NVIDIA has introduced the NVIDIA HGX-2, the first unified computing platform for both artificial intelligence (AI) and high performance computing (HPC).
With multi-precision computing capabilities, HGX-2 allows high-precision calculations using FP64 and FP32 for scientific computing and simulations, while also enabling FP16 and Int8 for AI training and inference.
This unprecedented versatility meets the requirements of the growing number of applications that combine HPC with AI.
“The world of computing has changed. CPU scaling has slowed at a time when computing demand is skyrocketing. NVIDIA’s HGX-2 with Tensor Core GPUs gives the industry a powerful, versatile computing platform that fuses HPC and AI to solve the world’s grand challenges,” said Jensen Huang, Founder and CEO of NVIDIA at GPU Technology Conference Taiwan.
HGX-2-serves as a “building block” for manufacturers to create advanced systems for HPC and AI. It has achieved record AI training speeds of 15,500 images per second on the ResNet-50 training benchmark and can replace up to 300 CPU-only servers.
Its features include NVIDIA NVSwitch interconnect fabric, which seamlessly links 16 NVIDIA Tesla V100 Tensor Core GPUs to work as a single, giant GPU delivering two petaflops of AI performance. The first system built using HGX-2 was the recently announced NVIDIA DGX-2.
Four leading server makers — Lenovo, QCT, Supermicro, and Wiwynn — announced plans to bring their own HGX-2-based systems to market later this year.
Additionally, four of the world’s top original design manufacturers — Foxconn, Inventec, Quanta, and Wistron — are designing HGX-2-based systems, also expected later this year.