Jetson Xavier NX/Introduction/Overview: Difference between revisions

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{{JetsonXavierNX/Head|previous=Introduction|next=Introduction/Developer_Kit|title=NVIDIA Jetson Xavier NX SoM Overview|description=This page provides a general overview of the Jetson Xavier NX SoM|keywords=SoM,System on Module,hardware,peripherals,processor,processor specification,peripherals,package,developer kit,developer tools,specification}}
{{JetsonXavierNX/Head|previous=Introduction|next=Introduction/Developer_Kit|title=NVIDIA Jetson Xavier NX SoM Overview|metadescription=This page provides a general overview of the Jetson Xavier NX SoM|metakeywords=SoM, System on Module, hardware, peripherals, processor, processor specification, peripherals, package, Jetson Xavier NX developer kit, Jetson Xavier NX developer tools, specification, Jetson AGX Xavier Developer Kit, Volta GPU, Jetson Xavier NX Block Diagram}}
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* '''Huge Performance'''
* '''Huge Performance'''


This platform delivers up to 21 TOPS at 15 W, making it ideal for high-performance compute and AI in embedded and edge systems with size and power-constrained requirements. With 384-CUDA/48-Tensor cores Volta GPU, 2 NVIDIA Deep Learning Accelerators (NVDLA) engines, 6 Carmel ARM CPUs, video encode/decode hardware accelerators, plus 51GB/s of memory bandwidth, make it the ideal platform to run multiple modern neural networks in parallel and process high-resolution data from multiple sensors simultaneously.
This platform delivers up to 21 TOPS at 15 W, making it ideal for high-performance computing and AI in embedded and edge systems with size and power-constrained requirements. With 384-CUDA/48-Tensor cores Volta GPU, 2 NVIDIA Deep Learning Accelerators (NVDLA) engines, 6 Carmel ARM CPUs, video encode/decode hardware accelerators, plus 51GB/s of memory bandwidth, make it the ideal platform to run multiple modern neural networks in parallel and process high-resolution data from multiple sensors simultaneously.


* '''Power efficiency'''
* '''Power efficiency'''
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===Developer Kit===
===Jetson Xavier NX Developer Kit===
The developer kit comes with 2x MIPI-CSI 15 pin camera connectors to enable video applications, as well as a Gigabit Ethernet port, WiFi, Bluetooth, HDMI output, Display Port output, 4x USB ports, USB 2.0 Micro-B port, and 40-pin header port. A 19V/3.4A power supply is included to power the Xavier NX developer kit. A micro SDcard (not included) is required to flash the system image and boot the board. Other features offered in the development kit accessible trough the 40-pin header port are:
The developer kit comes with 2x MIPI-CSI 15 pin camera connectors to enable video applications, as well as a Gigabit Ethernet port, WiFi, Bluetooth, HDMI output, Display Port output, 4x USB ports, USB 2.0 Micro-B port, and 40-pin header port. A 19V/3.4A power supply is included to power the Xavier NX developer kit. A micro SD card (not included) is required to flash the system image and boot the board. Other features offered in the development kit accessible through the 40-pin header port are:


* GPIO
* GPIO
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* PCIe
* PCIe


==Developer Tools==
==Jetson Xavier NX Developer Tools==


Software development can be done using NVIDIA's Jetpack, as in other NVIDIA Jetson boards. The image generated by Jetpack can be flashed into an SDCard to boot Jetson Xavier NX. Jetpack provides Ubuntu 18.04 OS with kernel 4.9. Please follow [https://developer.nvidia.com/embedded/jetpack  JetPack installation steps]. For AI and parallel computing applications, Jetpack provides CUDA, cuDNN, DeepStream, and TensorRT. Additionally, tools like nvpmodel to control the power/performance profile and tegrastats that provide CPUs and GPU stats, come with the filesystem.
Software development can be done using NVIDIA's Jetpack, as in other NVIDIA Jetson boards. The image generated by Jetpack can be flashed into an SDCard to boot Jetson Xavier NX. Jetpack provides Ubuntu 18.04 OS with kernel 4.9. Please follow [https://developer.nvidia.com/embedded/jetpack  JetPack installation steps]. For AI and parallel computing applications, Jetpack provides CUDA, cuDNN, DeepStream, and TensorRT. Additionally, tools like nvpmodel to control the power/performance profile and tegrastats that provide CPUs and GPU stats, come with the filesystem.