Nvidia Tegra X1 Category - Page 4 of 16 - CNX Software

September 21, 2022 by Jean-Luc Aufranc (CNXSoft) - 9 Comments

$199+ NVIDIA Jetson Orin Nano system-on-module delivers up to 40 TOPS

NVIDIA Jetson Orin Nano system-on-module (SoM) is an update to the Jetson Nano entry-level Edge AI and robotics module that delivers up to 40 TOPS of AI performance, meaning it’s up to 80 times faster than the original module. The new SoM features an hexa-core Arm Cortex-A78AE processor, an up to 1024-core NVIDIA Ampere architecture GPU with 32 Tensor cores, up to 8GB RAM, and the same 260-pin SO-DIMM connector found in the Jetson Orin NX modules. Two versions are offered with the following specifications: That means the Jetson Orin family has now six modules ranging from 20 TOPS to 275 TOPS. There’s no specific development kit for the Jetson Orin Nano SoM since it can be emulated on the NVIDIA Jetson AGX Orin developer kit, and supported by the JetPack 5.0.2 SDK based on Ubuntu 20.04. NVIDIA has tested some dense INT8 and FP16 pre-trained models from NGC and […]

September 5, 2022 by Jean-Luc Aufranc (CNXSoft) - No Comments

NVIDIA Jetson Xavier NX fanless embedded box PC features four HDMI input ports

NVIDIA Xavier NX embedded box pc four HDMI inputs

AAEON BOXER-8256AI is a fanless embedded box PC equipped with an NVIDIA Jetson Xavier NX system-on-module, offering four HDMI input ports – two Full HD, two 4K capable -, as well as two HDMI outputs for smart healthcare equipment, digital signage, and entertainment. The embedded computer comes with 8GB RAM and a 16GB flash provided by the NVIDIA module, supports M.2 NVMe and SATA storage, Gigabit Ethernet, plus optional WiFI, 4G, and 5G cellular connectivity through M.2 sockets. BOXER-8256AI specifications: SoM – NVIDIA Jetson Xavier NX with CPU – 6-core NVIDIA Carmel Armv8.2 64-bit CPU GPU – 384-core NVIDIA Volta GPU with 48 Tensor Cores AI accelerator – 2x NVDLA deep learning accelerators AI performance – Up to 21 TOPS at 15 Watts System Memory – 8GB LPDDR4x Storage – 16GB eMMC flash Storage – MicroSD Slot, M.2 NVMe SSD socket, SATA III port Display Interfaces – 2x HDMI […]

August 29, 2022September 2, 2022 by Jean-Luc Aufranc (CNXSoft) - 3 Comments

SyncBot educational mobile robot supports NVIDIA Xavier NX or Intel Tiger Lake controller

SyncBot educational mobile robot RBX-I2000 controller

Syncbotic Syncbot is a four-wheel autonomous mobile robot (AMR) platform for research and education that can be fitted with an NVIDIA Xavier NX or an Intel Apollo Lake/Tiger Lake-based controller running Ubuntu 20.04 operating system with ROS 2 framework, and comes with an motion control MCU board with an EtherCat master and running Zephyr OS. The robot comes with four 400W TECO servo motors, can handle up to 80kg payloads for sensors and a robotic arm, features 12V and 24V power output for sensors, four USB 3.0 ports, and can also be equipped with an eight-camera kit with Intel RealSense and ToF cameras. Syncbot AMR specifications: Robot Controller Platform (one or the other) SyncBotic A100 evaluation ki (Apollo Lake E3940) SyncBotic SBC-T800 series (Intel Tiger Lake UP3) SyncBotic SBC W series (Intel Tiger Lake UP3, waterproof version) SyncBotic NSync-200 series (NVIDIA NX) Dimensions – 200 x 190 mm STM32-based Motion […]

August 16, 2022 by Jean-Luc Aufranc (CNXSoft) - 4 Comments

NVIDIA Jetpack 5.0.2 release supports Ubuntu 20.04, Jetson AGX Orin

The NVIDIA Jetpack 5.0.2 production release is out with Ubuntu 20.04, the Jetson Linux 35.1 BSP 1 with Linux Kernel 5.10, an UEFI-based bootloader, support for Jetson AGX Orin module and developer kit, as new as updated packages such as CUDA 11.4, TensorRT 8.4.1, cuDNN 8.4.1. NVIDIA Jetson modules and developer kits are nice little pieces of hardware for AI workloads, but the associated NVIDIA Jetpack SDK was based on the older Ubuntu 18.04 which was not suitable for some projects. But the good news is that Ubuntu 20.04 was being worked on and initially available through the Jetpack 5.0.0/5.0.1 developer previews, and NVIDIA Jetpack 5.0.2 SDK is the first production release with support for Ubuntu 20.04. Besides the upgrade to Ubuntu 20.04, the Jetpack 5.0.2 SDK also adds support for both the Jetson AGX Orin Developer Kit and the newly-available Jetson AGX Orin 32 GB production module. It still […]

August 3, 2022October 13, 2022 by Jean-Luc Aufranc (CNXSoft) - 4 Comments

NVIDIA Jetson AGX Orin 32GB production module is now available

NVIDIA Jetson AGX Orin 32GB production module is now in mass production and available after the 12-core Cortex-A78E system-on-module was first announced in November 2021, and the Jetson AGX Orin developer kit was launched last March for close to $2,000. Capable of up to 200 TOPS of AI inference performance, or up to 6 times faster than the Jetson AGX, the NVIDIA Jetson AGX Orin 32GB can be used for AI, IoT, embedded, and robotics deployments, and NVIDIA says nearly three dozen partners are offering commercially available products based on the new module. Here’s a reminder of NVIDIA Jetson AGX Orin 32GB specifications: CPU – 8-core Arm Cortex-A78AE v8.2 64-bit processor with 2MB L2 + 4MB L3 cache GPU / AI accelerators NVIDIA Ampere architecture with 1792 NVIDIA CUDA cores and 56 Tensor Cores @ 1 GHz DL Accelerator – 2x NVDLA v2.0 Vision Accelerator – PVA v2.0 (Programmable Vision […]

August 2, 2022August 2, 2022 by Jean-Luc Aufranc (CNXSoft) - No Comments

reComputer J101/J202 carrier boards are designed for Jetson Nano/NX/TX2 NX SoM

Seeed Studio’s reComputer J101 & J202 are carrier boards with a similar form factor as the ones found in NVIDIA Jetson Nano and Jetson Xavier NX developer kits, but with a slightly different feature set. The reComputer J101 notably features different USB Type-A/Type-C ports, a microSD card, takes power from a USB Type-C port, and drops the DisplayPort connector, while the reComputer J201 board replaces the micro USB device port with a USB Type-C port, adds a CAN Bus interface, and switches to 12V power input instead of 19V. The table below summarizes the features and differences between the Jetson Nano devkit (B1), reComputer J101, Jetson Xavier NX devkit, and reComputer J202. Note the official Jetson board should also support production SoM with eMMC flash, but they do ship with a non-production SoM with a built-in MicroSD card socket instead. The carrier boards are so similar that if NVIDIA would […]

July 12, 2022July 12, 2022 by Jean-Luc Aufranc (CNXSoft) - 11 Comments

Benchmarks comparison between UP 4000, Raspberry Pi 4, UP board, and Jetson Nano

UP 4000 vs UP Board vs Raspberry Pi 4-vs-Jetson-Nano Phoronix benchmarks

We wrote about the UP 4000 SBC with an Intel Apollo Lake processor and Raspberry Pi form factor yesterday. But today, I noticed the UP community had put up a benchmarks comparison between the UP 4000 board, the original UP board (Atom x5-8350), the Raspberry Pi 4, and NVIDIA Jetson Nano. They used several of the Phoronix Test Suite benchmarks running on Ubuntu 20.04 (x86) or Ubuntu 18.04 (Arm) on all four boards. The UP 4000 board used featured an Intel Celeron N3350 dual-core processor @ 2.40GHz, the 2GB RAM version of the UP Board, an RPi 4 with 4GB RAM, and a Jetson Nano developer kit with 4GB RAM. As one would have expected, the UP 4000 is ahead in most tests, even though they did not select a model with a quad-core processor such as a Pentium N4200. Note that reading the table may be confusing as for […]

May 17, 2022May 17, 2022 by Jean-Luc Aufranc (CNXSoft) - 15 Comments

Turing Pi 2 mini-ITX cluster board supports RK3588 based Turing RK1, Raspberry Pi CM4, and NVIDIA Jetson SoMs (Crowdfunding)

We first covered the Turing Pi V2 mini-ITX cluster board supporting up to four Raspberry Pi CM4 or NVIDIA Jetson SO-DIMM system-on-module in August 2021. The company has now launched the Turing Pi 2 on Kickstarter with a little surprise: the Turing RK1 module with Rockchip RK3588 Cortex-A76/A55 processor and up to 32GB RAM. The board allows you to mix and match modules (e.g. 3x RPi CM4 + 1x Jetson module as on the photo below), and with SATA ports, Gigabit Ethernet networking, USB 3.0 ports, mPCIe socket, you could build a fairly powerful homelab, learn Kubernetes, or self-host your own apps. Turing Pi 2 specifications: SoM interface – 4x 260-pin SO-DIMM slots for up to four Raspberry Pi CM4 with Broadcom quad-core Cortex-A72 processor, up to 8GB RAM, up to 32GB eMMC flash (adapter needed) NVIDIA Jetson Nano/TX2 NX/Xavier NX SO-DIMM system-on-modules with up to 6x Armv8 cores, and […]