For enterprises that don’t want to spend $7 million to $60 million for Nvidia’s DGX SuperPOD AI supercomputer, the chipmaker is now giving customers the option of paying $90,000 a month for ...
The DGX B200 systems – used in Nvidia's Nyx supercomputer – boast about 2.27x higher peak floating point performance across FP8, FP16, BF16, and TF32 precisions than last gen's H100 systems.
The Eos supercomputer is built with 576 Nvidia DGX H100 systems, Nvidia Quantum-2 InfiniBand networking, plus software, and is capable of delivering a whopping 18.4 exaflops of FP8 AI performance.
These DGX systems, each of which contain eight H100 GPUs, are connected together using Nvidia’s ultra-low latency InfiniBand networking technology and managed by Equinix’s managed services ...
NVIDIA DRIVE DGX optimizes deep learning computations in the cloud. See H100. THIS DEFINITION IS FOR PERSONAL USE ONLY. All other reproduction requires permission.