Parallelization and Performance of the NIM Weather Model on CPU, GPU, and MIC Processors
| Autor: | Tom Henderson, Ning Wang, Alexander E. MacDonald, Antonio Duarte, Jim Rosinski, Jacques Middlecoff, Paul Madden, Mark Govett, Julie Schramm, Jin Lee |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
020203 distributed computing
Atmospheric Science 010504 meteorology & atmospheric sciences Computer science Fortran Graphics processing unit Multiprocessing 02 engineering and technology Parallel computing 01 natural sciences CUDA Scalability 0202 electrical engineering electronic engineering information engineering Code (cryptography) Central processing unit computer Xeon Phi 0105 earth and related environmental sciences computer.programming_language |
| Zdroj: | Bulletin of the American Meteorological Society. 98:2201-2213 |
| ISSN: | 1520-0477 0003-0007 |
| DOI: | 10.1175/bams-d-15-00278.1 |
| Popis: | The design and performance of the Non-Hydrostatic Icosahedral Model (NIM) global weather prediction model is described. NIM is a dynamical core designed to run on central processing unit (CPU), graphics processing unit (GPU), and Many Integrated Core (MIC) processors. It demonstrates efficient parallel performance and scalability to tens of thousands of compute nodes and has been an effective way to make comparisons between traditional CPU and emerging fine-grain processors. The design of the NIM also serves as a useful guide in the fine-grain parallelization of the finite volume cubed (FV3) model recently chosen by the National Weather Service (NWS) to become its next operational global weather prediction model. This paper describes the code structure and parallelization of NIM using standards-compliant open multiprocessing (OpenMP) and open accelerator (OpenACC) directives. NIM uses the directives to support a single, performance-portable code that runs on CPU, GPU, and MIC systems. Performance results are compared for five generations of computer chips including the recently released Intel Knights Landing and NVIDIA Pascal chips. Single and multinode performance and scalability is also shown, along with a cost–benefit comparison based on vendor list prices. |
| Databáze: | OpenAIRE |
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