3U rack mount takes up to 12 NVIDIA Jetson Nano/Xavier NX boards

Jetson nano rack mount

Myelectronics.nl has launched a 19-inch 3U rack mount taking up to twelve NVIDIA Jetson Nano or Jetson Xavier NX boards building on its experience with rack mount for Raspberry Pi introduced last year. The new model also includes front removal mounting systems so that you can replace a Jetson board without having to completely remove the rack mount, and even without having to power off the remaining boards since the boards would have to be powered from the DC jack or (not recommended) the Micro USB port on the front panel. PoE is probably not an option, albeit available on the Nano board, due to mechanical constraints. Specifications listed for the rack mount: Supported SBCs NVIDIA Jetson Nano 2GB Developer Kit NVIDIA Jetson Nano Developer Kit NVIDIA Jetson Xavier NX Developer Kit 12x front-removable trays with screw set, fast click buttons for easy removal Dimensions – 13.5 cm (H) x […]

Turing Pi V2 mini-ITX cluster board takes four Raspberry Pi CM4 or NVIDIA Jetson SoMs

Turing Pi v2 mini-ITX cluster board

The Turing Pi V2 is a mini-ITX cluster board that builds on the  Turing Pi mini-ITX cluster board taking up to 7 Raspberry Pi Compute Modules introduced in 2019, but instead supports up to four Raspberry Pi CM4 (Compute Modules 4) or NVIDIA Jetson Nano/TX2 NX/Xavier NX SO-DIMM system-on-modules. The Turing Pi 2 board is equipped with two Mini PCIe sockets, two Gigabit Ethernet ports, two SATA III ports, four USB 3.0 ports, a 40-pin GPIO header, and a 24-pin ATX connector for power. Since board-to-board connectors – as found in Raspberry Pi Computer Module 4 – are not ideal for density, the company went with a design including 260-pin SO-DIMM connectors plus CM4 adapter boards, a design that allows them to also integrate other SoMs like the NVIDIA Jetson SO-DIMM modules. Turing Pi V2 specifications: SoM interface – 4x 260-pin SO-DIMM slot for up to four Raspberry Pi CM4 […]

NVIDIA TAO Transfer Learning Toolkit (TLT) 3.0 released with pre-trained models

NVIDIA TAO Transfer Learning Toolkit

NVIDIA first introduced the TAO (Train, Adapt and Optimize) framework to eases AI model training on NVIDIA GPU’s as well as NVIDIA Jetson embedded platforms last April during GTC 2021. The company has now announced the release of the third version of the TAO Transfer Learning Toolkit (TLT 3.0) together with some new pre-trained models at CVPR 2021 (2021 Conference on Computer Vision and Pattern Recognition). The newly released pre-trained models are applicable to computer vision and conversational AI, and NVIDIA claims the release provides a set of powerful productivity features that boost AI development by up to 10 times. Highlights of TAO Transfer Learning Toolkit 3.0 Various computer vision pre-trained models for Computer vision: Body Pose estimation model that supports real-time inference on edge with 9x faster inference performance than the OpenPose model. Emotion recognition Facial landmark License plate detection and recognition Heart rate estimation Gesture recognition Gaze estimation […]

NVIDIA Jetson AGX Xavier Industrial module adds lockstep Cortex-R5 cluster, ECC RAM, and more

NVIDIA Jetson AGX Xavier Industrial

NVIDIA Jetson AGX Xavier is the most powerful module from the Jetson family packing 32 TOPS of AI inference performance. But with some customers wanting to use the embedded AI computer in harsher conditions, the company has now introduced a rugged version of the module with NVIDIA Jetson AGX Xavier Industrial. Some changes included a slightly lower performance (30 TOPS) to cater for an expanded temperature range, a dual-core Cortex-R5 cluster in lockstep, ECC memory, and compliance with shock and vibration standards. NVIDIA Jetson AGX Xavier Industrial specifications with bold highlights showing differences / new features: CPU – 8-core NVIDIA Carmel Arm v8.2 64-bit CPU with 8MB L2 + 4MB L3 GPU – NVIDIA Volta architecture with 512 NVIDIA CUDA cores and 64 Tensor cores for up to 20 TOPS (INT8) (Note: the standard version support 22 TOPS) DL Accelerator – 2x NVDLA accelerators for up to 10 TOPS (INT8) […]

NEON-2000-JNX series AI Camera Features NVIDIA Jetson Xavier NX SOM for AIoT Applications

NEON-2000-JNX series AI camera

Machine vision applications highlight the complexity of implementation due to the requirement of interfacing several devices. These devices include image sensor modules, cables, GPU modules, and memory units, thus increasing the time for development and deployment. ADLINK’s NEON-2000-JNX series AI camera aims to simplify the deployment of edge machine vision and AIoT use cases. NEON-2000-JNX series AI camera comes with an inbuilt ADLINK’s new edge vision analytics software known as the EVA SDK. The software reduces the time in designing and creating proofs-of-concept, which leads to quicker deployment of applications. Users get a wide range of options for selecting field-ready “application plug-ins and ADLINK-optimized AI models”. This ensures the quality of vision AI and eases the building of use cases with lesser software code and programs. Additionally, the preview function allows quicker verification of AI Inference flow. We saw the launch of NVIDIA’s Jetson Xavier NX SOM in April 2020 […]

Top 5 most powerful Arm SBC’s & Devkits in 2021

Most Powerful Arm SBCs development kit 2021

While companies like Hardkernel, Raspberry Pi, Orange Pi, and FriendlyArm offers affordable, great little Arm Linux development boards that are suitable for many projects, in some cases, your requirements may lead you to spend a bit more for either extra CPU power, more memory, AI processing power, faster I/Os and so on. That’s why I did a list of the most powerful Arm single board computers in late 2017, but with over three years passed since then an update is warranted. The boards from the list must be easily purchasable from individuals (with the cash to spare) or small companies, so we’ll exclude hard-to-source hardware, as well as Arm server boards like Ampere eMAG motherboard, that do not really qualify as single board computers. Snapdragon 888 Mobile Hardware Development Kit While there are plenty of Cortex-A72/A73 development boards around, it’s much hardware to find one with more recent Cortex-X1 or […]

Windows Performance on an Intel NUC 11 Enthusiast Phantom Canyon NUC11PHKi7C

NUC11PHKi7C skull

The Enthusiast Phantom Canyon is Intel’s flagship product from its latest NUC 11 range of mini PCs. Specifically targeting gamers it includes an NVIDIA RTX 2060 GPU. In this article, I take a brief look at the performance under Windows and compare it against Intel’s previous NUC with a discrete GPU: the NUC 9 Extreme Ghost Canyon. Hardware Overview The NUC11PHKi7C physically consists of a 221 x 142 x 42 mm (8.70 x 5.59 x 1.65 inches) rectangular plastic case which is remarkable because of its size and is similar to just a graphics card like NVIDIA’s GeForce RTX 2060 Founders Edition (229 x 113 x 35 mm). It is an actively cooled mini PC and uses Intel’s 10 nm Core i7-1165G7 Tiger Lake processor which is a quad-core 8-thread 2.80 GHz processor boosting to 4.70 GHz with Intel’s Iris Xe Graphics. But it also includes NVIDIA’s N18E-G1-B notebook graphics […]

Zymbit HSM4 & HSM6 security modules work with embedded Linux hardware, Raspberry Pi, Jetson Nano

Zymbit HSM4

Zymbit Zymkey security modules, now called Zymkey4i, were first introduced several years ago. Based on the Microchip ATECC508A CryptoAuthentication chip, the modules were available as a USB stick, an I2C module for Raspberry Pi boards, or an SMT component, and designed to enable multifactor device ID & authentication, data encryption & signing, key storage & generation, and physical tamper detection. The company has now informed CNX Software they had launched HSM4 cryptographic protection module and HSM6 hardware wallet with a different form factor for easy integration into embedded applications, and devkits compatible with Jetson Nano and Raspberry Pi SBCs. Zymbit HSM4 cryptographic protection module & devkit HSM4 crypto module key features and specifications: HSM4 is built upon Zymkey4i module, and integrates an Arm Cortex-M0 microcontroller, as well as a secure element likely to be Microchip ATECC508A, or the more recent ATECC608B CryptoAuthentication chip if the company upgrade System Identity & […]

Memfault IoT and embedded debugging platform