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LOCATION:Track 9
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UID:submissions.supercomputing.org_SC20_sess196@linklings.com
SUMMARY:WORKS20: 15th Workshop on Workflows in Support of Large-Scale Scie
 nce
DESCRIPTION:Workshop\n\nWORKS20 – Closing Remarks\n\nFerreira da Silva, Fi
 lgueira\n\n---------------------\nWORKS20 – Break\n\n\n\n-----------------
 ----\nWORKS20 – Introduction: 15th Workshop on Workflows in Support of Lar
 ge-Scale Science\n\nFerreira da Silva, Filgueira\n\nScientific workflows h
 ave been almost universally used across scientific domains and have underp
 inned some of the most significant discoveries of the past several decades
 . Workflow management systems (WMSs) provide abstraction and automation wh
 ich enable a broad range of researchers to easily define...\n\n-----------
 ----------\nWORKS20 – Introductory Remarks\n\nFerreira da Silva, Filgueira
 \n\n---------------------\nCharacterizing Scientific Workflows on HPC Syst
 ems Using Logs\n\nGhoshal, Austin, Bard, Daley, Lockwood...\n\nScientific 
 advances depend on the ability to effectively and efficiently use high per
 formance computing (HPC) systems to manage and run large, complex scientif
 ic workflows.  Toward understanding the characteristics of these large sci
 entific workflows, we propose two methods to identify workflows wit...\n\n
 ---------------------\nWorkflowHub: Community Framework for Enabling Scien
 tific Workflow Research and Development\n\nFerreira da Silva, Pottier, Col
 eman, Deelman, Casanova\n\nScientific workflows are a cornerstone of moder
 n scientific computing. They are used to describe complex computational ap
 plications that require efficient and robust management of large volumes o
 f data, which are typically stored/processed at heterogeneous, distributed
  resources. The workflow resear...\n\n---------------------\nWORKS20 – Bre
 ak\n\n\n\n---------------------\nWORKS20 – Break\n\n\n\n------------------
 ---\nWORKS20 – Keynote: In Situ Data Analytics for Next Generation Molecul
 ar Dynamics Workflows\n\nTaufer\n\n---------------------\nWorkflow Generat
 ion with wfGenes\n\nRoozmeh, Kondov\n\nPerforming simulation and data anal
 ysis on supercomputers requires using workflow management systems (WMSs). 
  Due to the high diversity of application requirements, there are currentl
 y many different WMSs in use with very different input languages and enact
 ment mechanisms.  This hinders the reuse of...\n\n---------------------\nW
 ORKS20 – Break\n\n\n\n---------------------\nRuntime vs Scheduler: Analyzi
 ng Dask's Overheads\n\nBöhm, Beránek\n\nDask is a distributed task framewo
 rk which is commonly used by data scientists to parallelize Python code on
  computing clusters with little programming effort. It uses a sophisticate
 d work-stealing scheduler which has been hand-tuned to execute task graphs
  as efficiently as possible. But is schedule...\n\n---------------------\n
 Enabling Discoverable Trusted Services for Highly Dynamic Decentralized Wo
 rkflows\n\nBarclay, Simpkin, Bent, La Porta, Millar...\n\nFifth generation
  (5G) mobile networks will revolutionize edge-based computing by providing
  fast and reliable network capabilities to remote sensors, devices, and mi
 croservices. This heralds new opportunities for researchers, allowing remo
 te instrumentation and analytic capabilities to be as accessib...\n\n-----
 ----------------\nSupercomputing with MPI Meets the CommonWorkflow Languag
 e Standards: An Experience Report\n\nNash, Brown, Crusoe, Kontak\n\nUse of
  standards-based workflows is still somewhat unusual by high-performance c
 omputing users. In this paper we describe the experience of using the Comm
 on Workflow Language (CWL) standards to describe the execution, in paralle
 l, of MPI-parallelised applications. In particular, we motivate and desc..
 .\n\n---------------------\nApplying Workflows to Scientific Projects Repr
 esented in File System Directory Tree\n\nMakuch, Malawski, Kocot, Szepieni
 ec\n\nMost workflow management systems represent scientific workflows as D
 AG (directed acyclic graph) and require to provide a workflow specificatio
 n before the workflow can be executed. Workflow can be designed using a gr
 aphical interface or with textual workflow editing. For uses unacquainted 
 with workf...\n\n---------------------\nAdaptive Optimizations for Stream-
 Based Workflows\n\nLiang, Filgueira, Yan\n\nThis work presents three new a
 daptive optimization techniques to maximize the performance of dispel4py w
 orkflows.  dispel4py is a parallel Python-based stream-oriented dataflow f
 ramework that acts as a bridge to existing parallel programming frameworks
  like MPI or Python multiprocessing.  When a use...\n\n\nTag: Scientific C
 omputing, Workflows\n\nRegistration Category: Workshop Reg Pass
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