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:20260422T000620Z
LOCATION:501-502
DTSTART;TZID=America/Denver:20231112T140000
DTEND;TZID=America/Denver:20231112T173000
UID:submissions.supercomputing.org_SC23_sess439@linklings.com
SUMMARY:The 18th Workshop on Workflows in Support of Large-Scale Science (
 WORKS23) - Part 1 of 2
DESCRIPTION:Laminar: A New Serverless Stream-Based Framework with Semantic
  Code Search and Code Completion\n\nThis paper introduces Laminar, a novel
  serverless framework based on dispel4py, a parallel stream-based dataflow
  library. Laminar efficiently manages streaming workflows and components t
 hrough a dedicated registry, offering a seamless serverless experience. Le
 veraging large language models, Laminar ...\n\n\nZaynab Zahra, Zihao Li, a
 nd Rosa Filgueira (University of St Andrews, Scotland)\n------------------
 ---\nScale Composite BaaS Services with AFCL Workflows\n\nDue to various r
 estrictions in serverless computing, developers face significant challenge
 s to pipeline multiple Backend-as-a-Service (BaaS) services, which is rest
 ricted by the maximum size of the serverless function’s deployment package
 , or by throughput and concurrency restrictions for func...\n\n\nThomas La
 rcher and Sashko Ristov (University of Innsbruck)\n---------------------\n
 End-to-End Workflows for Climate Science:  Integrating HPC Simulations, Bi
 g Data Processing, and Machine Learning\n\nCurrent scientific workflow sys
 tems do not typically integrate simulation-centric and data-centric aspect
 s due to their very different software/infrastructure requirements. A tran
 sparent integration of such components into a single end-to-end workflow w
 ould lead to a more efficient and automated way...\n\n\nDonatello Elia and
  Sonia Scardigno (Fondazione Centro Euro-Mediterraneo sui Cambiamenti Clim
 atici); Jorge Ejarque (Barcelona Supercomputing Center (BSC)); Alessandro 
 D’Anca, Gabriele Accarino, Enrico Scoccimarro, Davide Donno, and Daniele P
 eano (Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici); and 
 Francesco Immorlano and Giovanni Aloisio (Fondazione Centro Euro-Mediterra
 neo sui Cambiamenti Climatici; Department of Innovation Engineering, Unive
 rsity of Salento)\n---------------------\nWrap Up – Part I\n\nSilvina Cain
 o-Lores (French Institute for Research in Computer Science and Automation 
 (INRIA)) and Anirban Mandal (Renaissance Computing Institute (RENCI))\n---
 ------------------\nPatterns and Anti-Patterns in Migrating from Legacy Wo
 rkflows to Workflow Management Systems\n\nPatterns and Anti-Patterns in Mi
 grating from Legacy Workflows to Workflow Management Systems\n\n\nDaniela 
 Cassol, Jeff Froula, Edward Kirton, Seung-Jin Sul, Mario Melara, Ramani Ko
 thadia, Elais Player, Setareh Sarrafan, Stephen Chan, and Kjiersten Fagnan
  (Lawrence Berkeley National Laboratory (LBNL))\n---------------------\nTr
 anscriptomics Atlas Pipeline:  Cloud vs HPC\n\nTranscriptomics studies the
  RNA present in a specific cell or tissue at a given time or condition. Th
 is dependence on time makes the problem computationally challenging, as th
 e data generated by transcriptomics experiments is larger than the genomic
 s studies on DNA sequences. The goal of the Transcr...\n\n\nPiotr Kica (Sa
 no Centre for Computational Medicine, Krakow, Poland; AGH University of Sc
 ience and Technology, Krakow, Poland); Sabina Lichołai (Sano Centre for Co
 mputational Medicine, Krakow, Poland); and Maciej Malawski (Sano Centre fo
 r Computational Medicine, Krakow, Poland; AGH University of Science and Te
 chnology, Krakow, Poland)\n---------------------\nWorkflow Building Blocks
 : The Success Story of Environmental Modeling, HPC, and AI for Predicting 
 Farmed Seafood Bacteria Contamination\n\nRaffaele Montella (University of 
 Napoli Parthenope)\n---------------------\nWelcome – Part I\n\nSilvina Cai
 no-Lores (French Institute for Research in Computer Science and Automation
  (INRIA)) and Anirban Mandal (Renaissance Computing Institute (RENCI))\n--
 -------------------\nOptimization Toward Efficiency and Stateful of dispel
 4py\n\nScientific workflows bridge scientific challenges with computationa
 l resources. While dispel4py, a stream-based workflow system, offers mappi
 ngs to parallel enactment engines like MPI or Multiprocessing, its optimiz
 ation primarily focuses on dynamic process-to-task allocation for improved
  performanc...\n\n\nLiang Liang (Imperial College, London); Heting Zhang (
 University of St Andrews, Scotland); Guang Yang and Thomas Heinis (Imperia
 l College, London); and Rosa Filgueira (University of St Andrews, Scotland
 )\n---------------------\nA Systematic Mapping Study of Italian Research o
 n Workflows\n\nAn entire ecosystem of methodologies and tools revolves aro
 und scientific workflow management. They cover crucial non-functional requ
 irements that standard workflow models fail to target, such as interactive
  execution, energy efficiency, performance portability, Big Data managemen
 t, and intelligent ...\n\n\nMarco Aldinucci (University of Turin), Elena B
 aralis (Polytechnic University of Turin), Valeria Cardellini (University o
 f Rome Tor Vergata), Iacopo Colonnelli (University of Turin), Marco Danelu
 tto (University of Pisa), Sergio Decherchi (Fondazione Istituto Italiano d
 i Tecnologia), Giuseppe Di Modica (University of Bologna), Luca Ferrucci (
 University of Pisa), Marco Gribaudo (Polytechnic University of Milan), Fra
 ncesco Iannone (ENEA HPC laboratory), Marco Lapegna (University of Naples 
 Federico II), Doriana Medic (University of Turin), Giuseppa Muscianisi (CI
 NECA), Francesca Righetti (University of Pisa), Eva Sciacca (National Inst
 itute for Astrophysics), Nicola Tonellotto (University of Pisa), Mauro Tor
 tonesi (University of Ferrara), Paolo Trunfio (University of Calabria), an
 d Tullio Vardanega (University of Padua)\n---------------------\nThe 18th 
 Workshop on Workflows in Support of Large-Scale Science (WORKS23)\n\nScien
 tific workflows have underpinned some of the most significant discoveries 
 of the past several decades. Workflow management systems provide abstracti
 on and automation which enable a broad range of researchers to easily defi
 ne sophisticated computational processes and to then execute them efficie.
 ..\n\n\nAnirban Mandal (Renaissance Computing Institute (RENCI)) and Silvi
 na Caino-Lores (French Institute for Research in Computer Science and Auto
 mation (INRIA))\n---------------------\nWORKS23 – Afternoon Break\n-------
 --------------\nAccelerating Data-Intensive Seismic Research Through Paral
 lel Workflow Optimization and Federated Cyberinfrastructure\n\nEarthquake 
 early warning systems use synthetic data from simulation frameworks like M
 udPy to train models for predicting the magnitudes of large earthquakes. M
 udPy, although powerful, has limitations: a lengthy simulation time to gen
 erate the required data, lack of user-friendliness, and no platform...\n\n
 \nMarcus Adair, Ivan Rodero, and Manish Parashar (University of Utah; Univ
 ersity of Utah, Scientific Computing and Imaging Institute (SCI)) and Dieg
 o Melgar (University of Oregon)\n\nTag: Applications, Cloud Computing, Dis
 tributed Computing, Edge Computing, Large Scale Systems\n\nRegistration Ca
 tegory: Workshop Reg Pass\n\nSession Chairs: Silvina Caino-Lores (National
  Institute for Research in Digital Science and Technology (Inria)) and Ani
 rban Mandal (Renaissance Computing Institute (RENCI), University of North 
 Carolina at Chapel Hill)
END:VEVENT
END:VCALENDAR