The personal Supercomputer for Leading-Edge
AI Development
Your data science team depends on computing performance to gain insights, and innovate faster through the power of deep learning and data analytics. Until now,AI supercomputing was confined to the data center, limiting the experimentation
needed to develop and test deep neural networks prior to training at scale. Now there’s a solution, offering the power to experiment with deep learning while bringing AI supercomputing performance within arm’s reach.
Groundbreaking AI, at Your Desk
Now you can get the computing capacity of 400 CPU's, in a workstation that conveniently fits under your desk, drawing less than 1/20th the power. NVIDIA ® DGX Station ™ delivers incredible deep learning and analytics performance, designed for the office and whisper quiet with only 1/10th the noise of other
workstations. Data scientists and AI researchers can instantly boost their productivity with a workstation that includes access to optimized deep learning software and runs popular analytics software.
Get Started in Deep Learning, Faster
DGX Station breaks through the limitations of building your own deep learning platform. You could spend a month or longer, procuring, integrating, and testing hardware and software. Then additional expertise and effort are needed to optimize
frameworks, libraries, and drivers. That’s valuable time and money spent on systems integration and software engineering that could be spent training and experimenting.NVIDIA DGX Station is designed to kickstart your AI initiative, with a streamlined plug-in and power-up experience that can have you training deep neural networks in just one day.
productivity That Takes You from Desk to Data Center
Deep learning platforms require software engineering expertise to keep today’s frameworks optimized for maximum performance, with time spent waiting on stable versions of open source software. This means hundreds of thousands of dollars in lost productivity, dwarfing the initial hardware cost. NVIDIA DGX Station includes the same software stack found in all DGX solutions. This innovative, integrated system includes access to popular deep learning frameworks, updated monthly, each optimized by NVIDIA engineers for maximized performance. It also includes access to NVIDIA DIGITS™ deep learning training application, third-party accelerated solutions, the the NVIDIA Deep Learning SDK (e.g. cuDNN, cuBLAS, NCCL), CUDA ® Toolkit, and NVIDIA drivers.
Built on container technology powered by NVIDIA Docker, this
unified deep learning software stack simplifies workflow,saving you days in re-compilation time when you need to scale your work and deploy your models in the data center or cloud. The same workload running on DGX Station can be effortlessly
migrated to a DGX-1 or the cloud, without modification.
Supercomputing performance, at Your Desk
DGX Station brings the incredible performance of an AI supercomputer in a workstation form factor that takes advantage of innovative engineering and a water-cooled system that runs whisper-quiet.
The NVIDIA DGX Station packs 500 TeraFLOPS of performance,
with the first and only workstation built on four NVIDIA Tesla ®
V100 accelerators, including innovations like next generation
NVLink ™ and new Tensor Core architecture. This ground-
breaking solution offers:
> 47X the performance for deep learning training, compared
with CPU-based servers
> 100X in speed-up on large data set analysis, compared with
a 20 node Spark server cluster
> 5X increase in bandwidth compared to PCIe with NVIDIA
NVLink technology
> maximized versatility with deep learning training and over
30,000 images/second inferencing
Investment protection
With DGX Station, you get enterprise grade support with access to NVIDIA deep learning expertise, a library of expert training, software upgrades and updates, and priority resolution of your critical issues—all in one place
SYSTEM SPECIFICATIONS
GPUs
4X Tesla V100
Performance
(GPU FP16)
500
GPU Memory
64 GB total system
CPU
Intel Xeon E5-2698 v4 2.2 GHz
(20-Core)
NVIDIA CUDA ® Cores
20,480
NVIDIA Tensor Cores
2,560
Maximum Power
Requirements
1,500 W
System Memory
256 GB LRDIMM DDR4
Storage
Data: 3X 1.92 TB SSD RAID 0
OS: 1X 1.92 TB SSD
Network
Dual 10GBASE-T (RJ45)
Software
Ubuntu Desktop Linux OS
DGX Recommended GPU Driver
CUDA Toolkit