Innovative Deep Learning Workstation Service by Cirrascale Cloud Services

A new service by Cirrascale Cloud Services was released today, enhancing the already impressive lineup of cloud solutions. The Data Science Workstations Service is a welcome addition to the Cirrascale Cloud Services offerings.

The group behind the new service partnered with BOXX Technologies and NVIDIA to create state of the art workstation hardware. Clocking an impressive 260 teraflops on the NVIDIA Quadro RTX and a whopping 96GB of local memory, these workstations are designed for massive data sets and complex operations.

The cloud-based workstations allow customers to take the computing power to the next level.

“Our customers working with Autonomous Vehicle and Medical Imaging datasets are continuing to transition their deep learning workflows to the cloud,” said Vice President Mike LaPan. “We were challenged by those who had already adapted 80% of their current workflows to the cloud to move their Data Science Workstations there as well. By providing these dedicated, non-virtualized workstations with the latest Quadro RTX GPUs, we’ve been able to close the loop and deliver to our customers that final piece.”

By shifting to cloud-based services, businesses can adapt the agility needed to succeed in the market. Many businesses have a majority of their workflows in a cloud-based format, and with the new Data Science Workstations Service, deep learning can also transition to a cloud-based platform.

The new service provides dedicated support for all clients, a complete deep learning workflow, workstations, various storage options, as well as dedicated training servers. The service is billed at flat rates, which diverges from traditional billing practices in the industry.

The official launch of the new service is happening this week at CVPR 2019, will a full launch shortly after. The unique, non-virtualized workstation offering, along with the strong partnerships with BOXX and NVIDIA, sets Cirrascale Cloud Services up to pave the way for future deep learning cloud integration services.

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