Parsl: Enabling Scalable Interactive Computing in Python

Scientists and engineers like to use Python for interactive data science, machine learning, and online computing. However, computations that are simple to perform at small scales (e.g., on a laptop) can easily become prohibitively difficult as data sizes and analysis complexity grows. For example, efficient interactive analysis at scale can require real-time management of parallel and/or cloud computing resources, orchestration of remote task execution, and data staging across wide area networks. In this talk we introduce Parsl (Parallel Scripting Library), a pure Python library for orchestrating the concurrent and parallel execution of interactive and many-task workloads, and demonstrate how it integrates with the scientific Python ecosystem and how it is being used in a variety of scientific domains. The talk is intended for attendees interested in interactive and parallel computing.

 Speaker: Kyle Chard, Computation Institute, University of Chicago and Argonne National Lab
 Speaker: Yadu Babuji, University of Chicago
 Speaker: Ian Foster, University of Chicago and Argonne National Laboratory
 Speaker: Daniel Katz, University of Illinois at Urbana-Champaign
 Speaker: Mike Wilde, University of Chicago
 Speaker: Anna Woodard, University of Chicago
 Speaker: Justin Wozniak, Argonne National Laboratory