Difference between revisions of "Jetson Nano"

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Useful for deploying computer vision and deep learning, Jetson Nano runs Linux and provides 472 GFLOPS of FP16 compute performance with 5-10W of power consumption.
 
Useful for deploying computer vision and deep learning, Jetson Nano runs Linux and provides 472 GFLOPS of FP16 compute performance with 5-10W of power consumption.
  
Jetson Nano is currently available as the '''[https://developer.nvidia.com/embedded/buy/jetson-nano-devkit Jetson Nano Developer Kit]''' for $99, with the production compute module coming in June 2019.  See the wiki of the other Jetson's '''[[Jetson|here]]'''.
+
Jetson Nano is currently available as the '''[https://developer.nvidia.com/embedded/buy/jetson-nano-devkit Jetson Nano Developer Kit]''' for $99, and the production '''[https://developer.nvidia.com/embedded/jetson-nano compute module]'''.  See the wiki of the other Jetson's '''[[Jetson|here]]'''.
  
 
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The [https://developer.nvidia.com/embedded/buy/jetson-nano-devkit Jetson Nano Developer Kit] is an easy way to get started using Jetson Nano, including the module, carrier board, and software.  It costs $99 and is available from distributors worldwide.
 
The [https://developer.nvidia.com/embedded/buy/jetson-nano-devkit Jetson Nano Developer Kit] is an easy way to get started using Jetson Nano, including the module, carrier board, and software.  It costs $99 and is available from distributors worldwide.
  
[[File:Jetson_Nano_Developer_Kit.png|450px|right]]
+
[[File:Jetson_Nano_Developer_Kit_P3449_B01.jpg|450px|right]]
  
 
=== What's Included ===
 
=== What's Included ===
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** 5V⎓2A Micro-USB adapter (see [https://www.adafruit.com/product/1995 Adafruit GEO151UB])
 
** 5V⎓2A Micro-USB adapter (see [https://www.adafruit.com/product/1995 Adafruit GEO151UB])
 
** 5V⎓4A DC barrel jack adapter, 5.5mm OD x 2.1mm ID x 9.5mm length, center-positive (see [https://www.adafruit.com/product/1466 Adafruit 1446])
 
** 5V⎓4A DC barrel jack adapter, 5.5mm OD x 2.1mm ID x 9.5mm length, center-positive (see [https://www.adafruit.com/product/1466 Adafruit 1446])
** See [https://devtalk.nvidia.com/default/topic/1048640/jetson-nano/power-supply-considerations-for-jetson-nano-developer-kit/ Power Supply Considerations] for more information.
+
** See the [[Jetson Nano#Power_Supplies|Power Supplies]] section below and [https://devtalk.nvidia.com/default/topic/1048640/jetson-nano/power-supply-considerations-for-jetson-nano-developer-kit/ Power Supply Considerations] for more information.
 
* MicroSD card (16GB UHS-1 recommended minimum)
 
* MicroSD card (16GB UHS-1 recommended minimum)
  
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= Software Support =  
 
= Software Support =  
<div style="width:50%;column-count:2;-moz-column-count:2;-webkit-column-count:2">
+
<div style="width:40%;column-count:2;-moz-column-count:2;-webkit-column-count:2">
* [https://developer.nvidia.com/embedded/jetpack JetPack 4.2]
+
* [https://developer.nvidia.com/embedded/jetpack JetPack 4.2.2]
* [https://developer.nvidia.com/embedded/linux-tegra Linux4Tegra R32.1] (L4T)
+
* [https://developer.nvidia.com/embedded/linux-tegra Linux4Tegra R32.2.1] (L4T)
 
* Linux kernel 4.9
 
* Linux kernel 4.9
* Ubuntu 18.04 LTS aarch64
+
* Ubuntu 18.04 aarch64
* CUDA Toolkit 10.0
+
* [https://developer.nvidia.com/cuda-toolkit CUDA Toolkit] 10.0.326
* cuDNN 7.3.1
+
* [https://developer.nvidia.com/cudnn cuDNN] 7.5.0
* [https://developer.nvidia.com/tensorrt TensorRT] 5.0.6
+
* [https://developer.nvidia.com/tensorrt TensorRT] 5.1.6
* TensorFlow 1.31.1
+
* [https://docs.nvidia.com/deeplearning/frameworks/install-tf-jetson-platform/index.html TensorFlow] 1.14.0
 
* [https://developer.nvidia.com/embedded/visionworks VisionWorks] 1.6
 
* [https://developer.nvidia.com/embedded/visionworks VisionWorks] 1.6
 
* OpenCV 3.3.1
 
* OpenCV 3.3.1
* OpenGL 4.6  
+
* OpenGL 4.6 / OpenGL ES 3.2.5
* OpenGL ES 3.2
+
* Vulkan 1.1.1
* EGL 1.5
+
* [http://developer.nvidia.com/embedded/dlc/l4t-multimedia-api-reference-32-1 L4T Multimedia API] (Argus 0.97)
* Vulkan 1.1
 
 
* GStreamer 1.14.1
 
* GStreamer 1.14.1
 
* V4L2 media controller support
 
* V4L2 media controller support
 +
* [https://developer.nvidia.com/nsight-systems NVIDIA Nsight Systems] 2019.4
 +
* [https://developer.nvidia.com/nsight-graphics NVIDIA Nsight Graphics] 2019.2
 +
* [https://developer.nvidia.com/nsight-compute NVIDIA Nsight Compute] 1.0
 
</div>
 
</div>
 +
 +
See the '''[[Jetson Zoo]]''' for more software packages to install on top of JetPack.
  
 
= Guides and Tutorials =
 
= Guides and Tutorials =
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<div style="width:75%;column-count:2;-moz-column-count:2;-webkit-column-count:2">
 
<div style="width:75%;column-count:2;-moz-column-count:2;-webkit-column-count:2">
 
* [https://docs.nvidia.com/jetson/l4t/index.html L4T Kernel Development Guide]
 
* [https://docs.nvidia.com/jetson/l4t/index.html L4T Kernel Development Guide]
 +
* [[Jetson/Clone|Clone & Restore]]
 +
* [https://github.com/jtagxhub/jetpack-agx-build Jetson Nano Build Assistant Scripts]
 +
* [[Jetson/FAQ/BSP|BSP FAQ]]
 
* [https://devtalk.nvidia.com/default/topic/1048640/jetson-nano/power-supply-considerations-for-jetson-nano-developer-kit/ Power Supply Considerations]
 
* [https://devtalk.nvidia.com/default/topic/1048640/jetson-nano/power-supply-considerations-for-jetson-nano-developer-kit/ Power Supply Considerations]
 
* [[Jetson/Nano/Upstream|Upstream Development Guide]]
 
* [[Jetson/Nano/Upstream|Upstream Development Guide]]
 
* [https://devtalk.nvidia.com/default/topic/1049811/jetson-nano/cuda-and-vision-works-demos/post/5328027/#5328027 CUDA and VisionWorks Samples]
 
* [https://devtalk.nvidia.com/default/topic/1049811/jetson-nano/cuda-and-vision-works-demos/post/5328027/#5328027 CUDA and VisionWorks Samples]
 +
* [https://devtalk.nvidia.com/default/topic/1052324/jetson-nano/jetson-nano-aws-greengrass-/post/5341970/#5341970 Install AWS Greengrass] - IoT framework
 
* [https://support.rackspace.com/how-to/create-a-linux-swap-file/ Mounting a SWAP File]
 
* [https://support.rackspace.com/how-to/create-a-linux-swap-file/ Mounting a SWAP File]
 +
* [https://www.jetsonhacks.com/2019/04/25/jetson-nano-run-on-usb-drive/ Booting from SSD]
 
* [https://www.jetsonhacks.com/nvidia-jetson-nano-j41-header-pinout/ GPIO Header Pin-out]
 
* [https://www.jetsonhacks.com/nvidia-jetson-nano-j41-header-pinout/ GPIO Header Pin-out]
 +
* [https://github.com/jwatte/jetson-gpio-example GPIO Direct Access from C]
 +
* [https://github.com/rt-net/JetsonNano_DT_SPI Enabling SPI in DTS (R32.1)]
 +
* [https://github.com/gtjoseph/jetson-nano-support/tree/l4t_32.2.1 Enabling SPI in DTS (R32.2.1)]
 
* [https://devtalk.nvidia.com/default/topic/1050026/jetson-nano/read-serial-number-of-jetson-nano/post/5329191/#5329191 Reading Serial Number]
 
* [https://devtalk.nvidia.com/default/topic/1050026/jetson-nano/read-serial-number-of-jetson-nano/post/5329191/#5329191 Reading Serial Number]
 +
* [https://gist.github.com/dusty-nv/e4314241677cf38f40d556931d0c4a38 Reading MAC Address]
 
* [https://github.com/rbonghi/jetson_easy jetson_easy] - automatic setup/scripting
 
* [https://github.com/rbonghi/jetson_easy jetson_easy] - automatic setup/scripting
 
* [https://github.com/rbonghi/jetson_stats jetson_stats] - jtop, service and other tools
 
* [https://github.com/rbonghi/jetson_stats jetson_stats] - jtop, service and other tools
 +
* [https://github.com/pvaret/rtl8192cu-fixes rtl8192cu-fixes] - patched Edimax EW-7811 Wi-Fi driver
 
</div>
 
</div>
  
 
=== Deep Learning ===
 
=== Deep Learning ===
 +
See the '''[[Jetson Zoo]]''' for more resources on deploying AI and deep learning.
 +
 
* [https://github.com/dusty-nv/jetson-inference Hello AI World] (jetson-inference)
 
* [https://github.com/dusty-nv/jetson-inference Hello AI World] (jetson-inference)
* [https://developer.nvidia.com/embedded/downloads#?search=TensorFlow TensorFlow 1.13.1 Installer] (pip wheel)
+
* [https://developer.nvidia.com/embedded/downloads#?search=TensorFlow TensorFlow Installer] (pip wheel)
* [https://devtalk.nvidia.com/default/topic/1049071/jetson-nano/pytorch-for-jetson-nano/ PyTorch 1.1 Installer] (pip wheel)
+
* [https://devtalk.nvidia.com/default/topic/1049071/jetson-nano/pytorch-for-jetson-nano/ PyTorch Installer] (pip wheel)
 
* [https://devtalk.nvidia.com/default/topic/1049293/jetson-nano/i-was-unable-to-compile-and-install-mxnet-on-the-jetson-nano-is-there-an-official-installation-tutorial-/post/5326170/#5326170 MXNet 1.4 Installer] (pip wheel)
 
* [https://devtalk.nvidia.com/default/topic/1049293/jetson-nano/i-was-unable-to-compile-and-install-mxnet-on-the-jetson-nano-is-there-an-official-installation-tutorial-/post/5326170/#5326170 MXNet 1.4 Installer] (pip wheel)
 +
* [https://devtalk.nvidia.com/default/topic/1065203/jetson-nano/paddlepaddle-for-jetson-nano-version-1-5-2-now-available/ PaddlePaddle Installer] (pip wheel)
 
* [https://devtalk.nvidia.com/default/topic/1050377/jetson-nano/deep-learning-inference-benchmarking-instructions/ Deep Learning Inference Benchmarking Instructions]
 
* [https://devtalk.nvidia.com/default/topic/1050377/jetson-nano/deep-learning-inference-benchmarking-instructions/ Deep Learning Inference Benchmarking Instructions]
 
* [https://medium.com/swlh/how-to-run-tensorflow-object-detection-model-on-jetson-nano-8f8c6d4352e8 TensorFlow Object Detection With TensorRT] (TF-TRT)
 
* [https://medium.com/swlh/how-to-run-tensorflow-object-detection-model-on-jetson-nano-8f8c6d4352e8 TensorFlow Object Detection With TensorRT] (TF-TRT)
 
+
* [https://developer.ridgerun.com/wiki/index.php?title=GstInference RidgeRun's GstInference]
See the [https://github.com/NVIDIA-AI-IOT/ NVIDIA AI-IoT GitHub] for other coding resources on deploying AI and deep learning.
+
* [https://developer.ridgerun.com/wiki/index.php?title=R2Inference RidgeRun's R2Inference]
  
 
=== Robotics ===
 
=== Robotics ===
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* [http://wiki.ros.org/melodic/Installation/Ubuntu ROS Melodic] (ROS install guide)
 
* [http://wiki.ros.org/melodic/Installation/Ubuntu ROS Melodic] (ROS install guide)
 
* [https://github.com/dusty-nv/ros_deep_learning ros_deep_learning] (jetson-inference nodes)
 
* [https://github.com/dusty-nv/ros_deep_learning ros_deep_learning] (jetson-inference nodes)
 +
 +
=== Multimedia ===
 +
* [https://developer.ridgerun.com/wiki/index.php?title=GstInterpipe RidgeRun's GstInterpipe] (GStreamer plug-in for communication between two or more independent pipelines)
 +
* [https://developer.ridgerun.com/wiki/index.php?title=GstWebRTC RidgeRun's GstRRWebRTC] (GStreamer plug-in that turns pipelines into WebRTC compliant endpoints)
 +
* [https://developer.ridgerun.com/wiki/index.php?title=GstRtspSink RidgeRun's GstRTSPSink] (GStreamer element for high performance streaming to multiple computers using the RTSP/RTP protocols)
 +
* [https://developer.ridgerun.com/wiki/index.php?title=GStreamer_Daemon RidgeRun's Gstreamer Daemon - GstD] (GStreamer framework for controlling audio and video streaming using TCP connection messages)
 +
* [http://developer.ridgerun.com/wiki/index.php?title=GstCUDA RidgeRun's GstCUDA] (RidgeRun CUDA ZeroCopy for GStreamer)
 +
* [https://developer.ridgerun.com/wiki/index.php?title=GStreamer_Pan_Tilt_Zoom_and_Rotate_Element RidgerRun's GstPTZR] (GStreamer Pan Tilt Zoom and Rotate Element)
 +
* [https://developer.ridgerun.com/wiki/index.php?title=GStreamer_Color_Transfer RidgeRun's GstColorTransfer] (GStreamer plug-in that transfers the color scheme from a reference to a target image)
 +
 +
=== V4L2 drivers for cameras ===
 +
 +
*RidgeRun has a [https://developer.ridgerun.com/wiki/index.php?title=V4L2_drivers_available_for_Jetson_SoCs list of drivers already supported in Jetson], please check if the driver that you need is already there. Otherwise, RidgeRun offers [https://developer.ridgerun.com/wiki/index.php?title=V4L2_driver_for_camera_sensor_or_capture_chip services to create the driver for you]
 +
 +
=== Design FAQs ===
 +
 +
There are some useful FAQs for Jetson Nano design, link is [[Jetson_Nano/FAQ|here]].
 +
<br />
 +
<br />
  
 
= Ecosystem Products and Sensors =
 
= Ecosystem Products and Sensors =
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==== Cameras ====
 
==== Cameras ====
 +
* Allied Vision MIPI CSI-2 (one open-source CSI-2 driver for all cameras on [https://github.com/alliedvision/linux_nvidia_jetson Github.com])
 +
** [https://www.alliedvision.com/en/products/embedded-vision-cameras/detail/Alvium/1500%20C-050.html Alvium 1500 C-050] 0.5MP PYTHON 480
 +
** [https://www.alliedvision.com/en/products/embedded-vision-cameras/detail/Alvium/1500%20C-120.html Alvium 1500 C-120] 1.2MP AR0135CS
 +
** [https://www.alliedvision.com/en/products/embedded-vision-cameras/detail/Alvium/1500%20C-210.html Alvium 1500 C-210] 2.1MP AR0521
 +
** [https://www.alliedvision.com/en/products/embedded-vision-cameras/detail/Alvium/1500%20C-500.html Alvium 1500 C-500] 5MP AR0521
 +
** [https://www.alliedvision.com/en/products/embedded-vision-cameras/detail/Alvium/1800%20C-040.html Alvium 1800 C-040] 0.4MP Sony IMX287
 +
** [https://www.alliedvision.com/en/products/embedded-vision-cameras/detail/Alvium/1800%20C-158.html Alvium 1800 C-158] 1.6MP Sony IMX273
 +
* Allied Vision USB3 Vision
 +
** [https://www.alliedvision.com/en/products/embedded-vision-cameras/detail/Alvium/1800%20U-040.html Alvium 1800 U-040] 0.4MP Sony IMX287
 +
** [https://www.alliedvision.com/en/products/embedded-vision-cameras/detail/Alvium/1800%20U-050.html Alvium 1800 U-050] 0.5MP PYTHON 480
 +
** [https://www.alliedvision.com/en/products/embedded-vision-cameras/detail/Alvium/1800%20U-120.html Alvium 1800 U-120] 1.2MP AR0135CS
 +
** [https://www.alliedvision.com/en/products/embedded-vision-cameras/detail/Alvium/1800%20U-158.html Alvium 1800 U-158] 1.6MP Sony IMX273
 +
** [https://www.alliedvision.com/en/products/embedded-vision-cameras/detail/Alvium/1800%20U-500.html Alvium 1800 U-500] 5MP AR0521
 +
** [https://www.alliedvision.com/en/products/embedded-vision-cameras/detail/Alvium/1800%20U-501m%20NIR.html Alvium 1800 U-501m NIR] 5MP AR0522
 +
* DCDZ [https://item.taobao.com/item.htm?ft=t&id=618819673262 H2C-NCB] (HDMI to CSI2 camera board)
 +
* e-con Systems [https://www.e-consystems.com/nvidia-cameras/jetson-nano-cameras/5mp-mipi-nano-camera.asp e-CAM50_CUNANO] (5MP AR0521 MIPI Camera)
 
* e-con Systems [https://www.e-consystems.com/nvidia-cameras/jetson-nano-cameras/3mp-mipi-camera.asp e-CAM30_CUNANO] (3.4 MP MIPI Camera)
 
* e-con Systems [https://www.e-consystems.com/nvidia-cameras/jetson-nano-cameras/3mp-mipi-camera.asp e-CAM30_CUNANO] (3.4 MP MIPI Camera)
 +
* e-con Systems [https://www.e-consystems.com/nvidia-cameras/jetson-agx-xavier-cameras/stereo-camera.asp STEEReoCAM™] (2.0 MP MIPI Stereo Camera)
 +
* Logitech [https://www.logitech.com/en-us/product/hd-webcam-c270 C270] (USB webcam)
 
* Logitech [https://www.amazon.com/Logitech-Widescreen-Calling-Recording-Desktop/dp/B006JH8T3S C920] (USB webcam)
 
* Logitech [https://www.amazon.com/Logitech-Widescreen-Calling-Recording-Desktop/dp/B006JH8T3S C920] (USB webcam)
 
* Leopard Imaging [https://leopardimaging.com/product/li-imx219-mipi-ff-nano/ LI-IMX219-MIPI-FF-NANO] (IMX219 sensor)  
 
* Leopard Imaging [https://leopardimaging.com/product/li-imx219-mipi-ff-nano/ LI-IMX219-MIPI-FF-NANO] (IMX219 sensor)  
 
* Raspberry Pi [https://www.raspberrypi.org/products/camera-module-v2/ Camera v2] (IMX219 sensor)
 
* Raspberry Pi [https://www.raspberrypi.org/products/camera-module-v2/ Camera v2] (IMX219 sensor)
 +
* Appro [http://www.appropho.com/products_ii_en.html?id=187&type=36#pdb04 AP-IMX179-MIPIx1] (IMX179 sensor)
 +
* Appro [http://www.appropho.com/products_ii_en.html?id=187&type=36#pdc04 AP-IMX290-MIPIx1] (IMX290 sensor)
 
* Stereolabs [https://www.stereolabs.com/ ZED] (stereo camera)
 
* Stereolabs [https://www.stereolabs.com/ ZED] (stereo camera)
  
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* Auvidea [https://auvidea.eu/product/70780/ JN30] (module carrier)
 
* Auvidea [https://auvidea.eu/product/70780/ JN30] (module carrier)
 
* Auvidea [https://auvidea.eu/product/70781/ JN30-LC] (module carrier)
 
* Auvidea [https://auvidea.eu/product/70781/ JN30-LC] (module carrier)
 +
* ConnectTech [http://connecttech.com/product/photon-jetson-nano-ai-camera-platform/ Photon] (module carrier)
 +
* DCDZ(冬虫电子) [[Jetson_Nano/ncb00 | NCB00]] (module carrier)
 +
* Leopard Imaging [https://leopardimaging.com/product/li-nano-cb/ LI-NANO-CB] (module carrier)
 +
* Realtimes [http://www.realtimes.cn/cn/product/rtso-6001.html RTSO-6001] (module carrier)
  
 
==== Enclosures ====
 
==== Enclosures ====
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* Jetson [https://www.thingiverse.com/thing:3547555 NanoMesh Mini] (3D-printable enclosure)
 
* Jetson [https://www.thingiverse.com/thing:3547555 NanoMesh Mini] (3D-printable enclosure)
 
* [https://github.com/57Bravo/jetson_nano_enc jetson_nano_enc] (3D-printable enclosure)
 
* [https://github.com/57Bravo/jetson_nano_enc jetson_nano_enc] (3D-printable enclosure)
 +
* [https://github.com/dudasdavid/Jetson-nano-case Jetson-nano-case] (3D-printable enclosure)
 +
* [https://www.amazon.com/Geekworm-NVIDIA-Enclosure-Control-Developer/dp/B07RRRX121 Geekworm Jetson Nano Case] (metal enclosure)
 +
* [https://www.amazon.com/GeeekPi-NVIDIA-Cooling-Control-Developer/dp/B07VVJNXMB/ GeeekPi Jetson Nano Case] (metal enclosure)
 +
* [https://en.miivii.com/index.php?s=index/category/index&id=102 MiiVii Lite Nano] (metal enclosure)
 +
* [https://www.amazon.com/Case-Jetson-Nano-Compatible-Peripherals/dp/B07VTNSS4S Waveshare Jetson Nano Case] (metal enclosure)
 +
* [https://www.kksb-cases.us/collections/nvidia/products/kksb-jetson-nano-case-black# KKSB Jetson Nano Case] (metal enclosure)
 +
* [https://www.iotamy.com/Jetson-Nano-IP67-Fanless-Aluminium-Enclosure IP67 Fanless Aluminum Case] (metal enclosure)
 +
* [https://www.aaeon.com/en/p/edge-ai-box-pc-nvidia-jetson-nano-boxer-8220ai?dl=image AAEON BOXER-8820AI] (enclosure with 5xGbE)
 +
* [https://www.picocluster.com/collections/jeston-nano PicoCluster] (cluster chassis)
  
 
==== Power Supplies ====
 
==== Power Supplies ====
See the [[Jetson_Nano#What_You_Will_Need|Power Supply]] section for more information about selecting proper power adapters.
+
See the [[Jetson_Nano#What_You_Will_Need|Power Supply]] section and this [https://devtalk.nvidia.com/default/topic/1048640/jetson-nano/power-supply-considerations-for-jetson-nano-developer-kit/ forum post] for more information about selecting proper power adapters.
  
* Adafruit [https://www.adafruit.com/product/1995 GEO151UB] (5V⎓2.5A Micro-USB adapter)
+
* Adafruit [https://www.adafruit.com/product/1995 GEO151UB] (5V⎓2.5A MicroUSB adapter)
* Adafruit [https://www.adafruit.com/product/1466 1446] (5V⎓4A DC barrel jack adapter)
+
* Adafruit [https://www.adafruit.com/product/1466 GEO241DA-0540] (5V⎓4A DC barrel jack adapter)
 +
* Geekworm [https://www.amazon.com/dp/B07413Q5Y4 5V⎓4A DC barrel jack adapter]
 +
* GeekPi [https://www.amazon.com/dp/B07CYZ9GZZ ABT025050] (5V⎓2.5A MicroUSB Adapter with ON/OFF Switch)
 +
* Pwr+ [https://www.amazon.com/dp/B00L88M8TE PWR-TA05035N] (5V⎓3.5A MicroUSB AC Adapter)
 +
* Raspberry Pi [https://www.raspberrypi.org/products/raspberry-pi-universal-power-supply/ DSA-13PFC-05 FCA 051250] (5.1V⎓2.5A Universal MicroUSB Power Supply)
  
 
==== Battery Packs ====
 
==== Battery Packs ====
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* Edimax [https://www.edimax.com/edimax/merchandise/merchandise_detail/data/edimax/in/wireless_adapters_n150/ew-7811un/ EW-7811Un] (USB Wi-Fi wireless dongle)
 
* Edimax [https://www.edimax.com/edimax/merchandise/merchandise_detail/data/edimax/in/wireless_adapters_n150/ew-7811un/ EW-7811Un] (USB Wi-Fi wireless dongle)
 
* Intel [https://www.newegg.com/Product/Product.aspx?Item=9SIAH718PH3221 8265NGW] (M.2 Key-E Wi-Fi/BT wireless card)
 
* Intel [https://www.newegg.com/Product/Product.aspx?Item=9SIAH718PH3221 8265NGW] (M.2 Key-E Wi-Fi/BT wireless card)
 +
* Geekworm [https://geekworm.com/products/geekworm-nvidia-jetson-nano-dual-band-wireless-usb-3-0-adapter-5ghz-2-4ghz-1200m Dual Band Wireless USB 3.0 Wi-Fi Adapter] (USB3 Wi-Fi dongle and SMA antenna)
 +
 +
==== Storage ====
 +
* Geekworm [https://www.amazon.com/dp/B07T9FQ293 SATA SSD/HDD Shield] (USB3 SATA shield)
 +
* Geekworm [https://www.amazon.com/dp/B07TYKM7TCSATA NVMe SSD Shield] (USB3 SATA shield)
  
 
==== Other ====
 
==== Other ====
 +
* [https://www.seeedstudio.com/Grove-Base-Hat-for-Raspberry-Pi.html Grove Base Hat for Raspberry Pi] (support Jetson Nano)
 +
* [https://www.seeedstudio.com/Grove-Base-Hat-for-Raspberry-Pi-Zero-p-3187.html Grove Base Hat for Raspberry Pi Zero] (support Jetson Nano)
 +
* [https://auvidea.eu/product/heatsink-for-nvidia-jetson-nano/ Module Heatsink] (available from Auvidea)
 
* [https://www.amazon.com/NGFF-Mini-PCI-Adapter-Cable/dp/B07JFYSNVL M.2 Key-E to Mini-PCIe] (PCIe adapter)
 
* [https://www.amazon.com/NGFF-Mini-PCI-Adapter-Cable/dp/B07JFYSNVL M.2 Key-E to Mini-PCIe] (PCIe adapter)
 +
* [https://www.amazon.com/gp/product/B07DZF1W55 M.2 Key-E to Key-M] (PCIe adapter)
 
* Noctua [https://noctua.at/en/nf-a4x20-5v-pwm NF-A4x20 5V PWM] (optional fan)
 
* Noctua [https://noctua.at/en/nf-a4x20-5v-pwm NF-A4x20 5V PWM] (optional fan)
 +
* [[BeadaPanel#BeadaPanel_for_NVIDIA_Jetson_Dev._Board|BeadaPanel]] USB Display+WiFi+Storage 3-In-1 Companion Kit
 +
* [https://www.iotamy.com/20W-PoE-Module-for-Jetson-Nano 20W PoE Module for Jetson Nano] (5.2V⎓4A PoE)
  
 
See the Jetson Nano '''[https://developer.nvidia.com/embedded/dlc/jetson-nano-supported-components-list Supported Components List]''' for devices that have been qualified by NVIDIA to work with Jetson Nano.
 
See the Jetson Nano '''[https://developer.nvidia.com/embedded/dlc/jetson-nano-supported-components-list Supported Components List]''' for devices that have been qualified by NVIDIA to work with Jetson Nano.

Revision as of 07:06, 25 May 2020

NVIDIA Jetson Nano is an embedded system-on-module (SoM) and developer kit from the NVIDIA Jetson family, including an integrated 128-core Maxwell GPU, quad-core ARM A57 64-bit CPU, 4GB LPDDR4 memory, along with support for MIPI CSI-2 and PCIe Gen2 high-speed I/O.

Useful for deploying computer vision and deep learning, Jetson Nano runs Linux and provides 472 GFLOPS of FP16 compute performance with 5-10W of power consumption.

Jetson Nano is currently available as the Jetson Nano Developer Kit for $99, and the production compute module. See the wiki of the other Jetson's here.

  Technical BlogNVIDIA Jetson Nano Brings AI to Everyone


Jetson Nano Family.png

Jetson Nano Developer Kit

The Jetson Nano Developer Kit is an easy way to get started using Jetson Nano, including the module, carrier board, and software. It costs $99 and is available from distributors worldwide.

Jetson Nano Developer Kit P3449 B01.jpg

What's Included

  • 80x100mm Reference Carrier Board
  • Jetson Nano Module with passive heatsink
  • Pop-Up Stand
  • Getting Started Guide

(the complete devkit with module and heatsink weighs 138 grams)

What You Will Need

Ports & Interfaces

  • 4x USB 3.0 A (Host)
  • USB 2.0 Micro B (Device)
  • MIPI CSI-2 x2 (15-position Camera Flex Connector)
  • HDMI 2.0
  • DisplayPort
  • Gigabit Ethernet (RJ45)
  • M.2 Key-E with PCIe x1
  • MicroSD card slot
  • (3x) I2C, (2x) SPI, UART, I2S, GPIOs

Getting Started

Availability

The devkit is available for $99 from the NVIDIA webstore and global distributors, including:

For the full list, refer to the Region Selector.

Software Support

See the Jetson Zoo for more software packages to install on top of JetPack.

Guides and Tutorials

This section contains recipes for following along on Jetson Nano.

System Tools

Deep Learning

See the Jetson Zoo for more resources on deploying AI and deep learning.

Robotics

Multimedia

V4L2 drivers for cameras

Design FAQs

There are some useful FAQs for Jetson Nano design, link is here.

Ecosystem Products and Sensors

The following are 3rd-party accessories, peripherals, and cameras available for Jetson Nano.

Cameras

Carriers

Enclosures

Power Supplies

See the Power Supply section and this forum post for more information about selecting proper power adapters.

Battery Packs

  • INUI 10000mAh (dual 5V⎓3A Micro-USB)
  • Krisdonia 25000mAh (5V⎓3A Micro-USB / DC barrel jack)

Wireless

Storage

Other

See the Jetson Nano Supported Components List for devices that have been qualified by NVIDIA to work with Jetson Nano.

Getting Help

If you have a technical question or bug report, please visit the Jetson Nano Developer Forum and search or start a new topic.

See the official Support page on Embedded Developer Zone for warranty and RMA information.

For NVIDIA webstore Customer Service, please see the My Account page or contact 1-800-797-6530.