Difference between revisions of "Jetson TX2"

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NVIDIA's [https://developer.nvidia.com/embedded-computing 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.
+
NVIDIA [https://developer.nvidia.com/embedded/buy/jetson-tx2-devkit 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.
 
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 wiki of previous 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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{{spaces|1}} <span style="font-family: Trebuchet MS; color: white;">'''Parallel ForAll''' — </span>''[https://devblogs.nvidia.com/parallelforall/jetpack-doubles-jetson-inference-perf/ <span style="font-family: Trebuchet MS; color:white;">JetPack 3.1 Doubles Jetson's Low-Latency Inference Performance</span>]''
 
{{spaces|1}} <span style="font-family: Trebuchet MS; color: white;">'''Parallel ForAll''' — </span>''[https://devblogs.nvidia.com/parallelforall/jetpack-doubles-jetson-inference-perf/ <span style="font-family: Trebuchet MS; color:white;">JetPack 3.1 Doubles Jetson's Low-Latency Inference Performance</span>]''
 
|}
 
|}
 +
 +
== Jetson TX2i Module ==
 +
 +
[[File:Jetson TX2i Module and TTP 800px.png|600px]]
 +
 +
There's an extended-temperature variant of the TX2 module available called [https://developer.nvidia.com/embedded/buy/jetson-tx2i '''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 [https://developer.nvidia.com/embedded/faq#jetson-differences-tx2i "What changes for industrial environments does Jetson TX2i have compared to Jetson TX2?"]
  
 
<br />
 
<br />
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=== Getting Started ===
 
=== Getting Started ===
* Get the latest development software for PC and TX1 by using '''[https://developer.nvidia.com/embedded/jetpack JetPack]'''.<br />
+
* Get the latest development software for PC and TX2 by using '''[https://developer.nvidia.com/embedded/jetpack JetPack]'''.<br />
 
* Plug in an HDMI display into Jetson, attach the antennas and USB keyboard & mouse, and apply power to boot it up. {{spaces|0}} ('''[http://developer.nvidia.com/embedded/dlc/l4t-quick-start-guide-27-1 User Guide]''')<br />
 
* Plug in an HDMI display into Jetson, attach the antennas and USB keyboard & mouse, and apply power to boot it up. {{spaces|0}} ('''[http://developer.nvidia.com/embedded/dlc/l4t-quick-start-guide-27-1 User Guide]''')<br />
 
* Visit the '''[https://developer.nvidia.com/embedded-computing Embedded Developer Zone]''' and '''[https://devtalk.nvidia.com/default/board/188/jetson-tx2/ Jetson TX2 Developer Forum]''' to access the latest documentation & downloads.
 
* Visit the '''[https://developer.nvidia.com/embedded-computing Embedded Developer Zone]''' and '''[https://devtalk.nvidia.com/default/board/188/jetson-tx2/ Jetson TX2 Developer Forum]''' to access the latest documentation & downloads.
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= Platform Documentation =
 
= Platform Documentation =
  
NVIDIA has [https://developer.nvidia.com/embedded-computing released] comprehensive documentation and reference designs for the Jetson TX1 module and devkit. <br />
+
NVIDIA has [https://developer.nvidia.com/embedded-computing released] comprehensive documentation and reference designs for the Jetson TX2 module and devkit. <br />
  
 
* '''[https://developer.nvidia.com/embedded/dlc/jetson-tx2-module-datasheet Module Datasheet]''' {{spaces|8}} the official module features, ports, signal pin-out, and package specifications.  
 
* '''[https://developer.nvidia.com/embedded/dlc/jetson-tx2-module-datasheet Module Datasheet]''' {{spaces|8}} the official module features, ports, signal pin-out, and package specifications.  
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* '''[http://developer.nvidia.com/embedded/dlc/http://developer.nvidia.com/embedded/dlc/jetson-tx1-tx2-module-battery-and-charger-design-guide Battery Charger Guide]''' {{spaces|1}} document for the design of battery charger
 
* '''[http://developer.nvidia.com/embedded/dlc/http://developer.nvidia.com/embedded/dlc/jetson-tx1-tx2-module-battery-and-charger-design-guide Battery Charger Guide]''' {{spaces|1}} document for the design of battery charger
 
* '''[https://developer.nvidia.com/embedded/dlc/parker-series-trm Tegra X2 (Parker) TRM]''' {{spaces|1}} Technical Reference Manual for NVIDIA TX2 system-on-chip and register data.
 
* '''[https://developer.nvidia.com/embedded/dlc/parker-series-trm Tegra X2 (Parker) TRM]''' {{spaces|1}} Technical Reference Manual for NVIDIA TX2 system-on-chip and register data.
* '''[https://developer.nvidia.com/embedded/dlc/l4t-documentation-28-1 L4T Kernel Docs]''' {{spaces|11}} documentation for L4T kernel developers (including V4L2/camera drivers).
+
* '''[https://developer.nvidia.com/embedded/dlc/l4t-documentation-28-2 L4T Kernel Docs]''' {{spaces|11}} documentation for L4T kernel developers (including V4L2/camera drivers).
* '''[https://developer.nvidia.com/embedded/dlc/l4t-multimedia-api-reference-28-1 Multimedia API Reference]''' {{spaces|8}} documentation to Argus camera API and V4L2 media codecs
+
* '''[https://developer.nvidia.com/embedded/dlc/l4t-multimedia-api-reference-28-2 Multimedia API Reference]''' {{spaces|8}} documentation to Argus camera API and V4L2 media codecs
* '''[https://developer.nvidia.com/embedded/dlc/l4t-accelerated-gstreamer-guide-28-1 Accelerated GStreamer Guide]''' {{spaces|1}} example gstreamer pipelines for accessing H.264/H.265 hardware video codec.
+
* '''[https://developer.nvidia.com/embedded/dlc/l4t-accelerated-gstreamer-guide-28-2 Accelerated GStreamer Guide]''' {{spaces|1}} example gstreamer pipelines for accessing H.264/H.265 hardware video codec.
  
 
Above is a partial list of documents.
 
Above is a partial list of documents.
 
Please visit the '''[https://developer.nvidia.com/embedded/downloads#?tx=$product,jetson_tx2 Downloads Center]''' at Embedded Developer Zone for the full list that's currently available.<br />
 
Please visit the '''[https://developer.nvidia.com/embedded/downloads#?tx=$product,jetson_tx2 Downloads Center]''' at Embedded Developer Zone for the full list that's currently available.<br />
 
+
<br />
=== USB 3.0 webcams known to be working ===
 
 
 
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].
 
  
 
= Guides and Tutorials =
 
= Guides and Tutorials =
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Please see [http://elinux.org/Jetson_TX1#System_Tools Jetson TX1 Wiki] for similar entries that also apply to TX2.
 
Please see [http://elinux.org/Jetson_TX1#System_Tools Jetson TX1 Wiki] for similar entries that also apply to TX2.
  
 +
<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://developer.nvidia.com/embedded/downloads#?search=Factory%20Image Factory Images]
 
:* [https://developer.nvidia.com/embedded/downloads#?search=Factory%20Image Factory Images]
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:* [[Jetson/TX2_eMMC|Maximizing RootFS Partition on eMMC]]
 
:* [[Jetson/TX2_eMMC|Maximizing RootFS Partition on eMMC]]
 
:* [http://www.jetsonhacks.com/2017/03/25/nvpmodel-nvidia-jetson-tx2-development-kit/ nvpmodel] - dynamic performance profiles
 
:* [http://www.jetsonhacks.com/2017/03/25/nvpmodel-nvidia-jetson-tx2-development-kit/ nvpmodel] - dynamic performance profiles
:* [https://gist.github.com/JasonAtNvidia/e03e6675849d1d4049b85ea41efb2171 TX2 GPU support in Docker] - script to enable GPU from within Docker
+
:* [https://gist.github.com/JasonAtNvidia/e03e6675849d1d4049b85ea41efb2171 TX2 GPU support in Docker] - script for GPU from within Docker
 
:* [https://github.com/Technica-Corporation/Tegra-Docker Tegra-Docker]
 
:* [https://github.com/Technica-Corporation/Tegra-Docker Tegra-Docker]
 
:* [[Jetson/TX2|Ubuntu Base]] Minimal footprint (500Mb with OS only) using [https://wiki.ubuntu.com/Base Ubuntu Base]
 
:* [[Jetson/TX2|Ubuntu Base]] Minimal footprint (500Mb with OS only) using [https://wiki.ubuntu.com/Base Ubuntu Base]
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:* [[Jetson TX2/r28 Display debug|Display Driver Debugging]]
 
:* [[Jetson TX2/r28 Display debug|Display Driver Debugging]]
 
:* [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://sites.google.com/site/jetsontricks/ v4l2loopback,rtsp,screencapture,misc]
 +
</div>
  
 
=== Robotics ===
 
=== Robotics ===
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:* [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]
 
:* [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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:* [https://github.com/NVIDIA-Jetson/redtail NVIDIA Redtail] {{spaces|2}} (end-to-end deep learning drone for ROS)
 
:* [https://github.com/NVIDIA-Jetson/redtail NVIDIA Redtail] {{spaces|2}} (end-to-end deep learning drone for ROS)
 
:* Training a Fish Detector with DetectNet {{spaces|1}} [https://jkjung-avt.github.io/fisheries-dataset/ part 1] [https://jkjung-avt.github.io/detectnet-training/ part 2] {{spaces|1}} (jkjung)
 
:* Training a Fish Detector with DetectNet {{spaces|1}} [https://jkjung-avt.github.io/fisheries-dataset/ part 1] [https://jkjung-avt.github.io/detectnet-training/ part 2] {{spaces|1}} (jkjung)
</div><br />
+
:* [https://heyjetson.com/ Hey, Jetson!] {{spaces|2}} (Automatic Speech Recognition using CNN/RNN)
 +
</div>
 +
=== 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].
 +
*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
  
= Multiple Cameras =
+
=== Design FAQs ===
There are several ways to handle multiple cameras on Jetson TX2 at the same time:
 
  
[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
+
There are some useful FAQs for Jetson TX2 design, link is [[Jetson_TX2/FAQ|here]].
 +
<br />
 
<br />
 
<br />
 
= Ecosystem Products =
 
= Ecosystem Products =
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<div style="width:70%;column-count:3;-moz-column-count:3;-webkit-column-count:3">
 
<div style="width:70%;column-count:3;-moz-column-count:3;-webkit-column-count:3">
 +
:* Aaeon [http://www.aaeon.com/en/p/fanless-embedded-computers-boxer-8120ai BOXER-8120AI] enclosure
 
:* Abaco [https://www.abaco.com/products/gvc1000 GVC1000] enclosure
 
:* Abaco [https://www.abaco.com/products/gvc1000 GVC1000] enclosure
 +
:* Aeryon [https://www.aeryon.com/skyranger/r80/ SkyRanger R80] drone
 
:* Aetina [http://www.aetina.com.tw/wp-content/uploads/2017/04/eDM_ACE-N620_carrier/index.html N620] nano-ITX carrier
 
:* Aetina [http://www.aetina.com.tw/wp-content/uploads/2017/04/eDM_ACE-N620_carrier/index.html N620] nano-ITX carrier
 
:* Auvidea [http://auvidea.eu/j20/ J20] 6-camera module
 
:* Auvidea [http://auvidea.eu/j20/ J20] 6-camera module
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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]
 
:* [http://black.ai black.ai] perception platform
 
:* [http://black.ai black.ai] perception platform
 +
:* [https://www.bluetechnix.com/en/products/multi-tof-platform/product/multi-tof-platform/ Bluetechnix Multi-ToF platform]
 
:* ConnectTech [http://www.connecttech.com/sub/Products/ASG008.asp?l1=GPU&l2=ASG008 Sprocket] carrier
 
:* ConnectTech [http://www.connecttech.com/sub/Products/ASG008.asp?l1=GPU&l2=ASG008 Sprocket] carrier
 
:* ConnectTech [http://www.connecttech.com/sub/Products/ASG003.asp?l1=GPU&l2=ASG003 Orbitty] carrier
 
:* ConnectTech [http://www.connecttech.com/sub/Products/ASG003.asp?l1=GPU&l2=ASG003 Orbitty] carrier
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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
:* RidgeRun [https://developer.ridgerun.com/wiki/index.php?title=Tegra_X2_or_TX2 GStreamer and Multimedia Solutions]  
+
:* 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/jetson-tx2-ultra-low-light-camera-board.asp 2MP SONY IMX290 MIPI Jetson TX2 Camera]
+
:* 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/13mp-nvidia-jetson-tx2-camera-board.asp 13MP AR1335 MIPI Jetson TX2 Camera]
+
:* e-con Systems [https://www.e-consystems.com/3d-usb-stereo-camera-with-nvidia-accelerated-sdk.asp USB Stereo Camera for Jetson TX2]
:* e-con Systems [https://www.e-consystems.com/autofocus-liquid-lens-nvidia-jetson-tx2-camera.asp 3.4 MP AF AR0330 MIPI Jetson 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/13mp-nvidia-jetson-tx1-camera-board.asp 13MP AR1820 MIPI Jetson TX1 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/3MP-Jetson-TX1-Camera-board.asp 3.4 MP AR0330 MIPI Jetson TX1 Camera]
+
:* e-con Systems [https://www.e-consystems.com/13mp-nvidia-jetson-tx2-camera-board.asp 13MP AR1335 MIPI Jetson TX1/TX2 Camera]
 +
:* e-con Systems [https://www.e-consystems.com/autofocus-liquid-lens-nvidia-jetson-tx2-camera.asp 3.4 MP AF AR0330 MIPI Jetson TX1/TX2 Camera]
 +
:* e-con Systems [https://www.e-consystems.com/13mp-nvidia-jetson-tx1-camera-board.asp 13MP AR1820 MIPI Jetson TX1/TX2 Camera]
 +
:* e-con Systems [https://www.e-consystems.com/3MP-Jetson-TX1-Camera-board.asp 3.4 MP AR0330 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
 +
:* 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
 +
:* 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
 
:* [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
 
</div>
 
</div>

Revision as of 05:10, 20 March 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

  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

Camera Info

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.