When we announced our partnership with Cray, it was very exciting news. Our minds immediately went to how this could be a benefit to weather forecasting.
Weather modeling is an interesting use case. It requires a large number of cores with a low-latency interconnect, and it is very time sensitive. After all, what good is a one hour weather forecast if it takes 90 minutes to run? And weather is a very local phenomenon. In order to resolve smaller scale features without shrinking the domain or lengthening runtime, modelers must add more cores. A global weather model with a 0.5 degree grid spacing can require as many as 50,000 cores.
Read more about it in the Azure blog.