New GPU Instances in Microsoft Azure Cloud
Simulating protein molecules. Self-driving cars. Seismic exploration. Researchers and businesses have many choices to tackle these challenges with NVIDIA GPU computing.
The NVIDIA accelerated computing platform is accessible for the most demanding workloads from data centers or in the cloud. Today, researchers have another great option: GPU computing in the cloud with Microsoft Azure’s new instances.
Whether they’re sequencing DNA or providing real-time language translation, people using GPU computing in the cloud can accelerate their work, and scale it up or down on demand.
The City of Hope in Los Angeles is one such example. A team of computer scientists led by Dr. Nagarajan Vaidehi, director of the Computational Therapeutics Core at the medical research and treatment center, performs molecular modeling to better understand diseases such as cancer and diabetes.
To design drugs, Vaidehi’s team screens millions of protein molecules in 3D and performs related calculations to understand the shapes of specific candidates.
While the researchers focus their science at the molecular level of life, and the drugs that might sustain it, they’re increasingly putting their data in the cloud. Using Microsoft Azure virtual machines with NVIDIA Tesla GPU accelerators, they can scale up their computing needs to handle bigger simulations faster — and trim simulation times from weeks to days.
Read the entire article here, New GPU Instances in Microsoft Azure Cloud
via the fine folks at NVIDIA.