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SUMMARY:The 18th Workshop on Workflows in Support of Large-Scale Science (
 WORKS23) - Part 2 of 2
DESCRIPTION:Wrap Up – Part II\n\nSilvina Caino-Lores (INRIA) and Anirban M
 andal (Renaissance Computing Institute (RENCI))\n---------------------\nDe
 livering Rules-Based Workflows for Science\n\nRules-based workflow schedul
 ing is a recently developed method for constructing an analysis structure,
  in a far more dynamic manner than traditional graph based systems. Howeve
 r, rules-based workflows are still in their relative infancy and lack the 
 breadth of features available in traditional scien...\n\n\nDavid Marchant,
  Mark Blomqvist, Philip Jensen, Iben Lilholm, and Martin Nørgaard (Univers
 ity of Copenhagen, Department of Computer Science)\n---------------------\
 nLeveraging Large Language Models to Build and Execute Computational Workf
 lows\n\nThe recent development of large language models (LLMs) with multi-
 billion parameters, coupled with the creation of user-friendly application
  programming interfaces (APIs), has paved the way for automatically genera
 ting and executing code in response to straightforward human queries. This
  paper explo...\n\n\nAlejandro Duque (Universidad San Francisco de Quito);
  Abdullah Syed (University of Missouri, Columbia); Kastan Day and Matthew 
 Berry (University of Illinois); and Daniel S. Katz and Volodymyr Kindraten
 ko (University of Illinois, National Center for Supercomputing Application
 s (NCSA))\n---------------------\nFAIRIST of Them All:  Meeting Researcher
 s Where They Are With Just-in-Time, FAIR Implementation Advice\n\nChristin
 e Kirkpatrick (San Diego Supercomputer Center (SDSC))\n-------------------
 --\nDistributed Data Locality-Aware Job Allocation\n\nScheduling tasks clo
 se to their associated data is crucial in distributed systems to minimize 
 network traffic and latency. Some Big Data frameworks like Apache Spark em
 ploy locality functions and job allocation algorithms to minimize network 
 traffic and execution times. However, these frameworks rel...\n\n\nAna Mar
 kovic, Dimitris Kolovos, and Leandro Soares Indrusiak (University of York,
  England)\n---------------------\nA Data Science Pipeline Synchronization 
 Method for Edge-Fog-Cloud Continuum\n\nThis paper presents an adaptive con
 tinuum synchronization method for data science pipelines deployed on edge-
 fog-cloud infrastructures. In a diagnostic phase, a model, based on the Be
 rnoulli principle, is used as an analogy to create a global representation
  of bottlenecks in a pipeline. In a supervi...\n\n\nDante D. Sanchez-Galle
 gos (University Carlos III of Madrid, Spain); J. L. Gonzalez-Compean (Cinv
 estav Tamaulipas); Jesus Carretero (University Carlos III of Madrid, Spain
 ); and Heidy Marin-Castro (Cátedras CONACYT - Universidad Autónoma de Tama
 ulipas)\n---------------------\nThe Common Workflow Scheduler Interface:  
 Status Quo and Future Plans\n\nNowadays, many scientific workflows from di
 fferent domains, such as Remote Sensing, Astronomy, and Bioinformatics, ar
 e executed on large computing infrastructures managed by resource managers
 .  Scientific workflow management systems (SWMS) support the workflow exec
 ution and communicate with the infr...\n\n\nFabian Lehmann (Humboldt-Unive
 rsität zu Berlin), Jonathan Bader (Berlin Institute of Technology), Laurit
 z Thamsen (University of Glasgow), and Ulf Leser (Humboldt-Universität zu 
 Berlin)\n---------------------\nWORKS23 – Morning Break\n-----------------
 ----\nScaling on Frontier:  Uncertainty Quantification Workflow Applicatio
 ns Using ExaWorks to Enable Full System Utilization\n\nWhen running at sca
 le, modern scientific workflows require middleware to handle allocated res
 ources, distribute computing payloads and guarantee a resilient execution.
  While individual steps might not require sophisticated control methods, b
 ringing them together as a whole workflow requires advanced...\n\n\nMikhai
 l Titov (Brookhaven National Laboratory); Robert Carson (Lawrence Livermor
 e National Laboratory (LLNL)); Matthew Rolchigo and John Coleman (Oak Ridg
 e National Laboratory (ORNL)); James Belak (Lawrence Livermore National La
 boratory (LLNL)); Matthew Bement (Oak Ridge National Laboratory (ORNL)); D
 aniel Laney (Lawrence Livermore National Laboratory (LLNL)); and Matteo Tu
 rilli and Shantenu Jha (Rutgers University, Brookhaven National Laboratory
 )\n---------------------\nTaskVine: Managing In-Cluster Storage for High-T
 hroughput Data Intensive Workflows\n\nMany scientific applications are exp
 ressed as high-throughput workflows that consist of large graphs of data a
 ssets and tasks to be executed on large parallel and distributed systems. 
 A challenge in executing these workflows is managing data: both datasets a
 nd software must be efficiently distribute...\n\n\nBarry Sly-Delgado, Than
 h Son Phung, Colin Thomas, David Simonetti, Andrew Hennessee, Ben Tovar, a
 nd Douglas Thain (University of Notre Dame)\n---------------------\nWelcom
 e - Part II\n\nSilvina Caino-Lores (INRIA) and Anirban Mandal (Renaissance
  Computing Institute (RENCI))\n---------------------\nThe 18th Workshop on
  Workflows in Support of Large-Scale Science (WORKS23)\n\nScientific workf
 lows have underpinned some of the most significant discoveries of the past
  several decades. Workflow management systems provide abstraction and auto
 mation which enable a broad range of researchers to easily define sophisti
 cated computational processes and to then execute them efficie...\n\n\nAni
 rban Mandal (Renaissance Computing Institute (RENCI)) and Silvina Caino-Lo
 res (French Institute for Research in Computer Science and Automation (INR
 IA))\n---------------------\nFluxion:  A Scalable Graph-Based Resource Mod
 el for HPC Scheduling Challenges\n\nThe current era of exascale supercompu
 ting and the emergence of a computing continuum present several significan
 t resource management challenges. These include, but are not limited to, m
 anagement of complex scientific workflows, diverse resources such as power
 , elasticity in user jobs, and converged...\n\n\nTapasya Patki (Lawrence L
 ivermore National Laboratory (LLNL)); Dong Ahn (NVIDIA Corporation); Danie
 l Milroy, Jae-Seung Yeom, Jim Garlick, and Mark Grondona (Lawrence Livermo
 re National Laboratory (LLNL)); Stephen Herbein (NVIDIA Corporation); and 
 Thomas Scogland (Lawrence Livermore National Laboratory (LLNL))\n---------
 ------------\nJulia as a Unifying End-to-End Workflow Language on the Fron
 tier Exascale System\n\nWe evaluate Julia as a single language and ecosyst
 em paradigm powered by LLVM to develop workflow components for high-perfor
 mance computing. We run a Gray-Scott, 2-variable diffusion-reaction applic
 ation using a memory-bound, 7-point stencil kernel on Frontier, the US Dep
 artment of Energy's first ex...\n\n\nWilliam Godoy, Pedro Valero-Lara, Cai
 ra Anderson, Katrina Lee, Ana Gainaru, Rafael Ferreira da Silva, and Jeffr
 ey Vetter (Oak Ridge National Laboratory (ORNL))\n\nTag: Data Analysis, Vi
 sualization, and Storage, Large Scale Systems, Programming Frameworks and 
 System Software, Reproducibility, Resource Management, Runtime Systems\n\n
 Registration Category: Workshop Reg Pass\n\nSession Chairs: Silvina Caino-
 Lores (National Institute for Research in Digital Science and Technology (
 Inria)) and Anirban Mandal (Renaissance Computing Institute (RENCI), Unive
 rsity of North Carolina at Chapel Hill)
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