Woznia k and Nicholas Schwarz (Argonne National Laboratory (ANL))\n-------------- -------\nStreaming Data from Experimental Facilities to Supercomputers for Real-Time Data Processing\n\nIn this paper we demonstrate direct data str eaming from instruments and detectors at a large-scale experimental facili ty to a supercomputer for real-time data processing and feedback. Streamin g data to supercomputers introduces the potential for novel scientific app lications and workflow models, inc...\n\n\nSiniša Veseli, John Hammonds, S teven Henke, Hannah Parraga, and Nicholas Schwarz (Argonne National Labora tory (ANL))\n---------------------\nSpeeding Up Charge Exchange Recombinat ion Spectroscopy Analysis in Support of NERSC/DIII-D Realtime Workflow\n\n Aarushi Jain\n---------------------\nLinking the Dynamic PicoProbe Analyti cal Electron-Optical Beam Line / Microscope to Supercomputers\n\nThe Dynam ic PicoProbe at Argonne National Laboratory is undergoing upgrades that wi ll enable it to produce up to 100s of GB of data per day. While this data is highly important for both fundamental science and industrial applicatio ns, there is currently limited on-site infrastructure to handle these...\n \n\nAlexander Brace (University of Chicago, Argonne National Laboratory (A NL)); Rafael Vescovi and Ryan Chard (Argonne National Laboratory (ANL)); N ickolaus D. Saint (University of Chicago); and Arvind Ramanathan, Nestor J . Zaluzec, and Ian Foster (Argonne National Laboratory (ANL), University o f Chicago)\n---------------------\nExploring Benchmarks for Self-Driving L abs Using Color Matching\n\nSelf Driving Labs (SDLs) that combine automati on of experimental procedures with autonomous decision making are gaining popularity as a means of increasing the throughput of scientific workflows . The task of identifying a mix of supplied colored pigments that matches a target color, the color match...\n\n\nTobias Ginsburg (Argonne National Laboratory (ANL), Data Science and Learning Division); Kyle Hippe and Rya n Lewis (Argonne National Laboratory (ANL)); Aileen Cleary (Northwestern U niversity); Doga Ozgulbas (Argonne National Laboratory (ANL)); Rory Butler (University of Chicago); Casey Stone and Abraham Stroka (Argonne National Laboratory (ANL)); and Rafael Vescovi and Ian Foster (Argonne National La boratory (ANL), Data Science and Learning Division)\n--------------------- \nXLOOP – Morning Break\n---------------------\nEmpowering Scientific Disc overy through Computing at the Advanced Photon Source\n\nThis paper explor es the challenges and solutions for managing the vast amount of data gener ated by the Advanced Photon Source (APS), a synchrotron light source produ cing ultra-bright x-rays for diverse scientific domains. With 68 experimen tal beamlines, the APS serves a wide user base across academi...\n\n\nHann ah Parraga, John Hammonds, Steven Henke, Siniša Veseli, William Allcock, B enoit Côté, Ryan Chard, Suresh Narayanan, and Nicholas Schwarz (Argonne Na tional Laboratory (ANL))\n---------------------\nDLSIA: Deep Learning for Scientific Image Analysis\n\nEric Roberts (Lawrence Berkeley National Lab oratory (LBNL))\n---------------------\nXLOOP – Awards Ceremony\n\nJustin Wozniak and Nicholas Schwarz (Argonne National Laboratory (ANL))\n-------- -------------\nDemonstrating Cross-Facility Data Processing at Scale with Laue Microdiffraction\n\nIn February and April 2023 live, at-scale data pr ocessing demonstrations were conducted between the Advanced Photon Source (APS), a synchrotron light source, and the Argonne Leadership Computing Fa cility (ALCF). These tests were run as part of a novel beamline technique: coded aperture laue micro-di...\n\n\nMichael Prince, Doğa Gürsoy, Dina Sh eyfer, Ryan Chard, Benoit Côté, Hannah Parraga, Barbara Frosik, Jon Tischl er, and Nicholas Schwarz (Argonne National Laboratory (ANL))\n------------ ---------\nWorkflows Are the New Applications – So What?\n\nRangan Sukumar \n\nTag: Large Scale Systems, Performance Measurement, Modeling, and Tools , Software Engineering\n\nRegistration Category: Workshop Reg Pass\n\nSess ion Chairs: Nicholas Schwarz (Argonne National Laboratory (ANL)) and Justi n Wozniak (Argonne National Laboratory (ANL), University of Chicago) END:VEVENT END:VCALENDAR