Published in AI

Nvidia releases Jetson Xavier NX

by on07 November 2019

Claims it is the "smallest, most powerful AI supercomputer for robotic and embedded computing devices at the edge"

Nvidia has released a new compact chip which it claims is ideal for robots and edge computing.

Smaller than the size of a credit card, the energy-efficient Jetson Xavier NX module delivers server-class performance up to 21 TOPS for running modern AI workloads. It consumes as little as 10 watts of power.

According to Nvidia, the Jetson Xavier NX opens the door for embedded edge computing devices that demand increased performance but are constrained by size, weight, power budgets or cost. These include small commercial robots, drones, intelligent high-resolution sensors for factory logistics and production lines, optical inspection, network video recorders, portable medical devices and other industrial IoT systems.

Nvidia vice president and general manager of Edge Computing at Deepu Talla  said: "Many of these devices, based on small form factors and lower power, were constrained from adding more AI features. Jetson Xavier NX lets our customers and partners dramatically increase AI capabilities without increasing the size or power consumption of the device."

Jetson Xavier NX can run multiple neural networks in parallel and processing data from multiple high-resolution sensors simultaneously in a Nano form factor (the 70 mm x 45 mm). For companies already building embedded machines, Jetson Xavier NX runs on the same CUDA-X AI software architecture as all Jetson offerings, ensuring rapid time to market and low development costs, Nvidia said.

As part of Nvidia's "one software" architecture approach, Jetson Xavier NX is supported by the JetPack software development kit, which is a complete AI software stack that can run modern and complex AI networks, accelerated libraries for deep learning as well as computer vision, computer graphics, multimedia and more.

Nvidia claimed that the chip topped all five benchmarks measuring the performance of AI inference workloads in data centres and at the edge — building on the company's equally strong position in recent benchmarks measuring AI training. The results of MLPerf Inference 0.5, the industry's first independent AI benchmark for inference, demonstrate the inference capabilities of Turing GPUs for data centres and the Xavier system-on-a-chip for edge. The Jetson Xavier NX module is built around a new low-power version of the Xavier SoC used in these benchmarks.

Jetson Xavier NX module specifications:

  • GPU: Volta with 384 NVIDIA CUDA cores and 48 Tensor Cores, plus 2x NVDLA
  • CPU: 6-core Carmel ARM 64-bit CPU, 6 MB L2 + 4 MB L3
  • Video: 2x 4K30 Encode and 2x 4K60 Decode
  • Camera: Up to six CSI cameras (36 via virtual channels); 12 lanes (3x4 or 6x2) MIPI CSI-2
  • Memory: 8 GB 128-bit LPDDR4X, 51.2 GB/s
  • Connectivity: Gigabit Ethernet
  • OS Support: Ubuntu-based Linux
  • Module Size: 70 mm x 45 mm

Priced at $399, the Jetson Xavier NX module will be available in March from Nvidia's distribution channels for companies looking to create high-volume production edge systems. Developers can begin application development today using the Jetson AGX Xavier Developer Kit with a software patch to emulate Jetson Xavier NX.

Last modified on 07 November 2019
Rate this item
(0 votes)

Read more about: