Info
Info

NVIDIA’s Supercomputer supports Self-Driving cars

News

NVIDIA unveiled the world’s 22nd fastest supercomputer — DGX SuperPOD — which provides AI infrastructure that meets the massive demands of the company’s autonomous-vehicle deployment programme.

Info

The system was built in just three weeks with 96 NVIDIA DGX-2H supercomputers and Mellanox interconnect technology. Delivering 9.4 petaflops of processing capability, it has the muscle for training the vast number of deep neural networks required for safe self-driving vehicles. Customers can buy this system in whole or in part from any DGX-2 partner based on our DGX SuperPOD design.

AI training of self-driving cars is the ultimate compute-intensive challenge. A single data-collection vehicle generates 1 terabyte of data per hour. Multiply that by years of driving over an entire fleet, and you quickly get to petabytes of data. That data is used to train algorithms on the rules of the road — and to find potential failures in the deep neural networks operating in the vehicle, which are then re-trained in a continuous loop.

“AI leadership demands leadership in compute infrastructure,” said Clement Farabet, Vice President of AI infrastructure at NVIDIA. “Few AI challenges are as demanding as training autonomous vehicles, which requires retraining neural networks tens of thousands of times to meet extreme accuracy needs. There's no substitute for massive processing capability like that of the DGX SuperPOD.”

Powered by 1,536 NVIDIA V100 Tensor Core GPUs interconnected with NVIDIA NVSwitch and Mellanox network fabric, the DGX SuperPOD can tackle data with peerless performance for a supercomputer its size. The system is hard at work around the clock, optimising autonomous driving software and retraining neural networks at a much faster turnaround time than previously possible.

For example, the DGX SuperPOD hardware and software platform takes less than two minutes to train ResNet-50. When this AI model came out in 2015, it took 25 days to train on the then state-of-the-art system, a single NVIDIA K80 GPU. DGX SuperPOD delivers results that are 18,000x faster. While other TOP 500 systems with similar performance levels are built from thousands of servers, DGX SuperPOD takes a fraction of the space, roughly 400x smaller than its ranked neighbours.

NVIDIA DGX systems have already been adopted by other organisations with massive computational needs of their own — ranging from automotive companies such as BMW, Continental, Ford and Zenuity to enterprises including Facebook, Microsoft and Fujifilm, as well as research leaders like Riken and US Department of Energy national labs.


The Latest News, Brought To You By
NVIDIA’s Supercomputer supports Self-Driving cars
Modified on Thursday 20th June 2019
Find all articles related to:
NVIDIA’s Supercomputer supports Self-Driving cars
TaaS Technology Magazine
Info
Free2Move Lease Provides Funding And Telematics Package For Maxxis Tyres
BMW Group Ushers In Next Digital Key Generation
Chevrolet Menlo EV With 410 Kilometres Range Debuts In China
Hyundai Teases Plug-in Hybrid Electric SUV Concept Ahead Of 2019 AutoMobility LA
NASA Takes Delivery Of First All-electric Experimental Aircraft
Wind River Teams With Xilinx On Secure And Safe Platform For Automated Driving Applications
Audi Expands Its Mobility Offering Audi On Demand In Germany
E-Mobility Group Launches Comprehensive Ecosystem For Entry Into E-mobility
Smart Eye To Supply Driver Monitoring System To Another Japanese OEM
Škoda Introduces Plug-in Hybrid And Mild Hybrid Options For The Fourth Generation Octavia
Rampini And Caetanobus Reach Commercial Agreement
SafeRide Technologies Named Auto-ISAC Strategic Partner
Production Version Of The Aspark Owl Revealed
ElringKlinger Receives Another High-volume Light-weighting Order From US EV Manufacturer
Voi Technology Raises $85 Million In Series B Round
Tesla To Build Its European Gigafactory Near Berlin
SEAT’s Carsharing Company Respiro To Operate In L’Hospitalet De Llobregat, Spain
Hyundai Demonstrates Autonomous Driving Tech Capabilities With Successful Truck Platooning Trial
UCLA Health Center Receives All-electric Winnebago As A Zero-emission Mobile Surgical Instrument Lab
Foresight Receives Order Of QuadSight Prototype From American Division Of Leading South Korean Vehicle Manufacturer
Xpeng Motors Announces $400 Million Series C Capital Funding
Kandi Announces Successful Inspection Of Automatic Intelligent Battery Exchange System
NIU Unveils Brand-new Electric Bicycle, Aero EB-01
Dresden-based KaSiLi To Make Better Batteries For EVs In Germany
Info
Info
×
Search the news archive

To close this popup you can press escape or click the close icon.
Logo
×
Logo
×
Register - Step 1

You may choose to subscribe to the TaaS Magazine, the TaaS Newsletter, or both. You may also request additional information if required, before submitting your application.


Please subscribe me to:

 

You chose the industry type of "Other"

Please enter the industry that you work in:
Please enter the industry that you work in:
 
X
Info
X
Info
{taasPodcastNotification}