Cirrascale Cloud Services Expands Its Offerings with Support for NVIDIA Tesla V100 GPU Accelerators

Cirrascale Cloud Services, a provider of public and private dedicated, multi-GPU cloud solutions enabling deep learning, will begin offering NVIDIA Tesla V100 GPU accelerators as part of its dedicated, multi-GPU deep learning cloud service offerings.

The company plans to fully expand its current offerings to include the Tesla V100 within its PCIe-based multi-GPU cloud solution for the highest versatility for all workloads. Additionally, Cirrascale Cloud Services will offer NVIDIA NVLink high-speed interconnect technology on POWER9 and NVIDIA DGX solutions with Tesla V100 accelerators for the ultimate performance with deep learning frameworks.

Cirrascale Cloud Services will release its Tesla V100 solutions on the Cirrascale Cloud Services platform in Q4 2017.

AI, HPC, Graphics

nvidia tesla v100“Our customers are experts in artificial intelligence, deep learning and analytics and they demand the absolute highest performing tools available,” said Mike LaPan, vice president of marketing, Cirrascale Cloud Services. “The NVIDIA Tesla V100 fast-tracks their AI initiatives by providing increased performance and versatility while enabling them to tackle challenges that were once impossible.”

NVIDIA Tesla V100 accelerates AI, HPC, and graphics. Powered by the latest GPU architecture, NVIDIA Volta, Tesla V100 would offer the performance of 100 CPUs in a single GPU – enabling data scientists, researchers, and engineers to tackle their greatest challenges. The Tesla V100 specifications include 16GB of HBM2 stacked memory, 5,120 CUDA cores and 640 Tensor Cores.

“GPU computing has enabled incredible breakthroughs in AI and high performance computing,” said Paresh Kharya, group product marketing manager, NVIDIA. “Deploying the new NVIDIA Tesla V100 GPU accelerators within the Cirrascale Cloud Services platform will enable their customers to accelerate deep learning and HPC applications using the world’s most advanced data center GPUs.”