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NVIDIA Jetson Xavier NX : World's Smallest AI Supercomputer

NVIDIA Jetson Xavier NX : World’s Smallest AI Supercomputer

On 7 November 2019, NVIDIA introduced the Jetson Xavier NX – the world’s smallest AI supercomputer designed for robotics and embedded computing applications at the edge!

Here is EVERYTHING you need to know about the new NVIDIA Jetson Xavier NX!

 

NVIDIA Jetson Xavier NX : World’s Smallest AI Supercomputer

At just 70 x 45 mm, the new NVIDIA Jetson Xavier NX is smaller than a credit card. Yet it delivers server-class AI performance at up to 21 TOPS, while consuming as little as 10 watts of power.

Short for Nano Xavier, the NX is a low-power version of the Xavier SoC that came up tops in the MLPerf Inference benchmarks.

Recommended : NVIDIA Wins MLPerf Inference Benchmarks For DC + Edge!

With its small size and low-power, it opens up the possibility of adding AI on-the-edge computing capabilities to small commercial robots, drones, industrial IoT systems, network video recorders and portable medical devices.

The Jetson Xavier NX can be configured to deliver up to 14 TOPS at 10 W, or 21 TOPS at 15 W. It is powerful enough to run multiple neural networks in parallel, and process data from multiple high-resolution sensors simultaneously.

The NVIDIA Jetson Xavier NX runs on the same CUDA-X AI software architecture as all other Jetson processors, and is supported by the NVIDIA JetPack software development kit.

It is pin-compatible with the Jetson Nano, offering up to 15X higher performance than the Jetson TX2 in a smaller form factor.

It is not available for a few more months, but developers can begin development today using the Jetson AGX Xavier Developer Kit, with a software patch to emulate Jetson Xavier NX.

 

NVIDIA Jetson Xavier NX Specifications

Specifications NVIDIA Jetson Xavier NX
CPU NVIDIA Carmel
– 6 x Arm 64-bit cores
– 6 MB L2 + 4 MB L3 caches
GPU NVIDIA Volta
– 384 CUDA cores, 48 Tensor cores, 2 NVDLA cores
AI Performance 21 TOPS : 15 watts
14 TOPS : 10 watts
Memory Support 128-bit LPDDR4x-3200
– Up to 8 GB, 51.2 GB/s
Video Support Encoding : Up to 2 x 4K30 streams
Decoding : Up to 2 x 4K60 streams
Camera Support Up to six CSI cameras (32 via virtual channels)
Up to 12 lanes (3×4 or 6×2) MIPI CSI-2
Connectivity Gigabit Ethernet
OS Support Ubuntu-based Linux
Module Size 70 x 45 mm (Nano)

 

NVIDIA Jetson Xavier NX Price + Availability

The NVIDIA Jetson Xavier NX will be available in March 2020 from NVIDIA’s distribution channels, priced at US$399.

 

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NVIDIA Wins MLPerf Inference Benchmarks For DC + Edge!

The MLPerf Inference 0.5 benchmarks are officially released today, with NVIDIA declaring that they aced them for both datacenter and edge computing workloads.

Find out how well NVIDIA did, and why it matters!

 

The MLPerf Inference Benchmarks

MLPerf Inference 0.5 is the industry’s first independent suite of five AI inference benchmarks.

Applied across a range of form factors and four inference scenarios, the new MLPerf Inference Benchmarks test the performance of established AI applications like image classification, object detection and translation.

 

NVIDIA Wins MLPerf Inference Benchmarks For Datacenter + Edge

Thanks to the programmability of its computing platforms to cater to diverse AI workloads, NVIDIA was the only company to submit results for all five MLPerf Inference Benchmarks.

According to NVIDIA, their Turing GPUs topped all five benchmarks for both datacenter scenarios (server and offline) among commercially-available processors.

Meanwhile, their Jetson Xavier scored highest among commercially-available edge and mobile SoCs under both edge-focused scenarios – single stream and multi-stream.

The new NVIDIA Jetson Xavier NX that was announced today is a low-power version of the Xavier SoC that won the MLPerf Inference 0.5 benchmarks.

All of NVIDIA’s MLPerf Inference Benchmark results were achieved using NVIDIA TensorRT 6 deep learning inference software.

 

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FREE AI Course For Jetson Nano – What You Need To Know!

NVIDIA just announced a FREE course on getting started with AI on the Jetson Nano!

Here is everything you need to know about this new Jetson Nano AI course – the first to be offered for FREE by the Deep Learning Institute!

 

The FREE AI Course For NVIDIA Jetson Nano

Looking to get started with AI, but don’t know how? The NVIDIA Deep Learning Institute has just published a new self-paced course that uses the newly released Jetson Nano Developer Kit to get up and running fast.

Best of all – this AI course for the NVIDIA Jetson Nano is FREE. This is the first Deep Learning Institute course to be offered for free.

In the course, students will learn to collect image data and use it to train, optimize, and deploy AI models for custom tasks like recognizing hand gestures, and image regression for locating a key point in an image.

  • Set up your Jetson Nano and camera
  • Collect image data for classification models
  • Annotate image data for regression models
  • Train a neural network on your data to create your own models
  • Run inference on the Jetson Nano with the models you create
  • Upon completion, you’ll be able to create your own deep learning classification and regression models with the Jetson Nano.

Some experience with Python is helpful but not required. You will need the NVIDIA Jetson Nano Developer Kit, of course.

 

The FREE Jetson Nano AI Course Requirements

Duration : 8 hours

Prerequisites: Basic familiarity with Python (helpful, not required)

Tools, libraries, frameworks used: PyTorch, Jetson Nano

Certificate: Available

Assessment Type: Multiple-choice

Required Hardware

  • NVIDIA Jetson Nano Developer Kit
  • High-performance microSD card: 32GB minimum (NVIDIA tested and recommend this one)
  • 5V 4A power supply with 2.1mm DC barrel connector (NVIDIA tested and recommend this one)
  • 2-pin jumper: must be added to the Jetson Nano Developer Kit board to enable power from the barrel jack power supply (here’s an example)
  • Logitech C270 USB Webcam (NVIDIA tested and recommend this one). Alternate camera: Raspberry Pi Camera Module v2 (NVIDIA tested and recommend this one)
  • USB cable: Micro-B To Type-A with data enabled (NVIDIA tested and recommend this one)
  • A computer with an Internet connection and the ability to flash your microSD card

 

How To Sign Up For The FREE Jetson Nano AI Course

You can sign up for the free Jetson Nano AI course at this link – Getting Started with AI on Jetson Nano.

 

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Everything Jensen Huang Revealed @ NVIDIA Computex 2018!

At an exclusive NVIDIA Computex 2018 press conference, NVIDIA CEO Jensen Huang revealed a slew of new computing products. But first, let us break your hearts and tell you upfront that he did not announce the long-awaited replacements for NVIDIA Pascal graphics cards…

But he did show off a number of interesting products, and we have the opportunity to take some pictures and videos of the new NVIDIA HGX-2, NVIDIA Drive Xavier, NVIDIA Drive Pegasus and NVIDIA Jetson Xavier!

We have more than 1.5 hours of videos in this article, and lots of pictures from the event, so grab a drink, sit back and enjoy! 😊

 

The NVIDIA Computex 2018 Press Conference

As there are limited room, this is an invitation-only press conference at the Grand Hyatt Taipei.

What a crowd… 30 minutes before the NVIDIA Computex 2018 press conference kicks off! 

Guess who’s here too? 

Unbelievable – there was time to get a selfie with Jensen himself before the press conference 

He seemed to have a good time tossing cookies to members of the media.

Alright… now, let’s get to the actual press conference, which lasted over 1.5 hours and was punctuated by several emergency sirens!

Next Page > What Jensen Huang Revealed @ NVIDIA Computex 2018

 

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What Jensen Huang Revealed @ NVIDIA Computex 2018

Jensen’s presentation was about an hour long, followed by a 30 minute Q&A session. Here are the full videos of his presentation and Q&A session.

If you are looking for news on NVIDIA Turing – the next GeForce – skip to minute 13:02 of the Q&A session video. This was what Jensen said :

When is the next GeForce? I’m going to invite you guys. Don’t worry!

No only will you be invited, there will probably be lunch.

A little hint? It’s a long time from now. It’s a long time from now.

In the next page, we have the blow-by-blow account of Jensen’s announcements, as well as pictures. In the meantime, here are our video tour of some of the new NVIDIA products the Jensen just revealed.

 

The NVIDIA Jetson Xavier Up Close!

The NVIDIA Jetson Xavier is a new deep learning computer designed for intelligent machines, e.g. robots. It delivers 30 teraflops of performance in a small form factor. The developer’s kit will see an early release in August 2018, with a price of US$ 1,299.

 

The NVIDIA Drive Xavier + Drive Pegasus Up Close!

Both NVIDIA Drive Xavier and NVIDIA Drive Pegasus use the new NVIDIA Xavier SoC – the world’s largest System-On-Chip, with 9 billion transistors!

The Drive Xavier uses a single Xavier SoC, with 30 teraflops of computing performance. The Drive Pegasus, on the other hand, has two Xavier SoCs and two Tesla V100 GPUs, with a total computing performance of 280 teraflops!

 

The NVIDIA HGX-2 Up Close!

The NVIDIA HGX-2 is a new architecture for hyperscale servers, delivering 1 petaflops on a single board, or 2 petaflops with two boards! Each HGX-2 board has eight Tesla V100 GPUs with 32 GB of HBM2 memory per module,

Next Page > The NVIDIA Computex 2018 In Pictures

 

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The NVIDIA Computex 2018 Press Conference In Pictures

Jensen starts by showing off the new Tesla V100 GPU with 32 GB of HBM2 memory. 16 of these go into the new NVIDIA DGX-2 – the world’s largest GPU node with 2 teraflops of performance!

No… Jensen is not serving pizza 😂

That is the NVIDIA HGX-2 – world’s most powerful motherboard with eight Tesla V100 GPUs delivering 1 teraflops of computing power!

Jensen announces NVIDIA Xavier – the world’s first AI processor for intelligent machines.

Jensen shows off the NVIDIA Drive Pegasus – a complete intelligent platform powered by the new NVIDIA Xavier SoC.

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Introducing NVIDIA Jetson Xavier board for the NVIDIA ISAAC robotics platform!

This is the complete NVIDIA Jetson Xavier developer’s kit computer.

Here is a closer look at the NVIDIA Xavier board (middle), with its module (right), and the complete computer (right).

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The NVIDIA Jetson TX2 (Pascal) Tech Report

NVIDIA just announced the Jetson TX2 embedded AI supercomputer, based on the latest NVIDIA Pascal microarchitecture. It promises to offer twice the performance of the previous-generation Jetson TX1, in the same package. In this tech report, we will share with you the full details of the new Pascal-based NVIDIA Jetson TX2!

 

GPUs In Artificial Intelligence

Artificial intelligence is the new frontier in GPU compute technology. Whether they are used to power training or inference engines, AI research has benefited greatly from the massive amounts of compute power in modern GPUs.

The market is led by NVIDIA with their Tesla accelerators that run on their proprietary CUDA platform. AMD, on the other hand, is a relative newcomer with their Radeon Instinct accelerators designed to run on the open-source ROCm (Radeon Open Compute) platform.

 

The NVIDIA Jetson

GPUs today offer so much compute performance that NVIDIA has been able to create the NVIDIA Jetson family of embedded AI supercomputers. They differ from their Tesla big brother in their size, power efficiency and purpose. The NVIDIA Jetson modules are specifically built for “inference at the edge” or “AI at the edge“.

 

Unlike AI processing in the datacenters or in the cloud, AI in the edge refers to autonomous artificial intelligence processing, where there is poor or no Internet access or access must be restricted for privacy or security reasons. Therefore, the processor must be powerful enough for the AI application to run autonomously.

Whether it’s to automate robots in a factory, or to tackle industrial accidents like at the Fukushima Daiichi nuclear plant, AI at the edge is meant to allow for at least some autonomous capability right in the field. The AI in the edge processors must also be frugal in using power, as power or battery life is often limited.

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Hence, processors designed for AI on the edge applications must be small, power-efficient and yet, fast enough to run AI inference in real time. The NVIDIA Jetson family of embedded AI supercomputers promises to tick all of those boxes. Let’s take a look :

Next Page > The NVIDIA Jetson TX2, Specification Comparison, Price & Availability

 

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The NVIDIA Jetson TX2

The NVIDIA Jetson TX2 is the second-generation Jetson embedded AI module, based on the latest NVIDIA Pascal microarchitecture. It supersedes (but not replace) the previous-generation Jetson TX1, which was built on the NVIDIA Maxwell microarchitecture and released in November 2015.

Thanks to the faster and more power-efficient Pascal microarchitecture, the NVIDIA Jetson TX2 promises to be twice as energy-efficient as the Jetson TX1.

This means the developers switching to the Jetson TX2 can now opt to maximise power efficiency, or to maximise performance. In the Max-Q mode, the Jetson TX2 will use less than 7.5 W, and offer Jetson TX1-equivalent performance. In the Max-P mode, the Jetson TX2 will use less than 15 W, and offer up to twice the performance of the Jetson TX1.

 

NVIDIA Jetson Specification Comparison

The NVIDIA Jetson modules are actually built around the NVIDIA Tegra SoCs, instead of their GeForce GPUs. The Tegra SoC is a System On A Chip, which integrates an ARM CPU, an NVIDIA GPU, a chipset and a memory controller on a single package.

The Tegra SoC and the other components on a 50 x 87 mm board are what constitutes the NVIDIA Jetson module. The Jetson TX1 uses the Tegra X1 SoC, while the new Jetson TX2 uses the Tegra P1 SoC.

For those who have been following our coverage of the AMD Radeon Instinct, and its support for packed math, the NVIDIA Jetson TX2 and TX1 modules support FP16 operations too.

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NVIDIA Jetson TX2 Price & Availability

The NVIDIA Jetson TX2 Developer Kit is available for pre-order in the US and Europe right now, with a US$ 599 retail price and a US$ 299 education price. Shipping will start on March 14, 2017. This developer’s kit will be made available in APAC and other regions in April 2017.

The NVIDIA Jetson TX2 module itself will only be made available in the second quarter of 2017. It will be priced at US$ 399 per module, in quantities of 1,000 modules or more.

Note that the Jetson TX2 modules are exactly the same size and uses the same 400-pin connector. They are drop-in compatible replacements for the Jetson TX1 modules.

Next Page > NVIDIA Jetson TX1 Price Adjustments, NVIDIA Jetpack 3.0, The Slides

 

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NVIDIA Jetson TX1 Price Adjustments

With the launch of the Jetson TX2, NVIDIA is adjusting the price of the Jetson TX1. The Jetson TX1 will continue to sell alongside the new Jetson TX2.

The NVIDIA Jetson TX1 Developer Kit has been reduced to US$ 499, down from US$ 599.

The NVIDIA Jetson TX1 production has been reduced to US$ 299, down from US$ 399. Again, this is in quantities of 1,000 modules or more.

 

NVIDIA Jetpack 3.0

The NVIDIA Jetson is more than just a processor module. It is a platform that is made up of developer tools and codes, as well as APIs. Like AMD offers their MIOpen deep learning library, NVIDIA offers Jetpack.

In conjunction with the launch of the Jetson TX2, NVIDIA also announced the NVIDIA Jetpack 3.0. It promises to offer twice the system performance of Jetpack 2.3.

Jetpack 3.0 is not just for the new Jetson TX2. It will offer a nice boost in performance for existing Jetson TX1 users and applications.

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The Presentation Slides

For those who want the full set of NVIDIA Jetson TX2 slides, here they are :

 

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