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This is a fantastic answer. Could you or anyone else please point me to any examples of trying to run high-resolution weather forecasting, such as COAMPS [0] or

• scott_s 10y ago
  Googling turns up some hits, but not much. The basic issue is that weather prediction is one of those problems that can always use more computational power. It is even a known problem that the models used by the National Weather Service are inferior to the models used by agencies in Europe, and one of the things holding us back is raw computational power. From "Why Isn't the U.S. Better at Prediction Extreme Weather?" (http://www.nytimes.com/2016/10/23/magazine/why-isnt-the-us-better-at-predicting-extreme-weather.html?_r=0 http://www.nytimes.com/2016/10/23/magazine/why-isnt-the-us-b...): While Mass is the most outspoken on the subject, many experts insist that if the Weather Service wants to meaningfully improve its predictions, it must employ a technique called ensemble forecasting. The basic premise is either to tweak the physics equations or to make repeated changes to a model’s variables: You might bump up the temperature slightly, for example, and then run the model again. After a half-dozen or so reruns, you get a set, or “ensemble,” of forecasts that can be compared with one another. When all the forecasts in an ensemble agree, it’s a reasonably sure bet that the predictions will pan out. Nobody I’ve spoken to doubts the superiority of ensembles. Yet they haven’t been widely adopted in the United States at the resolution required to forecast localized, or “mesoscale,” events — specifically, thunderstorms, flash floods and tornadoes — because high-resolution ensembles require more computing power than the National Weather Service can currently provide. Higher-resolution ensembles translate to greater accuracy in the same way that HDTVs are clearer than analog sets. I met with a scientist at the National Center for Atmospheric Research in Boulder who showed me a prototype mesoscale ensemble for the United States. But at the moment, he can’t exploit its full potential because the supercomputing cluster at the Weather Service simply couldn’t handle the load. HPC systems are essentially designed for this type of computational problem, and we still want more powerful versions of it. For this reason, I find it unlikely that commodity cloud infrastructure - which was not explicitly designed for this type of problem, and it almost assuredly going to perform worse - will have much success in this area. At least in the near future.
• fnord123 10y ago
  I think the only thing that most HPC sites use which wouldn't be found in cloud infrastructure is the interconnects and a parallel file system. Back in 2004 I guess HPC sites were often using PPC on AIX. That's just gone. It's almost all Linux on x86_64 now aside from some interesting machines in Japan and China. So the distinction of "commodity" that Google made in the original map reduce paper in 2004 is gone. And the benefits of data locality are all but gone. The paper was great when it came out but it's long in the tooth since the hardware of today is different. To answer your actual question, I've never heard of anyone running WRF on cloud infrastructure. It doesn't have to be a terrible idea. If you're trying to come up with a competing model then the agility you get might be needed. i.e. being able to roll onto new hardware as it becomes available instead of having to work with budget cycles for a hardware refresh lets you move from tesla k80 to titans whenever AWS decided to make them available. Searching around, I see Glenn Lockwood did some benchmarks in 2013 with AWS: https://glennklockwood.blogspot.be/2013/12/high-performance-virtualization-sr-iov_14.html https://glennklockwood.blogspot.be/2013/12/high-performance-... This lot seem to have done some more benchmarking in 2014 (tldr 44% overhead on VMs - but take the time to read it since glockwood is always a good read): https://www.researchgate.net/publication/301407792_Performance_Characterisation_and_Evaluation_of_WRF_Model_on_Cloud_and_HPC_Architectures https://www.researchgate.net/publication/301407792_Performan... I think the prevailing issue is that latency on virtualized nodes is poor so you have to work around it. Maybe fat nodes with gpgpu can overcome the issues. If you need to talk to me privately then you can message me on reddit.
• timClicks 10y ago
  I know that New Zealand's MetService found that WRF running AWS is competitive, but I don't know if they published the results. Can put you in touch with their main point of contact for this kind of work. Abstract is here: http://www.eresearch.org.nz/event/eresearch-nz-2013/do-hpcs-at-bluefern-and-uoa-meet-metservices-research-requirements http://www.eresearch.org.nz/event/eresearch-nz-2013/do-hpcs-...