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Improving Uintah's Scalability Through the Use of Portable Kokkos-Based Data Parallel Tasks

Conference ·
 [1];  [2];  [3];  [2]
  1. Univ. of Utah, Salt Lake City, UT (United States); University of Utah
  2. Univ. of Utah, Salt Lake City, UT (United States)
  3. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
The University of Utah’s Carbon Capture Multidisciplinary Simulation Center (CCMSC) is using the Uintah Computational Framework to predict performance of a 1000 MWe ultra-supercritical clean coal boiler. The center aims to utilize the Intel Xeon Phi-based DOE systems, Theta and Aurora, through the Aurora Early Science Program by using the Kokkos C++ library to enable node-level performance portability. This paper describes infrastructure advancements and portability improvements made possible by the integration of Kokkos within Uintah. This integration marks a step towards consolidating Uintah’s MPI+PThreads and MPI+CUDA hybrid parallelism approaches into a single MPI+Kokkos approach. Scalability results are presented that compare serial and data parallel task execution models for a challenging radiative heat transfer calculation, central to the center’s predictive boiler simulations. Here, these results demonstrate both good strong-scaling characteristics to 256 Knights Landing (KNL) processors on the NSF Stampede system, and show the KNL-based calculation to compete with prior GPU-based results for the same calculation.
Research Organization:
Univ. of Utah, Salt Lake City, UT (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA)
DOE Contract Number:
NA0002375
OSTI ID:
1582430
Country of Publication:
United States
Language:
English

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