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DTSTART;TZID=Europe/Stockholm:20240603T143000
DTEND;TZID=Europe/Stockholm:20240603T163000
UID:submissions.pasc-conference.org_PASC24_sess130@linklings.com
SUMMARY:MS2E - Complex Autonomous Workflows that Interconnect AI/ML, Model
 ing and Simulation, and Experimental Instruments
DESCRIPTION:Minisymposium\n\nRecent advancements in edge computing, automa
 tion, and artificial intelligence (AI) have spurred the development of "sm
 art" autonomous laboratories and facilities that integrate complex workflo
 ws across experimental instruments and distributed heterogeneous computati
 onal resources. The primary objective of our minisymposium is to showcase 
 recent advances aimed at establishing research ecosystem capabilities that
  seamlessly integrate real-time experiment and computational workflows acr
 oss edge devices, cloud computing, and high-performance computing (HPC) re
 sources. While edge computing enables laboratories to rapidly process data
  at its source to reduce latency and improve real-time decision-making, AI
 /ML and HPC simulations are fundamental components that allow autonomous l
 aboratories to rapidly learn, adapt, and optimize workflow processes. Our 
 minisymposium presentations offer a distinct perspective that highlight co
 mmon smart autonomous science workflows that transcend disciplinary bounda
 ries to seamlessly foster cross-disciplinary collaboration and knowledge e
 xchange. The full integration of AI/ML, modeling and simulation, and exper
 imental instruments is an impossible task for a single group. Hence, our m
 inisymposium is intended to both inform attendees of recent complex workfl
 ow efforts and build new collaborations to tackle future challenges with b
 uilding an interoperable ecosystem for complex workflows that enable auton
 omous laboratories and facilities.\n\nNew Science from Cross-Facility Work
 flows: Case Studies in the Superfacility Model\n\nAs higher precision expe
 rimental instruments become available scientific facilities are shifting t
 he way they run experiments. With the increase in experimental data rates 
 scientists have had to rely more on large HPC resources for experimental p
 ost processing. One of the goals in developing the Sup...\n\n\nNicholas Ty
 ler (Lawrence Berkeley National Laboratory, NERSC)\n---------------------\
 nIntegrating Instruments and Compute Resources at Scale Using Globus\n\nIn
  modern experimental facilities, advanced detectors gather data at rates o
 f multiple gigabytes per second. To manage this massive influx of data eff
 ectively, experiment-time analysis techniques that allow tailoring of expe
 riment run (e.g. filter out irrelevant data elements ) are required.  Achi
 ev...\n\n\nRachana Ananthakrishnan, Kyle Chard, and Ian Foster (University
  of Chicago, Argonne National Laboratory)\n---------------------\nRecent A
 dvances in Interoperable Workflows for Complex System\n\nThis presentation
  delves into cutting-edge developments in the creation of interoperable wo
 rkflows that bridge the gap between experimental instruments and diverse c
 omputational platforms, highlighting the push towards an integrated resear
 ch ecosystem with a focus on seamlessly integrating experimen...\n\n\nRafa
 el Ferreira da Silva (Oak Ridge National Laboratory)\n--------------------
 -\nProgramming Dynamic and Intelligent Workflows for the Continuum\n\nScie
 ntific workflows are becoming more complex. While previously computations 
 were focused only on a single computational domain, nowadays it is common 
 that users pursue the combination of traditional HPC simulations, together
  with High Performance Data Analytics and Machine Learning algorithms, whi
 ...\n\n\nRaül Sirvent (Barcelona Supercomputing Center)\n\nDomain: Chemist
 ry and Materials, Climate, Weather, and Earth Sciences, Applied Social Sci
 ences and Humanities, Engineering, Life Sciences, Physics, Computational M
 ethods and Applied Mathematics\n\nSession Chair: Benjamin Mintz (Oak Ridge
  National Laboratory)
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