CloudyCluster Team's blog

Cloud HPC Insights

(reprint)… More and more businesses rely on data-driven decisions, simulations, models and customer interaction. More of these data-driven requirements need faster and faster responses, even real-time, and this demand is stressing traditional storage architectures. Historically, storage systems and protocols have single points of ingress and egress for data. These single pinch-points are increasingly becoming bottlenecks, limiting the ability to process data in a timely fashion. The High Performance Computing community has faced these problems since the inception of the Beowulf cluster, the original concept of tying several commodity computers together to distribute computational workloads.

Parallel Weather Modeling in the Cloud Weather and climate modeling is becoming more critical as more and more industries rely on accurate forecasting from typical weather to severe storms. This modeling can provide insights and cause/effect relationships we have yet to discover. It can also extend our current understanding of the changing climate. In this experiment, the computation tool is the Weather Research and Forecasting (WRF) model. WRF is a next-generation mesoscale numerical weather prediction system designed for both atmospheric research and operational forecasting applications.