Assessing Kokkos Performance on Selected Architectures

  • Chang PhuongEmail author
  • Noman Saied
  • Craig Tanis
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1087)


Performance Portability frameworks allow developers to write code for familiar High-Performance Computing (HPC) architecture and minimize development effort over time to port it to other HPC architectures with little to no loss of performance. In our research, we conducted experiments with the same codebase on a Serial, OpenMP, and CUDA execution and memory space and compared it to the Kokkos Performance Portability framework. We assessed how well these approaches meet the goals of Performance Portability by solving a thermal conduction model on a 2D plate on multiple architectures (NVIDIA (K20, P100, V100, XAVIER), Intel Xeon, IBM Power 9, ARM64) and collected execution times (wall-clock) and performance counters with perf and nvprof for analysis. We used the Serial model to determine a baseline and to confirm that the model converges on both the native and Kokkos code. The OpenMP and CUDA models were used to analyze the parallelization strategy as compared to the Kokkos framework for the same execution and memory spaces.


Performance Portability OpenMP CUDA Kokkos High-Performance Computing HPC Parallel programming 


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.University of TennesseeChattanoogaUSA

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