NVIDIA, at their GTC Taiwan event, introduced the NVIDIA HGX-2, a unified computing platform for both AI and high-performance computing equipped with 16 NVIDIA Tesla V100 graphics processing units. The 16 GPUs collectively provide half a terabyte of GPU memory and two petaflops of computing power.

The NVIDIA HGX-2 is a cloud-server platform with multi-precision computing capabilities and provide high flexibility to future-proof its computing power. It has achieved record AI training speeds. According to a statement by NVIDIA, the GPU server can process 15,500 images per second on the ResNet-50 training benchmark. It is capable of replacing up to 300 CPU-only servers. These high-precision calculations are done using FP64 and FP32 for scientific calculations and simulations and FP16 and Int8 for AI training and inference.

NVIDIA HGX-2Many leading computer makers like Lenovo, QCT, Supermicro, Wiwynn, and manufacturers like Foxconn, Inventec, Quanta, and Wistron are planning to bring systems based on NVIDIA HGX-2 platform for large cloud data centers. HGX-2 will be used by manufacturers to create advanced systems to be used for AI and HPC. The first system built using HGX-2 was the NVIDIA DGX-2 which was recently announced.

The 16 GPU units that HGX-2 consists are able to work collectively using NVIDIA NVSwitch interconnect fabric. It links the 16 NVIDIA Tesla V100 Tensor Core GPUs to act as a single, giant GPU.


Jensen Huang, founder and chief executive officer of NVIDIA, speaking at the GPU Technology Conference in Taiwan, said: “The world of computing has changed.” He further added, “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.”

HGX-2 follows the launch of the original NVIDIA HGX-1, at Computex 2017. The HGX-1 was powered by eight GPUs. The HGX-1 reference architecture was adopted worldwide by leading server makers and companies operating data centers, including Amazon Web Services, Facebook’s Big Basin and Microsoft Project Olympus.



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