• Corpus ID: 234680952

Toward Real-time Analysis of Experimental Science Workloads on Geographically Distributed Supercomputers

  title={Toward Real-time Analysis of Experimental Science Workloads on Geographically Distributed Supercomputers},
  author={Michael A. Salim and Thomas D. Uram and J. Taylor Childers and Venkatram Vishwanath and Michael E. Papka},
Massive upgrades to science infrastructure are driving data velocities upwards while stimulating adoption of increasingly dataintensive analytics. While next-generation exascale supercomputers promise strong support for I/O-intensive workflows, HPC remains largely untapped by live experiments, because data transfers and disparate batch-queueing policies are prohibitive when faced with scarce instrument time. To bridge this divide, we introduce Balsam: a distributed orchestration platform… 
Intelligent Resolution: Integrating Cryo-EM with AI-driven Multi-resolution Simulations to Observe the SARS-CoV-2 Replication-Transcription Machinery in Action
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Evaluating the capabilities of elastic containers and their usefulness for scientific computing in the scientific workflow paradigm using AWS Fargate and Google Cloud Run infrastructures shows that serverless containers can be successfully utilized for running scientific workflows.
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  • B. Enders, D. Bard, +20 authors Gabor Torok
  • Computer Science
    2020 IEEE/ACM 2nd Annual Workshop on Extreme-scale Experiment-in-the-Loop Computing (XLOOP)
  • 2020
Recent innovations in the Superfacility project are reported, including advanced data management, API-based automation, real-time interactive user interfaces, and supported infrastructure for “edge” services.
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Exploding data volumes and velocities, new computational methods and platforms, and ubiquitous connectivity demand new approaches to computation in the sciences. These new approaches must enable
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  • K. Chard, I. Foster
  • Computer Science
    2019 15th International Conference on eScience (eScience)
  • 2019
To demonstrate how serverless computing can transform scientific computing, three serverless Computing models are described: service-oriented computing, research automation, and function as a service, presenting illustrative case studies for each.