NVIDIA unveiled the world’s 22nd-fastest supercomputer—DGX SuperPOD—which provides an AI infrastructure that meets the massive demands of the company’s autonomous-vehicle deployment program.
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 the 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.
The DGX SuperPOD is powered by 1,536 NVIDIA V100 Tensor Core GPUs interconnected with NVIDIA NVSwitch and Mellanox network fabric.