Nvidia Tesla Supercomputer

The xeon w personal supercomputer is designed around nvidia quadro and tesla accelerated computation graphics processors.

Nvidia tesla supercomputer.

3x 1 92 tb ssd raid 0 os. Mercedes benz and nvidia announced a partnership for the next generation vehicles powered by ai computers much like tesla s electric cars. This high performance personal supercomputer comes stock with a high powered quadro graphics card and options to add nvidia tesla cards not only that but with options for xeon w up to 18 cores our supercomputer has the cpu power to back that up. It utilizes nvidia s cuda parallel computing architecture and is powered by up to 2688 parallel processing cores per gpgpu which allow it to achieve speeds up to 250.

That means your gpu accelerated supercomputer can act as a very high performance visualization and analysis system giving you the flexibility of scaling visualization resources with your compute resources. Nvidia describes the drive px 2 as the world s first ai supercomputer for self driving cars. Nvidia partners offer a wide array of cutting edge servers capable of diverse ai hpc and accelerated computing workloads. But tesla gpus offer all the high end graphics capabilities you would expect from quadro and geforce.

Leverage nvidia tesla gpus to accelerate deep learning analytics science simulation and other high performance computing hpc workloads and nvidia grid with gcp to accelerate graphics intensive workloads from anywhere. Learn more sales contact 1 844 613 7589. Paul shapiro professor at university of texas at austin shares how his team is using the tesla accelerated titan supercomputer at oak ridge national laboratory to analyze and visualize. Research astronomy astrophysics higher education academia share your science simulation supercomputing tesla nadeem mohammad posted jan 20 2016 dr.

It appears to be a custom solution for tesla and it is not as powerful as nvidia s most. The german luxury automaker is building its own in car. 1x 1 92 tb ssd. They are programmable using the cuda or opencl apis.

To promote the optimal server for each workload nvidia has introduced gpu accelerated server platforms which recommends ideal classes of servers for various training hgx t inference hgx i and supercomputing scx applications. It is meant to be a demonstration of the capabilities of nvidia s tesla gpgpu brand.