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DTSTART;TZID=America/New_York:20241118T112100
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UID:submissions.supercomputing.org_SC24_sess756_ws_worksp114@linklings.com
SUMMARY:Parsl+CWL: Towards Combining the Python and CWL Ecosystems
DESCRIPTION:Nishchay Karle (University of Chicago, Globus); Ben Clifford (
 Hawaga); Yadu Babuji (Globus, University of Chicago); Ryan Chard (Argonne 
 National Laboratory (ANL)); Daniel S. Katz (University of Illinois Urbana-
 Champaign); and Kyle Chard (Globus, University of Chicago)\n\nCommon Workf
 low Language (CWL) is a widely adopted language for defining and sharing c
 omputational workflows. It is designed to be independent of the execution 
 engine on which workflows are executed. Here, we describe our experiences 
 integrating CWL with Parsl, a Python-based parallel programming library de
 signed to manage execution of workflows across diverse computing environme
 nts. \n\nWe propose a new method that converts CWL CommandLineTool definit
 ions into Parsl apps, enabling Parsl scripts to easily import and use tool
 s represented in CWL. We describe a Parsl runner capable of executing a CW
 L CommandLineTool directly. We also describe a proof-of-concept extension 
 to support inline Python in a CWL workflow definition, enabling seamless u
 se in Parsl's Python ecosystem. We demonstrate benefits of this integratio
 n by presenting example CWL CommandLineTool definitions that show how they
  can be used in Parsl, and comparing performance of executing an image pro
 cessing workflow using Parsl-CWL and other CWL runners.\n\nTag: Applicatio
 ns and Application Frameworks, Distributed Computing, Middleware and Syste
 m Software\n\nRegistration Category: Workshop Reg Pass\n\nSession Chairs: 
 Silvina Caino-Lores (French Institute for Research in Computer Science and
  Automation (INRIA)) and Anirban Mandal\n\n
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