Cumulvs: Interacting with High-Performance Scientific Simulations, for Visualization, Steering and Fault Tolerance

  • Authors:

  • James A. Kohl;Torsten Wilde;David E. Bernholdt

  • Affiliations:

  • COMPUTER SCIENCE AND MATHEMATICS, OAK RIDGE NATIONAL LABORATORY OAK RIDGE, TN 37831-6016, USA;-;COMPUTER SCIENCE AND MATHEMATICS, OAK RIDGE NATIONAL LABORATORY OAK RIDGE, TN 37831-6016, USA

  • Venue:
  • International Journal of High Performance Computing Applications
  • Year:
  • 2006

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Abstract

High-performance computer simulations are an increasingly popular alternative or complement to physical experiments or prototypes. However, as these simulations grow more massive and complex, it becomes challenging to monitor and control their execution. CUMULVS is a middleware infrastructure for visualizing and steering scientific simulations while they are running. Front-end "viewers" attach dynamically to simulation programs, to extract and collect intermediate data values, even if decomposed over many parallel tasks. These data can be graphically viewed or animated in a variety of commercial or custom visualization environments using a provided viewer library. In response to this visual feedback, scientists can "close the loop" and apply interactive control using computational steering of any user-defined algorithmic or model parameters. The data identification interfaces and gathering protocols can also be applied for parallel data exchange in support of coupled simulations, and for application-directed collection of key program data in checkpoints, for automated restart in response to software or hardware failures. CUMULVS was originally based on PVM, but interoperates well with simulations that use MPI or other parallel environments. Several alternate messaging systems are being integrated with CUMULVS to ease its applicability, e.g. to MPI. CUMULVS has recently been integrated with the Common Component Architecture (CCA) for visualization and parallel data redistribution (referred to as "MxN"), and also with Global Arrays. This paper serves as a comprehensive overview of the CUMULVS capabilities, their usage, and their development over several years.