NVIDIA has announced plans to develop specific areas of the weather forecasting market that aligns with Tempo Quest, and has proclaimed that Tempo Quest is the best in the world at accelerating WRF. NVIDIA has declared Tempo Quest as NVIDIA’s exclusive accelerated WRF developer.
In November, 2018, NVIDIA CEO, Jensen Huang, revealed his organization’s focus on WRF:
Jensen Huang told the audience and countless thousands online (the video has now been viewed millions of times) that NVIDIA could now deliver “1 kilometer weather simulation in one box.” Mr. Huang emphasized that weather forecasting “has to be super real-time because that’s one of the criteria in predicting the future” and that “you have to be a time traveler to predict the future.
TempoQuest is accelerating WRF up to 700% and delivering 1km resolution.
Thank you for recent information regarding the next phase of your business plan. Following the discussions with TempoQuest executives and review of your past accomplishments, NVIDIA would like to express our interest and support for the TQI CUDA WRF project. NVIDIA considers WRF the most important numerical weather prediction and regional climate model worldwide, and we are very excited at the possibility of WRF software that will enable new markets that benefit from high-fidelity, scale-resolving simulations owing to GPU technology.
With the introduction of the general purpose Graphics Processing Unit (GPU) in 2004, NVIDIA set a milestone in high performance computing. Since then, NVIDIA expertise developed in programmable GPUs has led to breakthroughs in parallel computing, while also providing cost-efficient HPC solutions. NVIDIA would like to offer this expertise and other resources to ensure success in the CUDA WRF project.
NVIDIA would like to contribute to the CUDA WRF project with providing the following resources:
- Seed-GPU technology of the latest NVIDIA Tesla’s to TQI partners, SSEC and Hyper Sensing, LLC for local WRF development purposes
- Providing TQI partners with remote access to the large GPU cluster at NVIDIA Santa Clara for performance testing
- Technical guidance to TQI partners on applications engineering from the NVIDIA Developer Technology group
- Technical support TQI partners on hardware and software technology; cluster access and use; bug fix support
- Marketing, sales, and distribution support of CUDA WRF through an alliance led by TQI business objectives
NVIDIA are interested in this project in two respects. We are generally interested in supporting innovative and promising approaches to demonstrating capabilities of GPU technology to relevant real-life applications. Further, NVIDIA have interest in the experiences to be gained with implementing an optimized GPU-based WRF that can apply to a global advancement of weather and climate prediction.
Thank you for the opportunity for NVIDIA to participate in this collaboration with TempoQuest.
by: Gene Pache
Anyone concerned about weather forecasts, which is all of us, wants to know if it is possible to obtain more accurate forecasts faster. The National Weather service has made progress in the area of hail versus rain and the movement of thunderstorms. Noteworthy improvements have been made as a result of the 160 doppler radars located throughout the US. The dual polarization doppler radars are able to distinguish precipitation types. These radars enable more accurate forecasting of hail embedded in thunderstorms.
Doppler radar is an outstanding technology. But how do we achieve an order of magnitude improvement in accuracy and speed of weather forecasts? To attain an order of magnitude improvement in speed and accuracy of a regional weather forecast three elements have to be improved.
The three elements are:
(1) The weather model used to develop the forecast
(2) The accuracy of the “Initial Condition” of the atmosphere – the starting point
(3) Computing capability – the number of calculations per second available
All three elements are necessary to create a forecast. The weather models comprised of lines of code enable physical laws governing atmospheric motion, chemical reactions and other relationships to be applied to the initial condition of the atmosphere. The atmosphere’s “initial condition” is derived from the sensor dated collected and assimilated prior to beginning the forecast run. The weather forecasting model, with the initial conditions, is then run on high performance super computers with the capacity to perform trillions of calculations per second. The hardest element to improve with a given operating budget is element number three, computing capability.
To accelerate forecasting requires greater and greater numbers of CPUs. This significantly increases hardware costs. The greater CPU numbers also increase the cost of power and cooling.
One solution to the computing calculation capability problem is to use NVIDIA™ GPUs, graphic processing units. NVIDIA™ GPUs provide much greater calculating capability at far lower hardware and operating cost.
It is the solution TempoQuest is adopting.
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