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The Best Nvidia Single Board Computers for AI and More

The latest trend in IoT is the rise of the single board computer for AI, machine learning, autonomous driving and robotics, which is a device that is designed for a smaller form factor. If you are interested to learn, get certifications and work with Nvidia devices, contact IoT Worlds today.

Jetson Nano 2GB

If you’re looking for a small form factor computer that can help you develop a machine learning or robotics program, NVIDIA’s Jetson Nano 2GB is a great option. Although it’s not a direct competitor to the Raspberry Pi, it’s designed to help you get started with AI and robotics.

The new Nano features a 128-core Maxwell GPU and two gigabytes of RAM. It also has a 40-pin GPIO connector, HDMI display port, Gigabit Ethernet, and an HDMI camera port. Among the board’s other I/O are an M2 key E connector for a WiFi card, and a microSD card slot.

While Jetson Nano has a number of features, it’s the developer kit that really stands out. It includes a downloadable system image, the JetPack SDK, and some helpful applications. It also comes with a handy Getting Started guide, which is a good way to jump start your machine learning projects.

With the release of the Nano 2GB, NVIDIA is taking another step toward the ultimate edge AI solution. This small computer packs a punch, and it’s a perfect fit for entry-level edge AI devices.

Compared to the Nano’s predecessor, the 2GB model offers more RAM and faster performance, but loses some ports. The board’s USB and DisplayPort 1.2 ports are a bit smaller, while the M.2 slot for an optional Wi-Fi adapter is gone. Nevertheless, the new model is a better choice than the Raspberry Pi 4 for computer vision tasks.

Jetson Nano 2GB supports several advanced AI applications. Among these are semantic segmentation, object detection, and object recognition. These applications are important in helping to speed up the development of self-driving vehicles.

However, Jetson Nano 2GB does not come with built-in Bluetooth and WiFi. You’ll need to use the included M2 key E connector to add a Wi-Fi card, or connect your keyboard, HDMI display, and network. Likewise, the microSD card is a must-have for operating system and data storage.

If you’re ready to start developing your own machine learning or robotics program, the NVIDIA Jetson Nano 2GB Developer Kit is a worthwhile investment. As a bonus, it will let you see what you’ve been doing in real time, making it a particularly useful tool for hands-on learning.

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Jetson TX2

NVIDIA Jetson TX2 is a single board computer based on the ARM Cortex-A57 CPU and a 256-core Pascal GPU. It is a high-performance, low-power system for AI computing. This system can be used in a variety of applications, including intelligent video analytics, drones, and autonomous vehicles.

In the early days of the Jetson platform, it was primarily a system for accelerating machine learning applications. Today, however, it is an embedded computing platform that can be used in a variety of products. For example, it can be used in drones to stabilize video in real time.

The Jetson TX2 module weighs only 85 grams, with a 7.5-watt power consumption. As a result, it is ideal for small form factor systems, such as medical imaging devices, UAVs, and autonomous vehicles. Also, its small size allows for integration into a variety of products.

The Jetson TX2 features five power modes. These are numbered 0 through 4. Power mode 3 is the default mode. Each CPU core in the Jetson TX2 has a 2MB L2 cache.

This means that the Jetson TX2 can process an additional stream of high-bandwidth data simultaneously. Additionally, the coherency mechanism of the Jetson TX2 allows for free migration between CPU cores.

NVIDIA Jetson TX2 offers more than a TFLOP/s of compute performance. It also offers a lower power consumption than any server class CPU.

It can also offer better inference performance than AlexNet. Its FP16 compute capability is more than twice the performance of GoogleNet. Moreover, it can be used for computer vision applications. In particular, it can fuse multiple sensors, including stereo cameras, and perform accurate inferences.

The hex-core ARMv8 64-bit CPU complex is supported by optimized deep learning libraries. Combined with the 256-core Pascal GPU, it offers major performance improvements. Among the various hardware interfaces, it includes a USB 3.1 at 5 Gbps, HDMI, Gigabit Ethernet with Jumbo Frames, and PCI Express expansion.

It also features an eMMC 5.1 flash storage, which can provide up to 16GB of memory. This means that it has more than double the memory of the Jetson TX1 model.

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Jetson Xavier NX

Nvidia Jetson Xavier NX is a compute module that delivers supercomputer performance to the edge. This small form factor device is designed for use in autonomous machines, machine vision systems, and robotics.

Jetson Xavier NX has an embedded System-on-Module (SoM) that contains a CPU, GPU, flash storage, and PMICs. It supports high-speed CSI and computer vision, and can run popular AI frameworks like Caffe, Keras, and TensorFlow. The compute module is available as a production module or as a Developer Kit.

The compute module includes 8-32GB eMMC 5.1, and can be configured with an 800Mhz GPU. It is a 70 mm x 45 mm system-on-module with a 10W power envelope.

The compute module is pin-compatible with Jetson Nano SoM. Xavier NX is also available as a Developer Kit. With this kit, users can develop applications and perform performance tests with a pre-installed Nvidia JetPack software stack. In addition to a collection of CUDA demos, the software includes Gaussian blurs, fog simulations, and more.

Xavier NX is a powerful development environment. Users can run a benchmark or file system test, or back up their data to a file system. Using a tool called jetson-stats, they can monitor the status of the Jetson Xavier NX.

Xavier NX has a built-in WiFi/BT module. It can also process multiple camera feeds and provide containerized solutions for Azure cloud environments. Xavier NX supports a range of I2C and GPIO interfaces. There are also USB 3.1 ports and HDMI ports.

Xavier NX is powered by a proprietary power brick. A computer running Linux or Windows is required to install the software. The software comes pre-installed with the CUDA toolkit, DeepStream, and fog simulations. Xavier NX has a micro USB port for data transfers.

Xavier NX is an ideal solution for commercial robots and advanced robotics applications. Its compact size makes it easy to fit into small spaces, and its scalable compute capabilities allow for AI acceleration at scale. And Xavier NX is a great development tool for all AI networks, including MxNet, Keras, and TensorFlow.

Whether you are using Xavier NX for robotics, computer vision, or high-resolution sensor arrays, it will deliver superior performance.

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