Difference between revisions of "Jetson TX2"

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Useful for deploying computer vision and deep learning, Jetson TX2 runs Linux and provides greater than 1TFLOPS of FP16 compute performance in less than 7.5 watts of power.
 
Useful for deploying computer vision and deep learning, Jetson TX2 runs Linux and provides greater than 1TFLOPS of FP16 compute performance in less than 7.5 watts of power.
  
Jetson TX2 is available as the '''[[#Jetson TX2 Module|module]]''', '''[[#Jetson TX2 Developer Kit|developer kit]]''', and in compatible '''[[#Ecosystem Products|ecosystem]]''' products.  See the wiki of other Jetson's [[Jetson|here]].
+
Jetson TX2 is available as the '''[[#Jetson TX2 Module|module]]''', '''[[#Jetson TX2 Developer Kit|developer kit]]''', and in compatible '''[[#Ecosystem Products|ecosystem]]''' products.  See the wiki of other Jetson's '''[[Jetson|here]]''', including the latest [[Jetson AGX Xavier]].
  
 
{| style="color: black; background-color: #ffffff; width: 600px;"
 
{| style="color: black; background-color: #ffffff; width: 600px;"
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=== Software Support ===
 
=== Software Support ===
<div style="width:50%;column-count:2;-moz-column-count:2;-webkit-column-count:2">
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<div style="width:40%;column-count:2;-moz-column-count:2;-webkit-column-count:2">
* [https://developer.nvidia.com/embedded/jetpack JetPack 3.1]
+
* [https://developer.nvidia.com/embedded/jetpack JetPack 4.2.2]
* [https://developer.nvidia.com/embedded/linux-tegra Linux4Tegra R28.1] (L4T)
+
* [https://developer.nvidia.com/embedded/linux-tegra Linux4Tegra R32.2.1] (L4T)
* Linux kernel 4.4
+
* Linux kernel 4.9
* Ubuntu 16.04 aarch64
+
* Ubuntu 18.04 aarch64
* CUDA Toolkit 8
+
* [https://developer.nvidia.com/cuda-toolkit CUDA Toolkit] 10.0.326
* cuDNN v6.0
+
* [https://developer.nvidia.com/cudnn cuDNN] 7.5.0
* [https://developer.nvidia.com/tensorrt TensorRT] 2.1
+
* [https://developer.nvidia.com/tensorrt TensorRT] 5.1.6
 +
* [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
* OpenCV4Tegra 2.4.13-17
+
* OpenCV 3.3.1
* OpenGL 4.5 / OpenGL ES 3.1
+
* OpenGL 4.6 / OpenGL ES 3.2.5
 +
* Vulkan 1.1.1
 +
* [http://developer.nvidia.com/embedded/dlc/l4t-multimedia-api-reference-32-1 L4T Multimedia API] (Argus 0.97)
 +
* GStreamer 1.14.1
 
* V4L2 media controller support
 
* V4L2 media controller support
* GStreamer 1.8.2
+
* [https://developer.nvidia.com/nsight-systems NVIDIA Nsight Systems] 2019.4
* [https://developer.nvidia.com/tegra-system-profiler Tegra System Profiler] 3.7
+
* [https://developer.nvidia.com/nsight-graphics NVIDIA Nsight Graphics] 2019.2
* [https://developer.nvidia.com/tegra-graphics-debugger Tegra Graphics Debugger] 2.3
+
* [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.
  
 
{| style="color: black; background-color: #ffffff; width: 575px;"
 
{| style="color: black; background-color: #ffffff; width: 575px;"
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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">
 
:* [[Jetson/TX2_Cloning|Cloning & Restore]]
 
:* [[Jetson/TX2_Cloning|Cloning & Restore]]
 +
:* [https://github.com/jtagxhub/jetpack-agx-build Jetson TX2 Build Assistant Scripts]
 
:* [https://developer.nvidia.com/embedded/downloads#?search=Factory%20Image Factory Images]
 
:* [https://developer.nvidia.com/embedded/downloads#?search=Factory%20Image Factory Images]
 
:* [[Jetson/TX2_DTB|Setting the DTB]]
 
:* [[Jetson/TX2_DTB|Setting the DTB]]
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:* [https://medium.com/@ynd/getting-swift-to-run-on-nvidia-jetson-tx2-ai-computing-platform-1d9bcd6559dc Getting Swift to Run on TX2]
 
:* [https://medium.com/@ynd/getting-swift-to-run-on-nvidia-jetson-tx2-ai-computing-platform-1d9bcd6559dc Getting Swift to Run on TX2]
 
:* [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://sites.google.com/site/jetsontricks/ v4l2loopback,rtsp,screencapture,misc]  
 
:* [https://sites.google.com/site/jetsontricks/ v4l2loopback,rtsp,screencapture,misc]  
 +
:* [https://devtalk.nvidia.com/default/topic/1057158/jetson-tx2/guide-to-enabling-mcp251x-mcp2515-on-the-tx2-spi-can-/ Enabling MCP2515 SPI-CAN Device]
 
</div>
 
</div>
  
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:* [http://docs.opencv.org/3.2.0/d6/d15/tutorial_building_tegra_cuda.html Building OpenCV 3.2 with CUDA for Tegra]
 
:* [http://docs.opencv.org/3.2.0/d6/d15/tutorial_building_tegra_cuda.html Building OpenCV 3.2 with CUDA for Tegra]
 
:* [https://developer.nvidia.com/embedded/learn/tutorials#collapseVisionWorks VisionWorks training]
 
:* [https://developer.nvidia.com/embedded/learn/tutorials#collapseVisionWorks VisionWorks training]
:* [https://developer.ridgerun.com/wiki/index.php?title=Gstreamer_pipelines_for_Tegra_X2 gstreamer Pipelines for TX2]
 
:* [http://developer.ridgerun.com/wiki/index.php?title=GstCUDA GstCUDA] (RidgeRun CUDA ZeroCopy for GStreamer)
 
  
 
=== Deep Learning ===
 
=== Deep Learning ===
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:* [http://www.jetsonhacks.com/2017/04/02/tensorflow-on-nvidia-jetson-tx2-development-kit/ TensorFlow] post for JetPack 3.0 {{spaces|1}} (JetsonHacks)
 
:* [http://www.jetsonhacks.com/2017/04/02/tensorflow-on-nvidia-jetson-tx2-development-kit/ TensorFlow] post for JetPack 3.0 {{spaces|1}} (JetsonHacks)
 
:* [https://syed-ahmed.gitbooks.io/nvidia-jetson-tx2-recipes/content/first-question.html TensorFlow] install procedure {{spaces|1}} ([https://devtalk.nvidia.com/default/topic/1000717/jetson-tx2/tensorflow-on-jetson-tx2/post/5112792/#5112792 pip wheel])
 
:* [https://syed-ahmed.gitbooks.io/nvidia-jetson-tx2-recipes/content/first-question.html TensorFlow] install procedure {{spaces|1}} ([https://devtalk.nvidia.com/default/topic/1000717/jetson-tx2/tensorflow-on-jetson-tx2/post/5112792/#5112792 pip wheel])
 +
:* [https://developer.ridgerun.com/wiki/index.php?title=GstInference RidgeRun's GstInference]
 +
:* [https://developer.ridgerun.com/wiki/index.php?title=R2Inference RidgeRun's R2Inference]
 
:* [https://github.com/AastaNV/JEP/tree/master/script/TensorFlow_1.6 TensorFlow] script and pip wheel for JetPack 3.2 DP
 
:* [https://github.com/AastaNV/JEP/tree/master/script/TensorFlow_1.6 TensorFlow] script and pip wheel for JetPack 3.2 DP
 
:* [https://github.com/dusty-nv/jetson-reinforcement/blob/master/CMakePreBuild.sh Torch7]  {{spaces|1}} install script
 
:* [https://github.com/dusty-nv/jetson-reinforcement/blob/master/CMakePreBuild.sh Torch7]  {{spaces|1}} install script
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:* [https://heyjetson.com/ Hey, Jetson!] {{spaces|2}} (Automatic Speech Recognition using CNN/RNN)
 
:* [https://heyjetson.com/ Hey, Jetson!] {{spaces|2}} (Automatic Speech Recognition using CNN/RNN)
 
</div>
 
</div>
 +
 +
=== Multimedia ===
 +
* [https://developer.ridgerun.com/wiki/index.php?title=Xavier/GStreamer_Pipelines Gstreamer Pipelines for AGX Xavier]
 +
* [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)
 +
 
=== Camera Info ===
 
=== Camera Info ===
 
*USB3 - e-con Systems' [https://www.e-consystems.com/4k-usb-camera.asp See3CAM_CU135] was tested on Jetson TX2 with HD (1280X720) @ 46fps  and FullHD (1920x1080) @ 36fps in MJPEG (compressed) format, as well as [https://elinux.org/Jetson/Cameras#USB_3.0_webcams_known_to_be_working other settings].
 
*USB3 - e-con Systems' [https://www.e-consystems.com/4k-usb-camera.asp See3CAM_CU135] was tested on Jetson TX2 with HD (1280X720) @ 46fps  and FullHD (1920x1080) @ 36fps in MJPEG (compressed) format, as well as [https://elinux.org/Jetson/Cameras#USB_3.0_webcams_known_to_be_working other settings].
 
*CSI-2 - [https://www.e-consystems.com/multiple-csi-cameras-for-nvidia-jetson-tx2.asp 6 MIPI CSI-2 Cameras] support for Jetson TX2 from e-con Systems
 
*CSI-2 - [https://www.e-consystems.com/multiple-csi-cameras-for-nvidia-jetson-tx2.asp 6 MIPI CSI-2 Cameras] support for Jetson TX2 from e-con Systems
 
*CSI-2 - [https://www.e-consystems.com/three-synchronized-4k-cameras-for-nvidia-jetson-tx2.asp 3 MIPI CSI-2 Cameras] support for Jetson TX2 from e-con Systems
 
*CSI-2 - [https://www.e-consystems.com/three-synchronized-4k-cameras-for-nvidia-jetson-tx2.asp 3 MIPI CSI-2 Cameras] support for Jetson TX2 from e-con Systems
 +
 +
=== 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 ===
 
=== Design FAQs ===
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<br />
 
<br />
 
<br />
 
<br />
 +
 
= Ecosystem Products =
 
= Ecosystem Products =
  
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:* Auvidea [https://auvidea.com/j150/ J150] OpenGear blade
 
:* Auvidea [https://auvidea.com/j150/ J150] OpenGear blade
 
:* Auvidea [http://www.auvidea.eu/index.php/2015-11-08-08-01-27/2016-02-03-12-30-02/j200-dual-jetson-tx1-carrier J200] carrier
 
:* Auvidea [http://www.auvidea.eu/index.php/2015-11-08-08-01-27/2016-02-03-12-30-02/j200-dual-jetson-tx1-carrier J200] carrier
 +
:* Avermedia [https://www.avermedia.com/professional/product/ex731_aa_n1/overview EX731-AA] carrier
 +
:* Avermedia [https://www.avermedia.com/professional/product/ex713_aa/overview EX713-AA] carrier
 
:* Axiomtek [http://www.axiomtek.com/Default.aspx?MenuId=Products&FunctionId=ProductView&ItemId=24544&upcat=144&C=eBOX560-900-FL#/ eBOX560-900-FL]
 
:* Axiomtek [http://www.axiomtek.com/Default.aspx?MenuId=Products&FunctionId=ProductView&ItemId=24544&upcat=144&C=eBOX560-900-FL#/ eBOX560-900-FL]
 
:* [http://black.ai black.ai] perception platform
 
:* [http://black.ai black.ai] perception platform
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:* DCDZ(冬虫电子) [[Jetson/xcb-lite| XCB-8eyes ]]  4 or 8 cameras ADAS  expansion board
 
:* DCDZ(冬虫电子) [[Jetson/xcb-lite| XCB-8eyes ]]  4 or 8 cameras ADAS  expansion board
 
:* DCDZ(冬虫电子) [[Jetson/xcb-lite| XCB-AUDIO ]]  Sound card expansion board
 
:* DCDZ(冬虫电子) [[Jetson/xcb-lite| XCB-AUDIO ]]  Sound card expansion board
:* e-con Systems [https://www.e-consystems.com/3d-usb-stereo-camera-with-nvidia-accelerated-sdk.asp USB Stereo Camera for Jetson TX2]  
+
:* DCDZ(冬虫电子) [[Jetson/xcb-lite| XCB-DSPK ]]  Digital speaker and MIC expansion board
 +
:* e-con Systems [https://www.e-consystems.com/nvidia-cameras/jetson-agx-xavier-cameras/stereo-camera.asp 3D MIPI Stereo camera for NVIDIA® Jetson AGX Xavier™/TX2]
 +
:* e-con Systems [https://www.e-consystems.com/13mp-autofocus-nvidia-jetson-tx2-camera-board.asp 13MP AR1335 AF MIPI Jetson TX1/TX2 Camera]
 +
:* e-con Systems [https://www.e-consystems.com/3d-usb-stereo-camera-with-nvidia-accelerated-sdk.asp USB Stereo Camera for NVIDIA® Jetson AGX Xavier™/TX2]  
 
:* e-con Systems [https://www.e-consystems.com/2MP-HDR-Jetson-TX2-TX1-Camera-Board.asp 2MP AR0230AT MIPI Jetson TX1/TX2 Camera]  
 
:* e-con Systems [https://www.e-consystems.com/2MP-HDR-Jetson-TX2-TX1-Camera-Board.asp 2MP AR0230AT MIPI Jetson TX1/TX2 Camera]  
 
:* e-con Systems [https://www.e-consystems.com/jetson-tx2-ultra-low-light-camera-board.asp 2MP SONY IMX290 MIPI Jetson TX1/TX2 Camera]
 
:* e-con Systems [https://www.e-consystems.com/jetson-tx2-ultra-low-light-camera-board.asp 2MP SONY IMX290 MIPI Jetson TX1/TX2 Camera]
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:* e-con Systems [https://www.e-consystems.com/gmsl-camera-for-nvidia-jetson-tx2.asp 3.4 MP AR0330 GMSL MIPI Jetson TX1/TX2 Camera]
 
:* e-con Systems [https://www.e-consystems.com/gmsl-camera-for-nvidia-jetson-tx2.asp 3.4 MP AR0330 GMSL MIPI Jetson TX1/TX2 Camera]
 
:* Gumstix [https://store.gumstix.com/aerocore2-for-nvidia-jetson.html Aerocore2] drone carrier
 
:* Gumstix [https://store.gumstix.com/aerocore2-for-nvidia-jetson.html Aerocore2] drone carrier
 +
:* MiiVii [http://www.miivii.com/en/index.html Brain S2] enclosure
 
:* [http://www.phoronix.com/scan.php?page=article&item=silverstone-pt13-mini&num=2 Silverstone PT13] mini-ITX system
 
:* [http://www.phoronix.com/scan.php?page=article&item=silverstone-pt13-mini&num=2 Silverstone PT13] mini-ITX system
 
:* Rebotnix [https://rebotnix.com/product/gustav/ GUSTAV] enclosure
 
:* Rebotnix [https://rebotnix.com/product/gustav/ GUSTAV] enclosure
 +
:* Realtimes [http://www.realtimes.cn/en/product/9001.html RTSO-9001] carrier
 +
:* Realtimes [http://www.realtimes.cn/en/product/RTSO9002.html RTSO-9002] carrier
 +
:* Realtimes [http://www.realtimes.cn/en/product/rtso-9003.html RTSO-9003] carrier
 +
:* Realtimes [http://www.realtimes.cn/en/product/products-8-55.html RTSS-Z5O3U] enclosure
 
:* RidgeRun [https://developer.ridgerun.com/wiki/index.php?title=Tegra_X2_or_TX2 GStreamer and Multimedia Solutions]
 
:* RidgeRun [https://developer.ridgerun.com/wiki/index.php?title=Tegra_X2_or_TX2 GStreamer and Multimedia Solutions]
 
:* SMP Robotics [https://smprobotics.com/technology_autonomous_mobile_robot/video_analytics_security_system/ T9 System] enclosure
 
:* SMP Robotics [https://smprobotics.com/technology_autonomous_mobile_robot/video_analytics_security_system/ T9 System] enclosure
 
:* [https://www.vision4ce.com/wp-content/uploads/2017/09/CHARM-100-170801.pdf Vision4CE CHARM-100] enclosure
 
:* [https://www.vision4ce.com/wp-content/uploads/2017/09/CHARM-100-170801.pdf Vision4CE CHARM-100] enclosure
 +
:* [[BeadaPanel#BeadaPanel_for_NVIDIA_Jetson_Dev._Board|BeadaPanel USB Display+WiFi+Storage 3-In-1 Companion Kit]]
 
</div>
 
</div>
 
<br />
 
<br />

Revision as of 07:27, 19 September 2019

NVIDIA Jetson TX2 is an embedded system-on-module (SoM) with dual-core NVIDIA Denver2 + quad-core ARM Cortex-A57, 8GB 128-bit LPDDR4 and integrated 256-core Pascal GPU.

Useful for deploying computer vision and deep learning, Jetson TX2 runs Linux and provides greater than 1TFLOPS of FP16 compute performance in less than 7.5 watts of power.

Jetson TX2 is available as the module, developer kit, and in compatible ecosystem products. See the wiki of other Jetson's here, including the latest Jetson AGX Xavier.

  Parallel ForAllNVIDIA Jetson TX2 Delivers Twice the Intelligence to the Edge


NVIDIA Jetson TX2 Module Devkit.png

Jetson TX2 Module

The Jetson TX2 module contains all the active processing components. The ports are broken out through a carrier board.

Below is a partial list of the module's features. Please see the Jetson TX2 Module Datasheet for the complete specifications.

Tegra Parker Block Diagram.png

Processing Components

  • dual-core NVIDIA Denver2 + quad-core ARM Cortex-A57
  • 256-core Pascal GPU
  • 8GB LPDDR4, 128-bit interface
  • 32GB eMMC
  • 4kp60 H.264/H.265 encoder & decoder
  • Dual ISPs (Image Signal Processors)
  • 1.4 gigapixel/sec MIPI CSI camera ingest
NVIDIA Jetson TX2 Module TTP.png

Ports & Peripherals

  • HDMI 2.0
  • 802.11a/b/g/n/ac 2×2 867Mbps WiFi
  • Bluetooth 4.1
  • USB3, USB2
  • 10/100/1000 BASE-T Ethernet
  • 12 lanes MIPI CSI 2.0, 2.5 Gb/sec per lane
  • PCIe gen 2.0, 1×4 + 1×1 or 2×1 + 1×2
  • SATA, SDcard
  • dual CAN bus
  • UART, SPI, I2C, I2S, GPIOs

Form-Factor

  • 400-pin Samtec board-to-board connector
  • dimensions: 50x87mm   (1.96" x 3.42")
  • Thermal Transfer Plate (TTP), -25C to 80C operating temperature
  • mass: 85 grams, including TTP
  • 5.5-19.6VDC input power (consuming 7.5W under typical load)

Software Support

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

  Parallel ForAllJetPack 3.1 Doubles Jetson's Low-Latency Inference Performance

Jetson TX2i Module

Jetson TX2i Module and TTP 800px.png

There's an extended-temperature variant of the TX2 module available called Jetson TX2i that's intended for industrial environments. It has the same processing capabilities as TX2, with a rugged design.

For more info, see the FAQ "What changes for industrial environments does Jetson TX2i have compared to Jetson TX2?"


Jetson TX2 Developer Kit

The Jetson TX2 Developer Kit bundles together all the parts to get started, including:

NVIDIA Jetson TX2 Devkit Unbox.png

What's Included

  • mini-ITX Reference carrier board
  • Jetson TX2 Module
    • fan and heatsink (pre-assembled)
  • 5MP CSI camera module (with Omnivision OV5693)
  • WiFi/BT antennas
  • USB OTG adapter
  • 19VDC Power brick
  • AC Power cable

The design files for the reference carrier board and camera module are freely available for download.

Getting Started

Availability


Platform Documentation

NVIDIA has released comprehensive documentation and reference designs for the Jetson TX2 module and devkit.

  • Module Datasheet          the official module features, ports, signal pin-out, and package specifications.
  • Design Guide                  detailed technical design and layout information for creating OEM products.
  • DevKit Carrier Spec        design info about the reference carrier board from the devkit.
  • DevKit Design Files        schematics, layout, and design files for the devkit reference carrier board.
  • DevKit CAD Models        3D STEP file for reference carrier board, heatsink, camera board, and module.
  • Camera Design Files      schematics, layout, and design files for the devkit MIPI CSI-2 camera module.
  • Thermal Design Guide   mechanical specifications for designing active and passive cooling solutions.
  • TX1/TX2 Migration          guide to porting applications and hardware between Jetson TX1 and TX2
  • Battery Charger Guide   document for the design of battery charger
  • Tegra X2 (Parker) TRM   Technical Reference Manual for NVIDIA TX2 system-on-chip and register data.
  • L4T Kernel Docs             documentation for L4T kernel developers (including V4L2/camera drivers).
  • Multimedia API Reference          documentation to Argus camera API and V4L2 media codecs
  • Accelerated GStreamer Guide   example gstreamer pipelines for accessing H.264/H.265 hardware video codec.

Above is a partial list of documents. Please visit the Downloads Center at Embedded Developer Zone for the full list that's currently available.

Guides and Tutorials

This section contains recipes for following along on Jetson.

System Tools

Please see Jetson TX1 Wiki for similar entries that also apply to TX2.

Robotics

Computer Vision

Deep Learning

Multimedia

Camera Info

V4L2 drivers for cameras

Design FAQs

There are some useful FAQs for Jetson TX2 design, link is here.

Ecosystem Products

The following are 3rd-party carriers, enclosures, drones, and accessories available for Jetson TX2.

Please see additional backwards-compatible Ecosystem Products for TX1.


Getting Help

If you have a technical question or bug report, please visit the DevTalk Developer Forums and search or start a topic.

We summarize some useful topics in http://elinux.org/Jetson_TX2/TX2_Issue page.

See the official Support page on Embedded Developer Zone for warranty and RMA information: https://developer.nvidia.com/embedded/support

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