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GTC ON-DEMAND

Presentation
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Abstract:
We'll discuss the revolution in computing, modeling, data handling and software development that's needed to advance U.S. weather-prediction capabilities in the exascale computing era. Creating prediction models to cloud-resolving 1 KM-resolution scales will require an estimated 1,000-10,000 times more computing power, but existing models can't exploit exascale systems with millions of processors. We'll examine how weather-prediction models must be rewritten to incorporate new scientific algorithms, improved software design, and use new technologies such as deep learning to speed model execution, data processing, and information processing. We'll also offer a critical and visionary assessment of key technologies and developments needed to advance U.S. operational weather prediction in the next decade.
We'll discuss the revolution in computing, modeling, data handling and software development that's needed to advance U.S. weather-prediction capabilities in the exascale computing era. Creating prediction models to cloud-resolving 1 KM-resolution scales will require an estimated 1,000-10,000 times more computing power, but existing models can't exploit exascale systems with millions of processors. We'll examine how weather-prediction models must be rewritten to incorporate new scientific algorithms, improved software design, and use new technologies such as deep learning to speed model execution, data processing, and information processing. We'll also offer a critical and visionary assessment of key technologies and developments needed to advance U.S. operational weather prediction in the next decade.  Back
 
Topics:
Climate, Weather & Ocean Modeling, AI & Deep Learning Research, HPC and AI
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9750
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Abstract:

In an era defined by increasing diversity in computing architectures, performance portability is a key requirement for weather and climate applications that require massive computing resources. In this talk, you will learn about how we developed and achieve performance on CPU, GPU and MIC architectures using industry-standard OpenACC and OpenMP directives. Performance results from the NIM weather model will be shown for a number of device, node and multi-node and system configurations. Further, communications optimizations will highlight a more than a 40% improvement in runtime with scaling to thousands of GPUs.

In an era defined by increasing diversity in computing architectures, performance portability is a key requirement for weather and climate applications that require massive computing resources. In this talk, you will learn about how we developed and achieve performance on CPU, GPU and MIC architectures using industry-standard OpenACC and OpenMP directives. Performance results from the NIM weather model will be shown for a number of device, node and multi-node and system configurations. Further, communications optimizations will highlight a more than a 40% improvement in runtime with scaling to thousands of GPUs.

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Topics:
Climate, Weather & Ocean Modeling, Programming Languages, HPC and Supercomputing
Type:
Talk
Event:
GTC Silicon Valley
Year:
2016
Session ID:
S6117
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Abstract:
The Non-hydrostatic Icosahedral Model (NIM) is a next-generation global weather model being developed at NOAA to improve 0-100 day weather predictions. Since development began in 2008, the model has been designed to run on highly parallel computer architectures such as GPUs. GPU parallelization has relied on the directive-based Fortran-to-CUDA ACCelerator (F2C-ACC) compiler developed at NOAA. Recent work has focused on parallelization of model physics, evaluating the openACC compilers, and preparing the model to run at the full 3.5KM resolution on 5000 nodes of Titan. This talk will report on the development of the NIM model, describe our efforts to improve parallel performance on Titan, and report on our experiences using the openACC compilers.
The Non-hydrostatic Icosahedral Model (NIM) is a next-generation global weather model being developed at NOAA to improve 0-100 day weather predictions. Since development began in 2008, the model has been designed to run on highly parallel computer architectures such as GPUs. GPU parallelization has relied on the directive-based Fortran-to-CUDA ACCelerator (F2C-ACC) compiler developed at NOAA. Recent work has focused on parallelization of model physics, evaluating the openACC compilers, and preparing the model to run at the full 3.5KM resolution on 5000 nodes of Titan. This talk will report on the development of the NIM model, describe our efforts to improve parallel performance on Titan, and report on our experiences using the openACC compilers.  Back
 
Topics:
Climate, Weather & Ocean Modeling
Type:
Talk
Event:
GTC Silicon Valley
Year:
2014
Session ID:
S4157
Streaming:
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Abstract:

Two U.S. global-scale weather models, developed at NOAA, are running on GPUs. The FIM runs at 15 KM resolution and is expected to be run by the U.S. National Weather Service in the next year. The NIM is a next-generation forecast model designed to run at 4KM resolution. This presentation will give an update on our efforts to parallelize and run these models on GPUs.

Two U.S. global-scale weather models, developed at NOAA, are running on GPUs. The FIM runs at 15 KM resolution and is expected to be run by the U.S. National Weather Service in the next year. The NIM is a next-generation forecast model designed to run at 4KM resolution. This presentation will give an update on our efforts to parallelize and run these models on GPUs.

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Topics:
Climate, Weather & Ocean Modeling, HPC and Supercomputing
Type:
Talk
Event:
GTC Silicon Valley
Year:
2013
Session ID:
SC2018
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Abstract:

Two U.S. global-scale weather models, developed at NOAA, are running on GPUs. The FIM runs at 15 KM resolution and is expected to be run by the U.S. National Weather Service in the next year. The NIM is a next-generation forecast model designed to run at 4KM resolution. This presentation will give an update on our efforts to parallelize and run these models on GPUs.

Two U.S. global-scale weather models, developed at NOAA, are running on GPUs. The FIM runs at 15 KM resolution and is expected to be run by the U.S. National Weather Service in the next year. The NIM is a next-generation forecast model designed to run at 4KM resolution. This presentation will give an update on our efforts to parallelize and run these models on GPUs.

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Topics:
Climate, Weather & Ocean Modeling
Type:
Talk
Event:
Supercomputing
Year:
2012
Session ID:
SC2018
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Speakers:
Mark Govett
- National Oceanic and Atmospheric Administration
 
Topics:
Climate, Weather & Ocean Modeling
Type:
Talk
Event:
Supercomputing
Year:
2011
Session ID:
SC134
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Speakers:
Mark Govett
- National Oceanic and Atmospheric Administration
 
Topics:
Tools & Libraries
Type:
Talk
Event:
Supercomputing
Year:
2010
Session ID:
SC1024
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Speakers:
Mark Govett
- NOAA Earth System Research Laboratory
Abstract:
We are using GPUs to run a new weather model being developed at NOAA's Earth System Research Laboratory (ESRL) called the Non-hydrostatic Icosahedral Model (NIM). NIM is slated to run at high resolution (4km global scale) within two years. This presentation will highlight work required to parallelize and run the NIM. We will describe progress running on multiple GPUs, report on our evaluation of two FORTRAN GPU compilers, and give performance updates of NIM using Fermi. We will also discuss special challenges developing and running operational weather models on GPUs.
We are using GPUs to run a new weather model being developed at NOAA's Earth System Research Laboratory (ESRL) called the Non-hydrostatic Icosahedral Model (NIM). NIM is slated to run at high resolution (4km global scale) within two years. This presentation will highlight work required to parallelize and run the NIM. We will describe progress running on multiple GPUs, report on our evaluation of two FORTRAN GPU compilers, and give performance updates of NIM using Fermi. We will also discuss special challenges developing and running operational weather models on GPUs.  Back
 
Topics:
General Interest
Type:
Talk
Event:
GTC Silicon Valley
Year:
2010
Session ID:
SC1024
Streaming:
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