Tegra

Tegra is a system on a chip (SoC) series developed by Nvidia for mobile devices such as smartphones, personal digital assistants, and mobile Internet devices. The Tegra integrates an ARM architecture central processing unit (CPU), graphics processing unit (GPU), northbridge, southbridge, and memory controller onto one package. Early Tegra SoCs are designed as efficient multimedia processors. The Tegra-line evolved to emphasize performance for gaming and machine learning applications without sacrificing power efficiency, before taking a drastic shift in direction towards platforms that provide vehicular automation with the applied Nvidia Drive brand name on reference boards and its semiconductors; and with the Nvidia Jetson brand name for boards adequate for AI applications (e.g. within robots or drones) and for various smart high-level automation purposes.

## Contents

* 1 History
* 2 Models
* 2.1 Tegra APX
* 2.2 Tegra 6xx
* 2.3 Tegra 2
* 2.3.1 Devices
* 2.4 Tegra 3
* 2.4.1 Devices
* 2.5 Tegra 4
* 2.5.1 Devices
* 2.5.2 Tegra 4i
* 2.5.2.1 Devices
* 2.6 Tegra K1
* 2.6.1 Devices
* 2.7 Tegra X1
* 2.7.1 Devices
* 2.8 Tegra X2
* 2.8.1 Devices
* 2.9 Xavier
* 2.9.1 Devices
* 2.10 Orin
* 2.10.1 Devices
* 2.11 Grace
* 2.12 Atlan
* 2.13 Thor
* 2.13.1 Devices
* 3 Comparison
* 4 Software support
* 4.1 FreeBSD
* 4.2 Linux
* 4.3 QNX
* 5 Similar platforms
* 6 See also
* 7 References
* 8 External links

## History

The Tegra APX 2500 was announced on February 12, 2008. The Tegra 6xx product line was revealed on June 2, 2008,[1] and the APX 2600 was announced in February 2009. The APX chips were designed for smartphones, while the Tegra 600 and 650 chips were intended for smartbooks and mobile Internet devices (MID).[2]

The first product to use the Tegra was Microsoft's Zune HD media player in September 2009, followed by the Samsung M1.[3] Microsoft's Kin was the first cellular phone to use the Tegra;[4] however, the phone did not have an app store, so the Tegra's power did not provide much advantage. In September 2008, Nvidia and Opera Software announced that they would produce a version of the Opera 9.5 browser optimized for the Tegra on Windows Mobile and Windows CE.[5][6] At Mobile World Congress 2009, Nvidia introduced its port of Google's Android to the Tegra.

On January 7, 2010, Nvidia officially announced and demonstrated its next generation Tegra system-on-a-chip, the Nvidia Tegra 250, at Consumer Electronics Show 2010.[7] Nvidia primarily supports Android on Tegra 2, but booting other ARM-supporting operating systems is possible on devices where the bootloader is accessible. Tegra 2 support for the Ubuntu Linux distribution was also announced on the Nvidia developer forum.[8]

Nvidia announced the first quad-core SoC at the February 2011 Mobile World Congress event in Barcelona. Though the chip was codenamed Kal-El, it is now branded as Tegra 3. Early benchmark results show impressive gains over Tegra 2,[9][10] and the chip was used in many of the tablets released in the second half of 2011.

In January 2012, Nvidia announced that Audi had selected the Tegra 3 processor for its In-Vehicle Infotainment systems and digital instruments display.[11] The processor will be integrated into Audi's entire line of vehicles worldwide, beginning in 2013. The process is ISO 26262-certified.[12]

In summer of 2012 Tesla Motors began shipping the Model S electric sedan, which contains two NVIDIA Tegra 3D Visual Computing Modules (VCM). One VCM powers the 17-inch touchscreen infotainment system, and one drives the 12.3-inch all digital instrument cluster."[13]

In March 2015, Nvidia announced the Tegra X1, the first SoC to have a graphics performance of 1 teraflop. At the announcement event, Nvidia showed off Epic Games' Unreal Engine 4 "Elemental" demo, running on a Tegra X1.

On October 20, 2016, Nvidia announced that the Nintendo Switch hybrid video game console will be powered by Tegra hardware.[14] On March 15, 2017, TechInsights revealed the Nintendo Switch is powered by a custom Tegra X1 (model T210), with lower clockspeeds.[15]

## Models

### Tegra APX

Tegra APX 2500

* Processor: ARM11 600 MHz MPCore (originally GeForce ULV)
* Suffix: APX (formerly CSX)
* Memory: NOR or NAND flash, Mobile DDR
* Graphics: Image processor (FWVGA 854×480 pixels)
* Up to 12 megapixels camera support
* LCD controller supports resolutions up to 1280×1024
* Storage: IDE for SSD
* Video codecs: up to 720p MPEG-4 AVC/H.264 and VC-1 decoding
* Includes GeForce ULV support for OpenGL ES 2.0, Direct3D Mobile, and programmable shaders
* Output: HDMI, VGA, composite video, S-Video, stereo jack, USB
* USB On-The-Go

Tegra APX 2600

* Enhanced NAND flash
* Video codecs:[16]
* 720p H.264 Baseline Profile encode or decode
* 720p VC-1/WMV9 Advanced Profile decode
* D-1 MPEG-4 Simple Profile encode or decode

### Tegra 6xx

Tegra 600

* Targeted for GPS segment and automotive
* Processor: ARM11 700 MHz MPCore
* Memory: low-power DDR (DDR-333, 166 MHz)
* SXGA, HDMI, USB, stereo jack
* HD camera 720p

Tegra 650

* Targeted for GTX of handheld and notebook
* Processor: ARM11 800 MHz MPCore
* Low power DDR (DDR-400, 200 MHz)
* Less than 1 watt envelope
* HD image processing for advanced digital still camera and HD camcorder functions
* Display supports 1080p at 24 frame/s, HDMI v1.3, WSXGA+ LCD and CRT, and NTSC/PAL TV output
* Direct support for Wi-Fi, disk drives, keyboard, mouse, and other peripherals
* A complete board support package (BSP) to enable fast time to market for Windows Mobile-based designs

### Tegra 2

Nvidia Tegra 2 T20

The second generation Tegra SoC has a dual-core ARM Cortex-A9 CPU, an ultra low power (ULP) GeForce GPU,[17] a 32-bit memory controller with either LPDDR2-600 or DDR2-667 memory, a 32 KB/32 KB L1 cache per core and a shared 1 MB L2 cache.[18] Tegra 2's Cortex A9 implementation does not include ARM's SIMD extension, NEON. There is a version of the Tegra 2 SoC supporting 3D displays; this SoC uses a higher clocked CPU and GPU.

The Tegra 2 video decoder is largely unchanged from the original Tegra and has limited support for HD formats.[19] The lack of support for high-profile H.264 is particularly troublesome when using online video streaming services.

Common features:

* CPU cache: L1: 32 KB instruction + 32 KB data, L2: 1 MB
* 40 nm semiconductor technology

Model
number  | CPU | GPU | Memory  | Adoption

|
|
|
|

Processor  | Cores  | Frequency  | Micro-
architecture  | Core config1 | Frequency  | Type  | Amount  | Bus
width  | Band-
width  | Availability
AP20H
(Ventana/
Unknown) | Cortex-A9 | 2 | 1.0 GHz  | LPDDR2
300 MHz
DDR2
333 MHz | ? | 32 bit
single-
channel | 2.4 GB/s
2.7 GB/s  | Q1 2010
T20
(Harmony/
Ventana) | 333 MHz
AP25  | 1.2 GHz  | 400 MHz  | Q1 2011
T25

1 Pixel shaders : Vertex shaders : Texture mapping units : Render output units

#### Devices

File:Nvidia Tegra 2 T20 Die Shot.jpgNvidia Tegra 2 T20 die shot Model  | Devices

|

AP20H  | Motorola Atrix 4G, Motorola Droid X2, Motorola Photon, LG Optimus 2X / LG Optimus Dual P990 / Optimus 2x SU660 (?), Samsung Galaxy R, Samsung Captivate Glide, T-Mobile G2X P999, Acer Iconia Tab A200 and A500, LG Optimus Pad, Motorola Xoom,[20] Sony Tablet S, Dell Streak Pro,[21] Toshiba Thrive[22] tablet, T-Mobile G-Slate
AP215
T20  | Avionic Design Tamonten Processor Board,[23] Notion Ink Adam tablet, Olivetti OliPad 100, ViewSonic G Tablet, ASUS Eee Pad Transformer, Samsung Galaxy Tab 10.1, Toshiba AC100, CompuLab Trim-Slice nettop, Velocity Micro Cruz Tablet L510, Acer Iconia Tab A100
Unknown  | Tesla Motors Model S 2012~2017 and Model X 2015~2017 instrument cluster (IC)[24][25]

### Tegra 3

File:Nexus 7 (2012) - board - Nvidia T30L-P-A3-4854.jpgNvidia Tegra 3 T30L

NVIDIA's Tegra 3 (codenamed "Kal-El")[26] is functionally a SoC with a quad-core ARM Cortex-A9 MPCore CPU, but includes a fifth "companion" core in what Nvidia refers to as a "variable SMP architecture".[27] While all cores are Cortex-A9s, the companion core is manufactured with a low-power silicon process. This core operates transparently to applications and is used to reduce power consumption when processing load is minimal. The main quad-core portion of the CPU powers off in these situations.

Tegra 3 is the first Tegra release to support ARM's SIMD extension, NEON.

The GPU in Tegra 3 is an evolution of the Tegra 2 GPU, with 4 additional pixel shader units and higher clock frequency. It can also output video up to 2560×1600 resolution and supports 1080p MPEG-4 AVC/h.264 40 Mbit/s High-Profile, VC1-AP, and simpler forms of MPEG-4 such as DivX and Xvid.[28]

The Tegra 3 was released on November 9, 2011.[29]

Common features:

* CPU cache: L1: 32 KB instruction + 32 KB data, L2: 1 MB
* 40 nm LPG semiconductor technology by TSMC

Model
number  | CPU | GPU | Memory  | Adoption

|
|
|
|

Processor  | Cores  | Frequency
(multi-/single-
core mode)  | Micro-
architecture  | Core
config1 | Frequency  | Type  | Amount  | Bus
width  | Band-
width  | Availability
T30L  | Cortex-A9 | 4+1 | 1.2 GHz /
up to
1.3 GHz  | VLIW-based
VEC4 units
[30] | 8:4:8:8
[31] | 416 MHz  | DDR3-1333 | ? | 32 bit
single-
channel | 5.3 GB/s[32] | Q1 2012
T30  | 1.4 GHz /
up to
1.5 GHz  | 520 MHz  | LPDDR2-1066
DDR3-L-1500 | ? | 4.3 GB/s
6.0 GB/s[33] | Q4 2011
AP33
T33  | 1.6 GHz /
up to
1.7 GHz[32] | DDR3-1600 | ? | 6.4 GB/s[32] | Q2 2012

1 Pixel shaders : Vertex shaders : Texture mapping units : Render output units

#### Devices

The Ouya uses a Tegra 3 T33-P-A3. Model  | Devices

|

AP33  | LG Optimus 4X HD, HTC One X, XOLO Play T1000,[34] Coolpad 8735
T30  | Asus Eee Pad Transformer Prime (TF201),[35] IdeaTab K2 / LePad K2,[36] Acer Iconia Tab A510, Fuhu Inc. nabi 2 Tablet,[37] Microsoft Surface RT,[38] Lenovo IdeaPad Yoga 11,[39][40]
T30I  | Tesla Model S 2012~2017 and Model X 2015~2017 media control unit (MCU)[25][41]
T30L  | Asus Transformer Pad TF300T, Microsoft Surface, Nexus 7 (2012),[42] Sony Xperia Tablet S, Acer Iconia Tab A210, Toshiba AT300 (Excite 10),[43] BLU Quattro 4.5,[44] Coolpad 9070
T33  | Asus Transformer Pad Infinity (TF700T), Fujitsu ARROWS X F-02E, HTC One X+, Ouya (T33-P-A3)

### Tegra 4

The Tegra 4 (codenamed "Wayne") was announced on January 6, 2013, and is a SoC with a quad-core CPU, but includes a fifth low-power Cortex A15 companion core which is invisible to the OS and performs background tasks to save power. This power-saving configuration is referred to as "variable SMP architecture" and operates like the similar configuration in Tegra 3.[45]

The GeForce GPU in Tegra 4 is again an evolution of its predecessors. However, numerous feature additions and efficiency improvements were implemented. The number of processing resources was dramatically increased, and clock rate increased as well. In 3D tests, the Tegra 4 GPU is typically several times faster than that of Tegra 3.[46] Additionally, the Tegra 4 video processor has full support for hardware decoding and encoding of WebM video (up to 1080p 60 Mbit/s @ 60fps).[47]

Along with Tegra 4, Nvidia also introduced i500, an optional software modem based on Nvidia's acquisition of Icera, which can be reprogrammed to support new network standards. It supports category 3 (100 Mbit/s) LTE but will later be updated to Category 4 (150 Mbit/s).

Common features:

* CPU cache: L1: 32 KB instruction + 32 KB data, L2: 2 MB
* 28 nm HPL semiconductor technology

Model
number  | CPU | GPU | Memory  | Adoption

|
|
|
|

Processor
(Cores/Freq)  | Micro-
architecture  | Core config1 | Frequency  | Type  | Amount  | Bus
width  | Band-
width  | Availability
T114[48] | 4+1 x 1.9 GHz
Cortex-A15  | VLIW-based
VEC4 units[49] | 72[30][49]
(48:24:4)  | 672 MHz[50] | DDR3L or
LPDDR3 | ? | 32-bit
dual-
channel | up to
14.9 GB/s
(1866 MT/s
data rate)[51][52] | Q2 2013[53]

1 Pixel shaders : Vertex shaders : Pixel pipelines (pairs 1x TMU and 1x ROP)

#### Devices

Model  | Devices

|

T114  | Nvidia Shield Portable, Tegra Note 7, Microsoft Surface 2, HP Slate 7 Extreme,[54] HP Slate 7 Beats Special Edition,[55] HP Slate 8 Pro,[56] HP SlateBook x2,[57] HP SlateBook 14,[58] HP Slate 21,[59] ZTE N988S, nabi Big Tab, Nuvola NP-1, Project Mojo, Asus Transformer Pad TF701T, Toshiba AT10-LE-A (Excite Pro), Vizio 10" tablet, Wexler.Terra 7, Wexler.Terra 10, Acer TA272HUL AIO, Xiaomi Mi 3 (TD-LTE version),[60] Coolpad 8970L (大观 4),[61] Audi Tablet,[62] Le Pan TC1020 10.1",[63] Matrimax iPLAY 7,[64] Kobo Arc 10HD[65]

#### Tegra 4i

The Tegra 4i (codenamed "Grey") was announced on February 19, 2013. With hardware support for the same audio and video formats,[47] but using Cortex-A9 cores instead of Cortex-A15, the Tegra 4i is a low-power variant of the Tegra 4 and is designed for phones and tablets. Unlike its Tegra 4 counterpart, the Tegra 4i also integrates the Icera i500 LTE/HSPA+ baseband processor onto the same die.

Common features:

* 28 nm HPM semiconductor technology
* CPU cache: L1: 32 KB instruction + 32 KB data, L2: 1 MB

Model
number  | CPU | GPU | Memory  | Adoption

|
|
|
|

Processor
(Cores/Freq)  | Micro-
architecture  | Core config1 | Frequency  | Type  | Amount  | Bus
width  | Band-
width  | Availability
T148?[66] | 4+1 x 2.0 GHz
Cortex-A9 "R4"  | VLIW-based
VEC4 units[49] | 60[49]
(48:12:2)  | 660 MHz[50] | LPDDR3 |  | 32-bit
single-
channel | 6.4–7.5 GB/s
(800–933 MHz)[52] | Q1 2014

1 Pixel shaders : Vertex shaders : Pixel pipelines (pairs 1x TMU and 1x ROP)

##### Devices

Model  | Devices

|

T148?  | Blackphone, LG G2 mini LTE, Wiko Highway 4G,[67] Explay 4Game,[68] Wiko Wax[69][70] QMobile Noir LT-250[71]

### Tegra K1

Nvidia's Tegra K1 (codenamed "Logan") features ARM Cortex-A15 cores in a 4+1 configuration similar to Tegra 4, or Nvidia's 64-bit Project Denver dual-core processor as well as a Kepler graphics processing unit with support for Direct3D 12, OpenGL ES 3.1, CUDA 6.5, OpenGL 4.4/OpenGL 4.5, and Vulkan.[72][73] Nvidia claims that it outperforms both the Xbox 360 and the PS3, whilst consuming significantly less power.[74]

Support Adaptive Scalable Texture Compression.[75]

In late April 2014, Nvidia shipped the "Jetson TK1" development board containing a Tegra K1 SoC and running Ubuntu Linux.[76]

* Processor:
* 32-bit variant quad-core ARM Cortex-A15 MPCore R3 + low power companion core
* or 64-bit variant with dual-core Project Denver[77] (variant once codenamed "Stark"[78])
* GPU consisting of 192 ALUs using Kepler technology
* 28 nm HPM process
* Released in Q2 2014
* Power consumption: 8 watts[74]

Model number  | CPU | GPU | Memory  | Adoption

|
|
|
|

Processor
(Cores/Freq)  | Micro-
architecture  | Core
config1 | Frequency  | GFLOPS
(FP32)  | Type  | Amount  | Bus
width  | Band-
width  | Availability
T124[79][80] | 4+1 x 2.3 GHz
Cortex-A15 R3
(32-bit)  | GK20A
(Kepler)  | 192:8:4  | 756–951 MHz  | 290–365  | DDR3L,
LPDDR3  | max 8 GB
(with 40-bit
address
extension2) | 64 bit  | 17 GB/s  | Q2 2014
T132[81][82] | 2x 2.5GHz
Denver
(64-bit)  | max 8 GB  | ?  | ?  | Q3 2014

1 Unified Shaders : Texture mapping units : Render output units
2 ARM Large Physical Page Extension (LPAE) supports 1 TiB (240 bytes).
The 8 GiB limitation is part-specific.

#### Devices

Model  | Devices

|

T124  | Jetson TK1 development board,[83] Nvidia Shield Tablet,[84] Acer Chromebook 13,[85] HP Chromebook 14 G3,[86]
Xiaomi MiPad,[87] Snail Games OBox, UTStarcom MC8718, Google Project Tango tablet,[88] Fuze Tomahawk F1,[89]
Apalis TK1 System on Module,[90] JXD Singularity S192[91]
T132  | HTC Nexus 9[92][93]

In December 2015, the web page of wccftech.com published an article stating that Tesla is going to use a Tegra K1 based design derived from the template of the Nvidia Visual Computing Module (VCM) for driving the infotainment systems and providing visual driving aid in the respective vehicle models of that time.[94] This news has, as of now, found no similar successor or other clear confirmation later on in any other place on such a combination of a multimedia with an auto pilot system for these vehicle models.

### Tegra X1

Tegra X1 in Nvidia Shield TV Die shot of the Tegra X1

Released in 2015, Nvidia's Tegra X1 (codenamed "Erista") features two CPU clusters, one with four ARM Cortex-A57 cores and the other with four ARM Cortex-A53 cores, as well as a Maxwell-based graphics processing unit.[95][96] It supports Adaptive Scalable Texture Compression.[75] Only one cluster of cores can be active at once, with the cluster switch being handled by software on the BPMP-L. Devices utilizing the Tegra X1 have only been seen to utilize the cluster with the more powerful ARM Cortex-A57 cores. The other cluster with four ARM Cortex-A53 cores cannot be accessed without first powering down the Cortex-A57 cores (both clusters must be in the CC6 off state).[97] Nvidia has removed the ARM Cortex-A53 cores from later versions of technical documentation, implying that they have been removed from the die.[98][99] The Tegra X1 was found to be vulnerable to a Fault Injection (FI) voltage glitching attack, which allowed for arbitrary code execution and homebrew software on the devices it was implemented in.[100]

A revision (codenamed "Mariko") with greater power efficiency, named officially as Tegra X1+ was released in 2019,[101] fixing the Fusée Gelée (meaning: Frozen Rocket)[102][103] exploit as reported by Katherine Temkin (founder of Insomnia Security, an advocate for secure hardware)[104]. That revision is also known as model numbers T214 and T210B01.

* CPU: ARMv8 ARM Cortex-A57 quad-core (64-bit) + (unused?) ARM Cortex-A53 quad-core (64-bit)
* GPU: Maxwell-based 256 core GPU (Jetson Nano: only 128 cores)
* MPEG-4 HEVC VP8 encoding/decoding & VP9 decoding support[105] (Jetson Nano: encoders are H.265, H.264/Stereo, VP8, JPEG; decoders are H.265, H.264/Stereo, VP8, VP9, VC-1, MPEG-2, JPEG)
* TSMC 20 nm process for the Tegra X1
* TSMC 16 nm process for the Tegra X1+.
* TDP:
* T210: 15 W,[106] with average power consumption less than 10 W[105]
* Jetson Nano: 10 W (mode 0);[107] mode 1: 5W (only 2 CPU cores @ 918 MHz, GPU @ 640 MHz)

Model
number  | SoC / Variant  | Process  | CPU | GPU | Memory  | Adoption

|
|
|
|
|
|

Processor
(Cores/Freq1)  | Micro-
architecture  | Frequency
(Core config2)  | GFLOPS
(FP32)  | GFLOPS
(FP16)  | Type  | Amount3 | Bus
width  | Band-
width4 | Availability
T210  | ODNX02-A2
TM670D-A1
TM670M-A2
TM671D-A2  | TSMC
20 nm  | 4x 2.2 GHz[108]
Cortex-A57 +
4x 1.3 GHz
Cortex-A53 | GM20B
(Maxwell)
[109]: 14 | 1000 MHz
(256:16:16)
[109]: 753 | 512  | 1024  | LPDDR3
LPDDR4  | 8 GB  | 64 bit  | 25.6
GB/s  | Q2 2015
TM660M-A2  | 4x 1.4 GHz
Cortex-A57 +
4x 1.0 GHz
Cortex-A53 | 921 MHz
(128:16:16)
: 773 | 236  | 472  | LPDDR3?
LPDDR4  | 4 GB  | March 2019
T214 /
T210b01  | ODNX10-A1
TM675M-A1  | TSMC 16 nm  | 4x 2.1 GHz[110]
Cortex-A57 | GM21B (Maxwell)
[111] | 1267 MHz
(256:16:16)
[112] | 649  | 1298  | LPDDR4
LPDDR4X  | 8 GB  | 34.1
GB/s  | Q2 2019

1 CPU frequency may be clocked differently than the maximum validated by Nvidia at the OEM's discretion
2 Unified Shaders : Texture mapping units : Render output units
3 Maximum validated amount of memory, implementation is board specific
4 Maximum validated memory bandwidth, implementation is board specific

#### Devices

The X1 is the basis for the Nintendo Switch video game console. Model  | SoC / Variant  | Devices

|
|

T210  | ODNX02-A2  | Nintendo Switch (2017, HAC-001)[113][15]
TM670D-A1  | Nvidia Shield Android TV (2015)
TM670M-A2  | Nvidia Shield Android TV (2017)
TM660M-A2  | Jetson Nano 4 GB, Jetson Nano 2 GB
TM671D-A2  | Google Pixel C
TM670D-A2  | Nvidia Jetson TX1 development board,[114] Nvidia Drive CX & PX
T210b01  | ODNX10-A1  | Nintendo Switch (2019, HAC-001(-01)), Nintendo Switch Lite (HDH-001),
Nintendo Switch: OLED Model (HEG-001)
TM675M-A1  | Nvidia Shield Android TV (2019)

### Tegra X2

Nvidia's Tegra X2[115][116] (codenamed "Parker") features Nvidia's own custom general-purpose ARMv8-compatible core Denver 2 as well as code-named Pascal graphics processing core with GPGPU support.[117] The chips are made using FinFET process technology using TSMC's 16 nm FinFET+ manufacturing process.[118][119][120]

* CPU: Nvidia Denver2 ARMv8 (64-bit) dual-core + ARMv8 ARM Cortex-A57 quad-core (64-bit)
* RAM: up to 8 GB LPDDR4[121]
* GPU: Pascal-based, 256 CUDA cores; type: GP10B[122]
* TSMC 16 nm, FinFET process
* TDP: 7.5–15 W[123]

Model
number  | SoC
Variant  | CPU | GPU | Memory  | Adoption

|
|
|
|
|

Processor
(Cores / Freq)  | Micro-
architecture  | Frequency
(Core config1)  | GFLOPS
(FP32)  | GFLOPS
(FP16)  | Type  | Amount  | Bus
width  | Band-
width  | Availability
T186  | Tegra X2
(Parker)  | 2x 1.4–2.0 GHz
Denver2 +
4x 1.2–2.0 GHz
Cortex-A57 | GP10B
(Pascal)
[124] | 854–1465 MHz
256:16:16
(2)[125] | 437–
750  | 874–
1500  | LPDDR4  | 8 GB  | 128 bit  | 59.7 GB/s  |

1 Unified Shaders : Texture mapping units : Render output units (SM count)

#### Devices

Model  | Devices

|

T186  | Nvidia Drive PX2 (variants),
ZF ProAI 1.1[126]
T186  | Nvidia Jetson TX2[123]
Unknown  | Mercedes-Benz MBUX (infotainment system)[127]
Unknown  | 1 unit along with 1 GPU semiconductor is part of the ECU for "Tesla vision"
functionality in all Tesla vehicles since October 2016[128][129]
T186  | Magic Leap One[130][131] (mixed environment glasses)
Unknown  | Skydio 2 (drone)[132]

### Xavier

The Xavier Tegra SoC, named after the comic book character Professor X, was announced on 28 September 2016, and by March 2019, it had been released.[133] It contains 7 billion transistors and 8 custom ARMv8 cores, a Volta GPU with 512 CUDA cores, an open sourced TPU (Tensor Processing Unit) called DLA (Deep Learning Accelerator).[134][135] It is able to encode and decode 8K Ultra HD (7680×4320). Users can configure operating modes at 10 W, 15 W, and 30 W TDP as needed and the die size is 350 mm2.[136][137][138] Nvidia confirmed the fabrication process to be 12 nm FinFET at CES 2018.[139]

* CPU: Nvidia custom Carmel ARMv8.2-A (64-bit), 8 cores 10-wide superscalar[140]
* GPU: Volta-based, 512 CUDA cores with 1.4 TFLOPS;[141] type: GV11B[142][122]
* TSMC 12 nm, FinFET process[139]
* 20 TOPS DL and 160 SPECint @ 20 W;[136] 30 TOPS DL @ 30 W[138] (TOPS DL = Deep Learning Tera-Ops)
* 20 TOPS DL via the GPU based tensor cores
* 10 TOPS DL (INT8) via the DLA unit that shall achieve 5 TFLOPS (FP16)[141]
* 1.6 TOPS in the PVA unit (Programmable Vision Accelerator,[143] for StereoDisparity/OpticalFlow/ImageProcessing)
* 1.5 GPix/s in the ISP unit (Image Signal Processor, with native full-range HDR and tile processing support)
* Video processor for 1.2 GPix/s encoding and 1.8 GPix/s decode[141] including 8k video support[137]
* MIPI-CSI-3 with 16 lanes[144][145]
* 1 Gbit/s Ethernet
* 10 Gbit/s Ethernet

Module
(Model)  | SoC Variant  | CPU | GPU | Deep
Learning  | Memory  | Adoption  | TDP
(W)

|
|
|
|
|
|
|

Processor
(Cores/Freq)  | Micro-
architecture  | Frequency
(Core config1)  | TFLOPS
(FP32)  | TFLOPS
(FP16)  | TOPS
(INT8)  | Type  | Amount  | Bus
width  | Band-
width  | Availability
Xavier AGX  | 64 GB  | Carmel
(12 MB cache)
8x 2.2 GHz  | GV11B
(Volta)  | 1377 MHz
512:64
(8, 4, 1)  | 1.41  | 2.82  | 32  | LPDDR4X  | 64 GB  | 256-bit  | 136.5 GB/s  |  | 10-30
Xavier AGX  | 32 GB  | 32 GB  |
Xavier AGX  | Industrial  | Carmel
(12 MB cache)
8x 2.0 GHz  | 1221 MHz
512:64
(8, 4, 1)  | 1.24  | 2.48  | 30  | LPDDR4X  | 32 GB  | 256-bit  | 136.5 GB/s  |  | 20-40
Xavier NX  | 16 GB  | Carmel
(10 MB cache)
6x 1.9 GHz  | Volta | 1100 MHz
384:48
(6, 3, 1)  | 0.84  | 1.69  | 21  | LPDDR4X  | 16 GB  | 128-bit  | 59.7 GB/s  |  | 10-20
Xavier NX  | 8 GB  | 8 GB  |

1 CUDA cores : Tensor cores (SMs, TPCs, GPCs)

#### Devices

Model  | SoC Variant  | Devices

|
|

T194  | Unknown  | Nvidia Drive Xavier (Drive PX-series)[146]
(formerly named Xavier AI Car Supercomputer)
Unknown  | Nvidia Drive Pegasus (Drive PX-series)[146]
Unknown  | Nvidia Drive AGX Xavier Developer Kit[147]
Unknown  | Nvidia Jetson AGX Xavier Developer Kit[148]
Unknown  | Nvidia Jetson Xavier[148]
TE860M-A2  | Nvidia Jetson Xavier NX[149]
Unknown  | \-  | Unknown  | Bosch and Nvidia designed Self Driving System[152]
Unknown  | ZF ProAI[153][154]

On the Linux Kernel Mailing List, a Tegra194 based development board with type ID "P2972-0000" got reported:

The board consists of the P2888 compute module and the P2822 baseboard.[155]

### Orin

Nvidia announced the next-gen SoC codename Orin on March 27, 2018, at GPU Technology Conference 2018.[156]

It contains 17 billion transistors and 12 ARM Hercules cores and is capable of 200 INT8 TOPs @ 65W.[157]
The Drive AGX Orin board system family was announced on December 18, 2019, at GTC China 2019.

Nvidia has sent papers to the press documenting that the known (from Xavier series) clock and voltage scaling on the semiconductors

and by pairing multiple such chips a wider range of application can be realized with the thus resulting board concepts.[158]
In early 2021, Nvidia announced the Chinese vehicle company NIO will be using an Orin-based chip in their cars.[159]

The so far published specifications for Orin are:

* CPU: 12× Arm Cortex-A78AE (Hercules) ARMv8.2-A (64-bit)[160][161]
* GPU: Ampere-based, 2048[159] CUDA cores and 64 tensor cores1; "with up to 131 Sparse TOPs
of INT8 Tensor compute, and up to 5.32 FP32 TFLOPs of CUDA compute."[162]
* 5.3 CUDA TFLOPs (FP32)[163]
* 10.6 CUDA TFLOPs (FP16)[163]
* Samsung 8N process (derived from 8LPU)[163][164]
* 275 TOPS (INT8) DL[163]
* 170 TOPS DL (INT8) via the GPU
* 105 TOPS DL (INT8) via the 2x NVDLA 2.0 units (DLA, Deep Learning Accelerator)
* 85 TOPS DL (FP16)[163]
* 5 TOPS in the PVA v2.0 unit (Programmable Vision Accelerator for Feature Tracking)
* 1.85 GPix/s in the ISP unit (Image Signal Processor, with native full-range HDR and tile processing support)
* Video processor for ? GPix/s encoding and ? GPix/s decode
* 4× 10 Gbit/s Ethernet, 1× 1 Gbit/s Ethernet

1 Orin uses the double-rate tensor cores in the A100, not the standard tensor cores in consumer Ampere GPUs.

Nvidia announced the latest member of the family, "Orin Nano" in September 2022 at the GPU Technology Conference 2022.[165]

The Orin product line now features SoC and SoM (System-On-Module) based on the core Orin design and scaled for different uses from 60W all the way down to 5W. While less is known about the exact SoC's that are being manufactured, Nvidia has publicly shared detailed technical specifications about the entire Jetson Orin SoM product line. These module specifications illustrate how Orin scales providing insight into future devices that contain an Orin derived SoC.

Module
(Model)  | SoC Variant  | CPU | GPU | Deep
Learning  | Memory  | Adoption  | TDP
(W)

|
|
|
|
|
|
|

Processor
(Cores × Freq)  | Micro-
architecture  | Frequency
(Core config1)  | TFLOPS
(FP32)  | TFLOPS
(FP16)  | TOPS
(INT8)  | Type  | Amount  | Bus
width  | Band-
width  | Availability
Orin AGX
64 GB[166][167] |  | Cortex-A78AE
(9 MB cache)
12× 2.2 GHz  | Ampere | 1300 MHz
2048:64:8
(16, 8, 2)  | 5.32[162] | 10.649  | 275  | LPDDR5  | 64 GB  | 256-bit  | 204.8 GB/s  | Sample: 2021,
Dev-Kit: Q1 2022,
Prod: Dec 2022  | 15-60
Orin AGX
32 GB[168] |  | Cortex-A78AE
(6 MB cache)
8× 2.2 GHz  | 930 MHz
1792:56:7
(14, 7, 2)  | 3.365[162] | 6.73  | 200  | 32 GB  | Oct 2022  | 15-40
Orin NX
16 GB[169] | TE980-M[170] | Cortex-A78AE
(6 MB cache)
8× 2.0 GHz  | 918 MHz
1024:32:4
(8, 4, 1)  | 1.88  | 3.76  | 100  | 16 GB  | 128-bit  | 102.4 GB/s  | Dec 2022  | 10-25
Orin NX
8 GB[168] | TE980-M[170] | Cortex-A78AE
(5.5 MB cache)
6× 2.0 GHz  | 765 MHz
1024:32:4
(8, 4, 1)  | 1.57  | 3.13  | 70  | 8 GB  | Jan 2023  | 10-20
Orin Nano
8 GB[168] |  | Cortex-A78AE
(5.5 MB cache)
6× 1.5 GHz  | 625 MHz
1024:32:4
(8, 4, 1)  | 1.28  | 2.56  | 40  | 68 GB/s  | 7-15
Orin Nano
4 GB[168] |  | 625 MHz
512:16:2
(4, 2, 1)  | 0.64  | 1.28  | 20  | 4 GB  | 64-bit  | 34 GB/s  | 5-10
Module
(Model)  | SoC Variant  | CPU | GPU | Deep
Learning  | Memory  | Adoption  | TDP
(W)

|
|
|
|
|
|
|

Processor
(Cores × Freq)  | Micro-
architecture  | Frequency
(Core config1)  | TFLOPS
(FP32)  | TFLOPS
(FP16)  | TOPS
(INT8)  | Type  | Amount  | Bus
width  | Band-
width  | Availability
Orin Nano Super
8 GB[171] |  | Cortex-A78AE
(5.5 MB cache)
6× 1.7 GHz  | Ampere | 1020 MHz
1024:32:4
(8, 4, 1)  | 2.09  | 4.18  | 67  | LPDDR5  | 8 GB  | 128-bit  | 102.4 GB/s  | Dec 2024  | 7-25

1 CUDA cores : Tensor cores : RT cores (SMs, TPCs, GPCs)

#### Devices

Model  | Devices  | Comments

|
|

T234[172] | Nvidia Jetson AGX Orin[173][162] | comes in 32 GB and 64 GB RAM configurations, available as standalone module or devkit;
intended for industrial robotics and/or embedded HPC applications
Unknown  | Nvidia Jetson Orin NX[169] | mid-power SODIMM-form factor Orin-series module, available only as standalone module;
pin-compatible with Xavier NX carrier
Unknown  | Nvidia Jetson Orin Nano[174] | low-power, cost-effective SODIMM-form factor Orin-series module, available
as standalone module or devkit; intended for entry-level usage
Unknown  | Nvidia DRIVE AGX Orin | used in automotive ADAS applications. 1×Orin 12×A78AE 32GB LPDDR5 @100W, 167+87 INT8 TOPS
Unknown  | Nio Adam[175][176] | built from 4× Nvidia Drive Orin, totals to 48 CPU cores and 8,192 CUDA cores;
for use in vehicles ET7 in March 2022 and ET5 in September 2022
T239
"Drake"  | Nintendo Switch 2 | 8 × ARM Cortex-A78C,[177] 1536 Ampere CUDA cores,[178] 102.4 GB/s LPDDR5X[179]

### Grace

The Grace CPU is an NVIDIA-developed ARM Neoverse V2 (Demeter) CPU platform, targeted at large-scale AI and HPC applications, available within several NVIDIA products. The NVIDIA OVX platform combines the Grace Superchip (two Grace dies on one board) with desktop NVIDIA GPUs in a server form-factor, while the NVIDIA HGX platform is available with either the Grace Superchip or the Grace Hopper Superchip.[180]

The latter is an HPC platform in of itself, combining a Grace CPU with a Hopper-based GPU, announced by NVIDIA on March 22, 2022.[181]

Linux kernel patch sets indicate that a single Grace CPU is also known as T241, placing it under the Tegra SoC branding, despite the chip itself not including a GPU (a referenced T241 patch set cites impact to "NVIDIA server platforms that use more than two T241 chips...interconnected," pointing to the Grace Superchip design).[182]

Model
number  | CPU | Memory  | Adoption

|
|
|

Processor
(Cores/Frequency)  | Cache  | TFLOPS
(FP64)  | Type  | Amount  | Bus
width  | Band-
width  | Availability
T241[183] | Grace - 72x
ARM Neoverse
V2 cores
(ARMv9)[184] | L1: 64 KB I-cache
\+ 64 KB D-cache
per core
L2: 1 MB per core
L3: 117 MB shared[184] | 3.551[184] | LPDDR5X
ECC[184] | Up to
480 GB1[184] | ?  | 500 GB/s[184] | H2 2023[185]

1Figures cut in half from full Grace Superchip specification

### Atlan

Nvidia announced the next-gen SoC codename Atlan on April 12, 2021,[186] at GPU Technology Conference 2021.[187]

Nvidia announced the cancellation of Atlan on September 20, 2022, and their next SoC will be Thor.[188]

Functional units known so far are:

* Grace Next CPU[187]
* Ada Lovelace GPU[189]
* Bluefield DPU (Data Processing Unit)
* other Accelerators
* Security Engine
* Functional Safety Island
* On-Chip-Memory
* External Memory Interface(s)
* High-Speed-IO Interfaces

Model
number  | CPU | GPU | Deep
Learning  | Memory  | Adoption

|
|
|
|
|

Processor
(Cores/Freq)  | Micro-
architecture  | Core
config1 | Freq  | GFLOPS
(FP32)  | GFLOPS
(FP16)  | TOPS
(INT8)  | Type  | Amount  | Bus
width  | Band-
width  | Availability
T254?  | Grace-Next[187]
(?/?)  | Ada
Lovelace[189] | ?  | ?  | ?  | ?  | >1000[189] | ?  | ?  | ?  | ?  | Cancelled[189]
Sept.2022

### Thor

Nvidia announced the next-gen SoC codename Thor on September 20, 2022, at GPU Technology Conference 2022, replacing the cancelled Atlan.[188]

A patchset adding support for Tegra264 to mainline Linux was submitted May 5, 2023, likely indicating initial support for Thor.[190]

The ARM Neoverse V3AE (Poseidon-AE) CPU is built to deliver maximum performance for automotive applications, central compute and machine learning (ML) workloads.[191]

Model
number  | CPU | GPU | Deep
Learning  | Memory  | Adoption  | TDP
(W)

|
|
|
|
|
|

Processor
(Cores/Freq)  | Micro-
architecture  | Core
config1 | Freq.  | TFLOPS
(FP32)  | TFLOPS
(FP16)  | TOPS
(FP8)  | Type  | Amount  | Bus
width  | Band-
width  | Availability
T264[192] | 12x
Neoverse
V3AE
(2.6 GHz)  | Blackwell  | 1536:64:?
(12, 6, 2)  | 1575 MHz  | 4.838  | ?  | 600[188] | LPDDR5X  | 64 GB  | 256-bit  | 273 GB/s  | 2025[188] | 40-70
14x
Neoverse
V3AE[193]
(2.6 GHz)  | 2560:96:?
(20, 10, 3)  | 8.064  | 500  | 1035[188] | 128 GB  | 40-130

#### Devices

* Nvidia DRIVE Thor[188][194]
* Jetson AGX Thor[195]

## Comparison

Generation  | Tegra 2
(Ventana)  | Tegra 3
(Kal-El)  | Tegra 4
(Wayne)  | Tegra 4i
(Grey)  | Tegra K1
(Logan)  | Tegra X1
(Erista)  | Tegra X1+
(Mariko)  | Tegra X2
(Parker)  | Tegra
Xavier  | Tegra
Orin  | Tegra
Thor

|
|
|
|
|
|
|
|
|
|
|

CPU  | Models  | T25 | T30/T33 | T114 | T148? | T124 | T132 | T210 | T214 | T186 | T194 | T234 | T264[196]
Cores  | 2x
Cortex-A9  | 4+1
Cortex-A9  | 4+1
Cortex-A15  | 4+1
Cortex-A9  | 4+1
Cortex-A15  | 2x
Denver | 4x Cortex-A53
(disabled)
\+ 4x Cortex-A57 | 2x Denver2
\+ 4x Cortex-A57 | 8x
Carmel  | 12x
Cortex-A78AE  | 14x
Neoverse
V3AE
Instruction
set  | ARMv7-A (32-bit)  | ARMv8-A (64-bit)  | ARMv8.2-A (64-bit)  | ARMv9.2-A
(64-bit)
L1 cache
(I/D)  | 32/32 KB  | 128/64 KB  | 32/32 KB +
64/32 KB  | 128/64 KB \+
48/32 KB  | 128/64 KB  | 64/64 KB
L2 cache  | 1 MB  | 2 MB  | 128 KB + 2 MB  | 2 MB + 2 MB  | 8 MB  | 3 MB  | 14 MB
L3 cache  | N/A  | 4 MB  | 6 MB  | 16 MB
GPU  | Architecture  | Vec4  | Kepler | Maxwell | Pascal | Volta | Ampere | Blackwell
CUDA cores  | 4+4*  | 8+4*  | 48+24*  | 48+12*  | 192  | 256  | 512  | 2048  | 2560
Tensor cores  | N/A  | 64  | 96
RT cores  | N/A  | 8  | N/A[197]
RAM  | Protocol  | DDR2/
LPDDR2  | DDR3/
LPDDR2  | DDR3/
LPDDR3  | LPDDR3/
LPDDR4  | LPDDR4/
LPDDR4X  | LPDDR5  | LPDDR5X
Max. size  | 1 GB  | 2 GB  | 4 GB  | 8 GB  | 64 GB  | 128 GB
Bandwidth  | 2.7 GB/s  | 6.4 GB/s  | 7.5 GB/s  | 14.9 GB/s  | 25.6 GB/s  | 34.1 GB/s  | 59.7 GB/s  | 136.5 GB/s  | 204.8 GB/s  | 273.0 GB/s
Process  | 40 nm  | 28 nm | 20 nm  | 16 nm  | 12 nm  | 8 nm | 4 nm

* VLIW-based Vec4: Pixel shaders \+ Vertex shaders. Since Kepler, Unified shaders are used.

## Software support

### FreeBSD

FreeBSD supports a number of different Tegra models and generations, ranging from Tegra K1,[198] to Tegra 210.[199]

### Linux

Nvidia distributes proprietary device drivers for Tegra through OEMs and as part of its "Linux for Tegra" (formerly "L4T") development kit, also Nvidia provides JetPack SDK with "Linux for Tegra" and other tools with it. The newer and more powerful devices of the Tegra family are now supported by Nvidia's own Vibrante Linux distribution. Vibrante comes with a larger set of Linux tools plus several Nvidia provided libraries for acceleration in the area of data processing and especially image processing for driving safety and automated driving up to the level of deep learning and neuronal networks that make e.g. heavy use of the CUDA capable accelerator blocks, and via OpenCV can make use of the NEON vector extensions of the ARM cores.

As of April 2012[update], due to different "business needs" from that of their GeForce line of graphics cards, Nvidia and one of their Embedded Partners, Avionic Design GmbH from Germany, are also working on submitting open-source drivers for Tegra upstream to the mainline Linux kernel.[200][201] Nvidia co-founder & CEO laid out the Tegra processor roadmap using Ubuntu Unity in GPU Technology Conference 2013.[202] By end of 2018 it is evident that Nvidia employees have contributed substantial code parts to make the T186 and T194 models run for HDMI display and audio with the upcoming official Linux kernel 4.21 in about Q1 2019. The affected software modules are the open source Nouveau and the closed source Nvidia graphics drivers along with the Nvidia proprietary CUDA interface.[203] As of May, 2022, NVIDIA has open-sourced their GPU kernel modules for both Jetson and desktop platforms, allowing all but proprietary userspace libraries to be open-source on Tegra platforms with official NVIDIA drivers starting with T234 (Orin).[204]

### QNX

The Drive PX2 board was announced with QNX RTOS support at the April 2016 GPU Technology Conference.[205]

## Similar platforms

SoCs and platforms with comparable specifications (e.g. audio/video input, output and processing capability, connectivity, programmability, entertainment/embedded/automotive capabilities & certifications, power consumption) are:

* A-Series by AllWinner
* Apple silicon by Apple
* Atom by Intel
* Exynos by Samsung
* i.MX by Freescale Semiconductor
* Jaguar and Puma by AMD
* K3Vx/Kirin by HiSilicon
* MTxxxx by MediaTek
* NovaThor by ST-Ericsson
* OCTEON by Cavium
* OMAP / Sitara ARM Processor by Texas Instruments
* Qualcomm Snapdragon
* R-Car by Renesas
* RK3xxx by Rockchip
* VideoCore by Broadcom

## See also

* Project Denver
* Nomadik
* XScale
* ZiiLABS

## References

1. ↑ "Techtree.com India > News > Hardware > Nvidia Rolls out "Tegra" Chips". June 4, 2008. http://www.techtree.com/India/News/Nvidia_Rolls_out_Tegra_Processors/551-89833-581.html.
2. ↑ "NVIDIA Tegra FAQ". http://www.nvidia.com/docs/IO/55043/NVIDIA_Tegra_FAQ_External.pdf.
3. ↑ "Nvidia prepara Tegra 3 a 1,5 GHz". TugaTech. 2011-01-27. http://tugatech.com.pt/t3108-nvidia-prepara-tegra-3-a-15-ghz.
4. ↑ "Microsoft's Kin are the first Tegra smartphones – PC World Australia". 2010-04-13. http://www.pcworld.idg.com.au/article/342826/microsoft_kin_first_tegra_smartphones/.
5. ↑ "Nvidia and Opera team to accelerate the full Web on mobile devices" (Press release). Opera Software. 2008-09-09. Archived from the original on March 30, 2012. Retrieved 2009-01-09.
6. ↑ "Nvidia And Opera Team To Accelerate The Full Web On Mobile Devices" (Press release). NVIDIA. 2008-09-09. Archived from the original on December 24, 2011. Retrieved 2009-04-17.
7. ↑ "New Nvidia Tegra Processor Powers The Tablet Revolution". Nvidia. January 7, 2010. http://www.nvidia.com/object/io_1262837617533.html.
8. ↑ "What operating systems does Tegra support?" (Press release). NVIDIA. 2011-08-17. Archived from the original on September 3, 2011. Retrieved 2011-09-14.
9. ↑ "Why nVidia's Tegra 3 is faster than a Core 2 Duo T7200". Brightsideofnews.com. February 21, 2011. http://www.brightsideofnews.com/news/2011/2/21/why-nvidiae28099s-tegra-3-is-faster-than-a-core-2-duo-t7200.aspx.
10. ↑ Hruska, Joel (2011-02-22). "Nvidia's Kal-El Demonstration Marred By Benchmark Confusion". HotHardware. http://hothardware.com/News/Nvidias-KalEl-Demonstration--Marred-By-Benchmark-Shenanigans/.
11. ↑ "Audi selects Tegra processor for infotainment and dashboard". EE Times. 2012-01-18. http://eetimes.com/electronics-news/4234777/Audi-selects-Tegra3-processor-for-infotainment--dashboard.
12. ↑ "What Is Automotive Grade? Here's What It Means". The Official NVIDIA Blog. July 15, 2016. https://blogs.nvidia.com/blog/2016/07/15/automotive-grade/.
13. ↑ "Tegra Automotive Infotainment and Navigation". NVIDIA. http://www.nvidia.com/object/automotive-infotainment-navigation.html.
14. ↑ "NVIDIA Gaming Technology Powers Nintendo Switch | NVIDIA Blog" (in en-US). The Official NVIDIA Blog. 2016-10-20. https://blogs.nvidia.com/blog/2016/10/20/nintendo-switch/.
15. ↑ 15.0 15.1 techinsights.com. "Nintendo Switch Teardown". http://www.techinsights.com/about-techinsights/overview/blog/nintendo-switch-teardown/.
16. ↑ "Nvidia Tegra APX Specifications". http://www.nvidia.com/object/product_tegra_apx_us.html.
17. ↑ "LG Optimus 2X & Nvidia Tegra 2 Review: The First Dual-Core Smartphone". AnandTech. http://www.anandtech.com/show/4144/lg-optimus-2x-nvidia-tegra-2-review-the-first-dual-core-smartphone/5.
18. ↑ "NVidia Tegra 2 Product Information". NVidia. http://www.nvidia.com/object/tegra-2.html.
19. ↑ "NVidia Tegra 2 Product Information". NVidia. http://www.nvidia.com/object/tegra-superchip.html.
20. ↑ "Motorola Xoom Specifications Table". Motorola Mobility, Inc. February 16, 2011. http://developer.motorola.com/products/xoom-mz601/.
21. ↑ Savov, Vlad (2011-05-19). "Dell Streak Pro Honeycomb tablet pictured, likely to be with us in June". Engadget. https://www.engadget.com/2011/05/19/dell-streak-pro-honeycomb-tablet-pictured-likely-to-be-with-us/.
22. ↑ "Toshiba Thrive Review". TabletPCReview. TechTarget, Inc.. August 3, 2011. http://www.tabletpcreview.com/default.asp?newsID=2476&review=toshiba+thrive+android+honeycomb+os+tablet.
23. ↑ "Avionic Design Tegra 2 (T290) Tamonten Processor Module — Product Brief". Avionic Design. http://www.avionic-design.de/uploads/pdf/tamonten_tegra_processor-COM_EN.pdf.
24. ↑ Nvidia inside: Hands on with Audi, Lamborghini, and Tesla by Megan Geuss in May 2014
25. ↑ 25.0 25.1 Processors Analysis and Count in May 2013
26. ↑ "Nvidia announces the Tegra 3 – Kal-El brings PC class performance to Android". Android Central. 2011-11-09. http://www.androidcentral.com/nvidia-announces-tegra-3-pc-class-performance-comes-android-tablets.
27. ↑ "Tegra 3 Multi-Core Processors". NVIDIA. http://www.nvidia.com/object/tegra-3-processor.html.
28. ↑ "ASUS Transformer Prime introduced and examined". HEXUS.net. November 9, 2011. http://hexus.net/mobile/news/tablets/32531-asus-transformer-prime-introduced-examined/.
29. ↑ "NVIDIA Quad-Core Tegra 3 Chip Sets New Standards of Mobile Computing Performance, Energy Efficiency – NVIDIA Newsroom". January 11, 2012. http://pressroom.nvidia.com/easyir/customrel.do?easyirid=A0D622CE9F579F09&version=live&prid=819304&releasejsp=release_157&xhtml=true.
30. ↑ 30.0 30.1 Cite error: Invalid `<ref>` tag; no text was provided for refs named `AnandTech Tegra 4`
31. ↑ "NVIDIA Tegra 3 GPU Specs". July 25, 2023. https://www.techpowerup.com/gpu-specs/tegra-3-gpu.c3226.
32. ↑ 32.0 32.1 32.2 "A Faster Tegra 3, More Memory Bandwidth – ASUS Transformer Pad Infinity (TF700T) Review". http://www.anandtech.com/show/6036/asus-transformer-pad-infinity-tf700t-review/3.
33. ↑ "Tegra 3 Multi-Core Processors". NVIDIA. http://www.nvidia.com/object/tegra-3-processor.html.
34. ↑ "XOLO – The Next Level". July 21, 2013. http://www.xolo.in/xolo-play-features-specs.
35. ↑ "Asus Eee Pad Transformer Prime (Nvidia Tegra 3 Processor; 10.1-inch display) Review". December 30, 2011. http://asia.cnet.com/product/asus-eee-pad-transformer-prime-nvidia-tegra-3-processor-10-1-inch-display-45735891.htm.
36. ↑ "GFXBench – unified graphics benchmark based on DXBenchmark (DirectX) and GLBenchmark (OpenGL ES)". http://www.glbenchmark.com/phonedetails.jsp?benchmark=glpro21&D=Lenovo+LePad+K2&testgroup=system.
37. ↑ Summerson, Cameron (June 19, 2012). "Fuhu Nabi 2 Review: A Quad-Core Android 4.0 Tablet Designed Just For Your Kids – And It's Surprisingly Awesome". http://www.androidpolice.com/2012/06/19/fuhu-nabi-2-review-a-quad-core-android-4-0-tablet-designed-just-for-your-kids-and-its-surprisingly-awesome/.
38. ↑ "Microsoft Announces New Surface Details | News Center". 2012-10-16. http://www.microsoft.com/en-us/news/Press/2012/Oct12/10-16announcementPR.aspx.
39. ↑ "Lenovo Introduces The IdeaPad Yoga 11 and 13, The First Tablet & Laptop Ultrabook Hybrid". TechCrunch. 2012-10-09. https://techcrunch.com/2012/10/09/lenovo-introduces-the-ideapad-yoga-11-and-13-the-first-tablet-laptop-ultrabook-hybrid/.
40. ↑ Jackson, Jerry (2012-10-09). "Lenovo Launches IdeaPad Yoga 11, Yoga 13". http://www.notebookreview.com/default.asp?newsID=6600&news=lenovo+ideapad+yoga.
41. ↑ Hacking a Tesla Model S: What we found and what we learned by Kevin Mahaffey on August 7, 2015
42. ↑ "Nexus 7 tablet hands-on". Engadget. June 27, 2012. https://www.engadget.com/2012/06/27/nexus-7-tablet-hands-on/.
43. ↑ "Toshiba Excite 10 Benchmark Test". YouTube. May 29, 2012. https://www.youtube.com/watch?v=8K8AseX6S1g.
44. ↑ "Blu Products: Quattro45". April 20, 2013. http://bluproducts.com/pro-detail/quattro45.
45. ↑ "Tegra 4 Processors". NVIDIA. http://www.nvidia.com/object/tegra-4-processor.html.
46. ↑ Parrish, Kevin (November 12, 2013). "Results: GPU Benchmarks – EVGA Tegra Note 7 Review: Nvidia's Tegra 4 For $200". http://www.tomshardware.com/reviews/nvidia-tegra-note-7-evga-tablet-review,3668-9.html.
47. ↑ 47.0 47.1 "NVIDIA Tegra Multi-processor Architecture". http://www.nvidia.com/docs/IO/116757/Tegra_4_GPU_Whitepaper_FINALv2.pdf.
48. ↑ Larabel, Michael (December 20, 2012). "NVIDIA Publishes Their Next-Gen Tegra 4 Code". phoronix.com. https://www.phoronix.com/scan.php?page=news_item&px=MTI1OTA.
49. ↑ 49.0 49.1 49.2 49.3 Walrath, Josh (February 26, 2013). "NVIDIA Details Tegra 4 and Tegra 4i Graphics". PC Perspective. http://www.pcper.com/news/Graphics-Cards/NVIDIA-Details-Tegra-4-and-Tegra-4i-Graphics.
50. ↑ 50.0 50.1 Angelini, Chris (February 24, 2013). "Nvidia's Tegra 4 GPU: Doubling Down On Efficiency". Tom's Hardware. http://www.tomshardware.com/reviews/tegra-4-tegra-4i-gpu-architecture,3445.html.
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56. ↑ "HP Slate 8 Pro 7600us Tablet Product Specifications". hp.com. http://support.hp.com/us-en/document/c04005245.
57. ↑ "HP SlateBook x2 Overview – Android Tablet Notebook | HP Official Site". .hp.com. http://www8.hp.com/us/en/ads/x2/slatebook-x2.html.
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63. ↑ "Le Pan – TC1020". Lepantab.com. http://lepantab.com/v2/?portfolio=tc1020.
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71. ↑ "QMobile Noir LT-250". DeviceSpecifications. http://www.hitmobile.pk/phones/qmobile/qmobile-noir-lt-250/.
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73. ↑ "NVIDIA Shield Tablet K1 gets Vulkan support with Android 6.0.1 update". http://www.androidcentral.com/nvidia-shield-tablet-k1-android-601-update-brings-vulkan-graphics-api-support.
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76. ↑ Larabel, Michael (29 April 2014). "NVIDIA's Tegra TK1 Jetson Board Is Now Shipping". Phoronix. https://www.phoronix.com/scan.php?page=news_item&px=MTY3NjA.
77. ↑ Anthony, Sebastian (January 6, 2014). "Tegra K1 64-bit Denver core analysis: Are Nvidia's x86 efforts hidden within?". ExtremeTech. http://www.extremetech.com/computing/174023-tegra-k1-64-bit-denver-core-analysis-are-nvidias-x86-efforts-hidden-within.
78. ↑ NVIDIA CEO confirms Tegra roadmap, building all now: Kal-El, Wayne, Logan, Stark , October 21, 2011: Finally, he confirmed that the inner workings we've heard about in Project Denver will first be present in the Tegra line with the introduction of Stark(...)
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80. ↑ Klug, Brian; Shimpi, Anand Lal (January 6, 2014). "NVIDIA Tegra K1 Preview & Architecture Analysis". AnandTech. p. 3. http://www.anandtech.com/show/7622/nvidia-tegra-k1/3.
81. ↑ Stam, Nick. "Mile High Milestone: Tegra K1 "Denver"? Will Be First 64-bit ARM Processor for Android | The Official NVIDIA Blog". http://blogs.nvidia.com/blog/2014/08/11/tegra-k1-denver-64-bit-for-android/.
82. ↑ Ho, Joshua (5 January 2015). "NVIDIA Tegra X1 Preview & Architecture Analysis". https://www.anandtech.com/show/8811/nvidia-tegra-x1-preview/2.
83. ↑ "Jetson TK1 development board". https://developer.nvidia.com/jetson-tk1.
84. ↑ "SHIELD Tablet, The Ultimate Tablet For Gamers". GeForce. 2014-07-22. http://www.geforce.com/whats-new/articles/shield-tablet-the-ultimate-tablet-for-gamers.
85. ↑ "Tegra K1 Lands in Acer's Newest Chromebook". Anandtech. 2014-08-11. http://www.anandtech.com/show/8354/tegra-k1-lands-in-acers-newest-chromebook.
86. ↑ "HP Chromebook 14 G3 – Specifications". HP. 2018-08-30. https://support.hp.com/us-en/product/hp-chromebook-14-g3/7096564/document/c04481826.
87. ↑ "Xiaomi MiPad 7.9". Techindeep. https://www.techindeep.com/xiaomi-mi-pad-7.9.
88. ↑ "Google". https://www.google.com/atap/projecttango/.
89. ↑ Rothman, Chelsea. "Fuze Tomahawk F1: The Chinese Android XStation 4". http://www.cgmagonline.com/2016/05/11/fuze-tomahawk-f1-the-chinese-android-xstation-4/.
90. ↑ "NVIDIA Tegra K1 System/Computer on Module – Apalis TK1 SOM". https://www.toradex.com/computer-on-modules/apalis-arm-family/nvidia-tegra-k1.
91. ↑ "JXD S192 "retro" gaming tablet is powered by Nvidia's Tegra K1 chipset". https://www.gsmarena.com/jxd_s192_retro_gaming_tablet_is_powered_by_nvidias_tegra_k1_chipset-blog-17904.php.
92. ↑ "Nexus 9". https://www.google.com/nexus/9/.
93. ↑ "Google Nexus 9 Specs and Reviews | HTC United States". http://www.htc.com/us/tablets/nexus-9/.
94. ↑ Exclusive: The Tesla AutoPilot – An In-Depth Look At The Technology Behind the Engineering Marvel by Usman Pirzada on Dec 3, 2015
95. ↑ "Tegra X1 Super Chip | NVIDIA Tegra". NVIDIA. http://www.nvidia.com/object/tegra-x1-processor.html.
96. ↑ "NVIDIA Tegra X1 Preview & Architecture Analysis". http://www.anandtech.com/show/8811/nvidia-tegra-x1-preview.
97. ↑ Tegra_X1_TRM_DP07225001_v1.0.pdf
98. ↑ "Tegra X1 advertised as four core to developers". NVIDIA. December 19, 2015. https://devtalk.nvidia.com/default/topic/904289/jetson-tx1/does-anyone-get-8-cpus-listed-/post/4759807/#4759807.
99. ↑ "Tegra X1's A53 cores are disabled on the Pixel C". Anandtech. http://www.anandtech.com/show/9972/the-google-pixel-c-review/2.
100. ↑ Bittner, Otto; Krachenfels, Thilo; Galauner, Andreas; Seifert, Jean-Pierre (16 August 2021). "The Forgotten Threat of Voltage Glitching: A Case Study on Nvidia Tegra X2 SoCs". 2021 Workshop on Fault Detection and Tolerance in Cryptography (FDTC). pp. 86–97. doi:10.1109/FDTC53659.2021.00021. ISBN 978-1-6654-3673-1.
101. ↑ "NVIDIA Shield Android TV 2019 review" (in en-us). https://www.guru3d.com/articles_pages/nvidia_shield_android_tv_2019_review,2.html.
102. ↑ "Vulnerability Disclosure: Fusée Gelée". https://switch.hacks.guide/files/extras/fusee_gelee_nvidia.pdf.
103. ↑ "Fusée Gelée". https://open-rt.gitbook.io/open-surfacert/common/boot-sequence/tegra-soc-boot-process/fusee-gelee.
104. ↑ "Spreading The Load: Building A Better Hardware Hacking Community by Kate Temkin (@ktemkin) - Media Center | hardwear.io". https://media.hardwear.io/spreading-the-load-building-a-better-hardware-hacking-community/.
105. ↑ 105.0 105.1 Crider, Michael (January 5, 2015). "NVIDIA Announces The New Tegra X1 Mobile Chipset With 256-Core Maxwell GPU". http://www.androidpolice.com/2015/01/04/nvidia-announces-the-new-tegra-x1-mobile-chipset-with-256-core-maxwell-gpu/.
106. ↑ "NVIDIA Jetson TX1 Supercomputer-on-Module Drives Next Wave of Autonomous Machines | Parallel Forall". 2015-11-11. https://devblogs.nvidia.com/parallelforall/nvidia-jetson-tx1-supercomputer-on-module-drives-next-wave-of-autonomous-machines/.
107. ↑ "Slide set from Jetson Nano webinar". https://info.nvidia.com/rs/156-OFN-742/images/Jetson_Nano_Webinar.pdf.
108. ↑ [1]Tegra T210 dfll table
109. ↑ 109.0 109.1 "Tegra X1 (SoC) Technical Reference Manual" (in en-US). http://developer.nvidia.com/embedded/dlc/tegra-x1-technical-reference-manual. (registration required)
110. ↑ Tegra T210b01 dfll table
111. ↑ Strings found in libnvrm_gpu.so and in glxinfo when driver is loaded in linux
112. ↑ Leadbetter, Richard (2019-06-27). "Switch's next Tegra X1 looks set to deliver more performance and longer battery life" (in en). https://www.eurogamer.net/articles/digitalfoundry-2019-switch-new-tegra-x1-silicon-comes-into-focus.
113. ↑ "3.3 Hardware Specifications" (in en-US). http://dystify.com/Overview/contents/Pages/Page_124923644.html.
114. ↑ "Embedded Systems Development Solutions from NVIDIA Jetson". NVIDIA. 2015-03-18. http://www.nvidia.com/object/embedded-systems.html.
115. ↑ "DATA SHEET - NVIDIA Jetson TX2 System-on-Module.pdf". https://www.assured-systems.com/uploads/media/products/axiomtek/eboxs/jetson tx2/data sheet - nvidia jetson tx2 system-on-module.pdf.
116. ↑ NVIDIA Jetson TX2 Delivers Twice the Intelligence to the Edge by Dustin Franklin on March 7, 2017 at Nvidia Developer Blogs
117. ↑ "Jetson TX2 module - Data sheet". https://developer.nvidia.com/embedded/dlc/jetson-tx2-module-data-sheet.
118. ↑ "NVIDIA Discloses Next-Generation Tegra SoC; Parker Inbound?". 2016-01-05. http://www.anandtech.com/show/9902/nvidia-discloses-2016-tegra.
119. ↑ Ho, Joshua. "Hot Chips 2016: NVIDIA Discloses Tegra Parker Details". https://www.anandtech.com/show/10596/hot-chips-2016-nvidia-discloses-tegra-parker-details.
120. ↑ Ho, Joshua (25 August 2016). "Hot Chips 2016: NVIDIA Discloses Tegra Parker Details". Anandtech. http://www.anandtech.com/show/10596/hot-chips-2016-nvidia-discloses-tegra-parker-details.
121. ↑ "NVIDIA Jetson TX2: High Performance AI at the Edge". https://www.nvidia.com/en-us/autonomous-machines/embedded-systems/jetson-tx2/.
122. ↑ 122.0 122.1 "NVIDIA Bringing up Open-Source Volta GPU Support for Their Xavier SoC". https://www.phoronix.com/scan.php?page=news_item&px=NVIDIA-Nouveau-GV11B-Volta-Xav.
123. ↑ 123.0 123.1 NVIDIA Announces Jetson TX2: Parker Comes To NVIDIA's Embedded System Kit , March 7, 2017
124. ↑ NVIDIA Rolls Out Tegra X2 GPU Support In Nouveau by Michael Larabel at phoronix.com on March 29, 2017
125. ↑ "NVIDIA Jetson TX2 GPU Specs | TechPowerUp GPU Database". Techpowerup.com. August 22, 2022. https://www.techpowerup.com/gpu-specs/jetson-tx2-gpu.c3231. Retrieved 2022-08-22.
126. ↑ Shapiro, Danny (January 4, 2017). "ZF Launches ProAI, DRIVE PX 2 Self-Driving System for Cars, Trucks, Factories – NVIDIA Blog". https://blogs.nvidia.com/blog/2017/01/04/zf-ces/.
127. ↑ NVIDIA Powers Mercedes-Benz MBUX, Its Next-Gen AI Cockpit by Danny Shapiro on January 9, 2018 via Nvidia company blogs
128. ↑ Look inside Tesla's onboard Nvidia supercomputer for self-driving by Fred Lambert on May 22, 2017
129. ↑ Tesla Working With AMD on Self-Driving Car Processor by Joel Hruska on September 21, 2017
130. ↑ "Magic Leap One will ship this summer with Nvidia Tegra X2 processor" (in en-US). VentureBeat. 2018-07-11. https://venturebeat.com/2018/07/11/magic-leap-one-will-ship-this-summer-with-nvidia-tegra-x2-processor/.
131. ↑ Magic Leap One teardown at ifixit.com
132. ↑ Skydio's second-gen drone, a $1,000 self-flying action cam, sells out for 2019 by Stephen Shankland on October 2, 2019
133. ↑ Franklin, Dustin (December 12, 2018). "NVIDIA Jetson AGX Xavier Delivers 32 TeraOps for New Era of AI in Robotics". https://devblogs.nvidia.com/nvidia-jetson-agx-xavier-32-teraops-ai-robotics/?ncid=so-fac-mdjngxxrmllhml-69163.
134. ↑ Smith, Ryan. "The NVIDIA GPU Tech Conference 2017 Keynote Live Blog". https://www.anandtech.com/show/11360/the-nvidia-gpu-tech-conference-2017-keynote-live-blog.
135. ↑ Huang, Jensen (May 24, 2017). "The AI Revolution Is Eating Software: NVIDIA Is Powering It | NVIDIA Blog". https://blogs.nvidia.com/blog/2017/05/24/ai-revolution-eating-software/.
136. ↑ 136.0 136.1 Smith, Ryan. "NVIDIA Teases Xavier, a High-Performance ARM SoC for Drive PX & AI". http://www.anandtech.com/show/10714/nvidia-teases-xavier-a-highperformance-arm-soc.
137. ↑ 137.0 137.1 Shapiro, Danny (September 28, 2016). "Introducing NVIDIA Xavier – NVIDIA Blog". https://blogs.nvidia.com/blog/2016/09/28/xavier/.
138. ↑ 138.0 138.1 Cutress, Ian; Tallis, Billy (4 January 2016). "CES 2017: Nvidia Keynote Liveblog". Anandtech.com. http://www.anandtech.com/show/10999/ces-2017-nvidia-keynote-live-blog.
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140. ↑ NVIDIA Drive Xavier SOC Detailed by Hassan Mujtaba on Jan 8, 2018 via WccfTech
141. ↑ 141.0 141.1 141.2 Abazovic, Fuad. "Nvidia Xavier sampling in Q1 18". https://www.fudzilla.com/news/45328-nvidia-xavier-sampling-in-q1-18.
142. ↑ "Welcome — Jetson LinuxDeveloper Guide 34.1 documentation". https://docs.nvidia.com/jetson/l4t/index.html#page/Tegra Linux Driver Package Development Guide/power_management_jetson_xavier.html.
143. ↑ "Programmable Vision Accelerator". https://www.freepatentsonline.com/y2016/0321074.html.
144. ↑ "Understanding MIPI Alliance Interface Specifications". April 1, 2014. https://www.electronicdesign.com/communications/understanding-mipi-alliance-interface-specifications.
145. ↑ Mujtaba, Hassan (January 8, 2018). "NVIDIA Xavier SOC Is The Most Biggest and Complex SOC To Date". https://wccftech.com/nvidia-drive-xavier-soc-detailed/.
146. ↑ 146.0 146.1 Schilling, Andreas (March 27, 2018). "Auf Pegasus folgt Orin: Drive-PX-Plattform mit Turing- oder Ampere-Architektur". https://www.hardwareluxx.de/index.php/news/hardware/prozessoren/46029-auf-pegasus-folgt-orin-drive-px-plattform-mit-turing-oder-ampere-architektur.html.
147. ↑ Sundaram, Shri (September 12, 2018). "Introducing NVIDIA DRIVE AGX Xavier Developer Kit – NVIDIA Blog". https://blogs.nvidia.com/blog/2018/09/12/nvidia-drive-agx-developer-kit-autonomous-driving/.
148. ↑ 148.0 148.1 "Jetson AGX Xavier Developer Kit". July 9, 2018. https://developer.nvidia.com/embedded/buy/jetson-agx-xavier-devkit.
149. ↑ "Jetson Xavier NX Developer Kit". November 6, 2019. https://www.nvidia.com/en-us/autonomous-machines/embedded-systems/jetson-xavier-nx/.
150. ↑ Powell, Kimberly (September 12, 2018). "NVIDIA Clara Platform to Usher in Next Generation of Medical Instruments – NVIDIA Blog". https://blogs.nvidia.com/blog/2018/09/12/nvidia-clara-platform/.
151. ↑ "NVIDIA Rolls Out Tesla T4 GPUs, DRIVE AGX Xavier & Clara Platform – Phoronix". https://www.phoronix.com/scan.php?page=news_item&px=NVIDIA-GTC-Japan-2018.
152. ↑ Shilov, Anton (18 March 2017). "Bosch and Nvidia Team Up for Xavier based Self-Driving Systems for Mass Market Cars". Anandtech.com. http://www.anandtech.com/show/11205/bosch-and-nvidia-team-up-for-xavierbased-selfdriving-systems-for-mass-market-cars.
153. ↑ "Dream safety: 'Dream Car' learns to drive autonomously". https://vision.zf.com/site/magazine/en/articles_3392.html.
154. ↑ "Baidu, NVIDIA and ZF team to drive autonomous vehicles in China". January 8, 2018. https://techwireasia.com/2018/01/baidu-nvidia-and-zf-team-to-drive-autonomous-vehicles-in-china/.
155. ↑ Linux Kernel Mailing List: (PATCH v3 7/7) arm64: tegra: Add device tree for the Tegra194 P2972-0000 board by Mikko Perttunen on Feb 15 2018
156. ↑ Smith, Ryan. "NVIDIA ARM SoC Roadmap Updated: After Xavier Comes Orin". https://www.anandtech.com/show/12598/nvidia-arm-soc-roadmap-updated-after-xavier-comes-orin.
157. ↑ Smith, Ryan. "NVIDIA Details DRIVE AGX Orin: A Herculean Arm Automotive SoC For 2022". https://www.anandtech.com/show/15245/nvidia-details-drive-agx-orin-a-herculean-arm-automotive-soc-for-2022.
158. ↑ online, heise (December 18, 2019). "Nvidia Orin: Next-Gen-Prozessor für autonome Fahrzeuge mit hoher Rechenleistung". https://www.heise.de/newsticker/meldung/Autonomes-Fahren-Nvidia-bringt-Kombiprozessor-Orin-mit-Next-Gen-GPU-4619375.html.
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160. ↑ Williams, Chris. "Arm hasn't given up on self-driving car brains – its new Cortex-A78AE is going into Nvidia's Orin chip, for a start". https://www.theregister.com/2020/09/29/arm_cortex_a78ae/.
161. ↑ Ltd, Arm. "Cortex-A78AE – Arm". https://www.arm.com/products/silicon-ip-cpu/cortex-a/cortex-a78ae.
162. ↑ 162.0 162.1 162.2 162.3 "NVIDIA Jetson AGX Orin Technical Brief.pdf". https://www.nvidia.com/content/dam/en-zz/Solutions/gtcf21/jetson-orin/nvidia-jetson-agx-orin-technical-brief.pdf.
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164. ↑ Tingle, Jeremy. "Nvidia's Ampere & Process Technology: Sunk by Samsung?" (in en). https://chipsandcheese.com/p/nvidias-ampere-process-technology-sunk-by-samsung.
165. ↑ Nvidia. "NVIDIA Jetson Orin Nano Sets New Standard for Entry-Level Edge AI and Robotics With 80x Performance Leap". https://nvidianews.nvidia.com/news/nvidia-jetson-orin-nano-sets-new-standard-for-entry-level-edge-ai-and-robotics-with-80x-performance-leap.
166. ↑ "kernel/git/next/linux-next.git - The linux-next integration testing tree". https://git.kernel.org/pub/scm/linux/kernel/git/next/linux-next.git/commit/?id=b0e0423cfabc1eb407baee52cabbd9df2830feb0.
167. ↑ "Linux 5.10 Has Initial Support For NVIDIA Orin, DeviceTree For Purism's Librem 5 - Phoronix". https://www.phoronix.com/scan.php?page=news_item&px=Linux-5.10-ARM-Platform.
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169. ↑ 169.0 169.1 "Embedded Robotics Modules - Jetson Orin NX". https://www.nvidia.com/en-us/autonomous-machines/embedded-systems/jetson-orin-nx/.
170. ↑ 170.0 170.1 "Jetson Orin NX Series - Thermal Design Guide". September 28, 2022. https://developer.download.nvidia.com/assets/embedded/secure/jetson/orin_nx/docs/Jetson_Orin_NX_Series_Thermal_Design_Guide_TDG-11127-001_v1.0.pdf.
171. ↑ "Jetson Orin Nano Super Developer Kit | NVIDIA". https://www.nvidia.com/en-us/autonomous-machines/embedded-systems/jetson-orin/nano-super-developer-kit/.
172. ↑ "Linux 5.18 Adding Audio Support for NVIDIA's Orin SoC". https://www.phoronix.com/scan.php?page=news_item&px=NVIDIA-Orin-Tegra234-Audio.
173. ↑ "NVIDIA Jetson AGX Orin". https://www.nvidia.com/en-us/autonomous-machines/embedded-systems/jetson-agx-orin/.
174. ↑ "Jetson Orin for Next-Gen Robotics". NVIDIA Corporation. https://www.nvidia.com/en-us/autonomous-machines/embedded-systems/jetson-orin/.
175. ↑ "NIO ET5 Designed for Autonomous Era with DRIVE Orin". December 20, 2021. https://blogs.nvidia.com/blog/2021/12/20/nio-et5-designed-autonomous-era-drive-orin/.
176. ↑ "Chinese Automaker NIO Selects NVIDIA for Electric Vehicles". January 9, 2021. https://blogs.nvidia.com/blog/2021/01/09/nio-selects-nvidia-intelligent-electric-vehicles/.
177. ↑ "Nintendo Switch 2: Die-Shot zeigt Nvidia Tegra T239 im Detail". https://www.pcgameshardware.de/Nintendo-Switch-2-Konsolen-280469/News/Nvidia-Tegra-T239-im-Detail-1472183/.
178. ↑ "Nintendo Switch 2: Nvidia Tegra T239 ist größer als Apple M4, zeigt sich auf Mainboard-Foto - Notebookcheck.com News". https://www.notebookcheck.com/Nintendo-Switch-2-Nvidia-Tegra-T239-ist-groesser-als-Apple-M4-zeigt-sich-auf-Mainboard-Foto.1003961.0.html.
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180. ↑ "Introducing Grace" (in en-us). https://www.nvidia.com/en-us/data-center/grace-cpu/.
181. ↑ "NVIDIA Introduces Grace CPU Superchip" (in en-us). http://nvidianews.nvidia.com/news/nvidia-introduces-grace-cpu-superchip.
182. ↑ "LKML: Marc Zyngier: Re: [PATCH irqchip/gicv3: Workaround for NVIDIA erratum T241-FABRIC-4"]. https://lkml.org/lkml/2023/3/7/162.
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185. ↑ "Nvidia CEO Comments on Grace CPU Delay, Teases Sampling Silicon" (in en). 2023-03-22. https://www.tomshardware.com/news/nvidia-ceo-jensen-huang-grace-delay.
186. ↑ "NVIDIA Unveils DRIVE Atlan Autonomous Vehicle Platform". April 12, 2021. https://blogs.nvidia.com/blog/2021/04/12/nvidia-drive-atlan-autonomous-vehicle-platform/.
187. ↑ 187.0 187.1 187.2 "NVIDIA Unveils NVIDIA DRIVE Atlan, an AI Data Center on Wheels for Next-Gen Autonomous Vehicles". https://nvidianews.nvidia.com/news/nvidia-unveils-nvidia-drive-atlan-an-ai-data-center-on-wheels-fornext-gen-autonomous-vehicles.
188. ↑ 188.0 188.1 188.2 188.3 188.4 188.5 "NVIDIA Unveils DRIVE Thor — Centralized Car Computer Unifying Cluster, Infotainment, Automated Driving, and Parking in a Single, Cost-Saving System". https://nvidianews.nvidia.com/news/nvidia-unveils-drive-thor-centralized-car-computer-unifying-cluster-infotainment-automated-driving-and-parking-in-a-single-cost-saving-system.
189. ↑ 189.0 189.1 189.2 189.3 "NVIDIA Drops DRIVE Atlan SoC, Introduces 2 PFLOPS DRIVE Thor for 2025 Autos". https://www.anandtech.com/show/17582/nvidia-drops-drive-atlan-soc-introduces-2-pflops-drive-thor-for-2025-autos.
190. ↑ "'[PATCH 1/5 dt-bindings: mailbox: tegra: Document Tegra264 HSP' - MARC"]. https://marc.info/?l=linux-tegra&m=168354850122564&w=2.
191. ↑ "Neoverse V3AE - CPU - Arm • www.arm.com › products › silicon-ip-cpu › neoverse". https://www.arm.com/products/silicon-ip-cpu/neoverse/neoverse-v3ae.
192. ↑ "テカナリエ清水 on X: "Thor チップ開封終わったよー". https://x.com/techanalye1/status/1979239029335036371.
193. ↑ "NVIDIA DRIVE Thor Strikes AI Performance Balance, Uniting AV and Cockpit on a Single Computer". September 20, 2022. https://blogs.nvidia.com/blog/2022/09/20/drive-thor/.
194. ↑ "NVIDIA DRIVE Powers Next Generation of Transportation — from Cars and Trucks to Robotaxis and Autonomous Delivery Vehicles". https://nvidianews.nvidia.com/news/nvidia-drive-powers-next-generation-transportation.
195. ↑ "NVIDIA Announces Project GR00T Foundation Model for Humanoid Robots and Major Isaac Robotics Platform Update". https://nvidianews.nvidia.com/news/foundation-model-isaac-robotics-platform.
196. ↑ "テカナリエ清水 on X: "Thor チップ開封終わったよー". https://x.com/techanalye1/status/1979239029335036371.
197. ↑ "Thor & RT cores - Jetson Thor - NVIDIA Developer Forums". https://forums.developer.nvidia.com/t/thor-rt-cores/343693.
198. ↑ "FreeBSD on Jetson TK1 | FreeBSD developer's notebook". https://kernelnomicon.org/?p=628.
199. ↑ "src - FreeBSD source tree". https://cgit.freebsd.org/src/commit/?id=b9cbd68d1cbbb21eade18182a797d5fa7d0dc11.
200. ↑ Mayo, Jon (April 20, 2012). "[RFC 0/4] Add NVIDIA Tegra DRM support". dri-devel (Mailing list). Archived from the original on December 25, 2014. Retrieved 2012-08-21.
201. ↑ Larabel, Michael (April 11, 2012). "A NVIDIA Tegra 2 DRM/KMS Driver Tips Up". Phoronix Media. https://www.phoronix.com/scan.php?page=news_item&px=MTA4NjA.
202. ↑ "GTC 2013: NVIDIA's Tegra Roadmap (6 of 11)". YouTube. March 19, 2013. https://www.youtube.com/watch?v=8kIQWWJs_po&t=9m35s.
203. ↑ "NVIDIA Tegra X2 & Xavier Get HDMI Audio With Linux 4.21 – Phoronix". https://www.phoronix.com/scan.php?page=news_item&px=Tegra-X2-Xavier-HDMI-Audio.
204. ↑ "NVIDIA Releases Open-Source GPU Kernel Modules" (in en-US). 2022-05-19. https://developer.nvidia.com/blog/nvidia-releases-open-source-gpu-kernel-modules/.
205. ↑ "DRIVE PX 2 Shows Next-Gen Nvidia Tegra, Pascal Processors". April 5, 2016. https://vrworld.com/2016/04/05/nvidia-drive-px2-next-gen-tegra-pascal-gpu/.

## External links

* Official website
* Nvidia's Tegra APX website
* Nvidia's Tegra FAQ
* Tegra X1 Whitepaper
* Tegra K1 Whitepaper
* Tegra 4 CPU Whitepaper
* Tegra 4 GPU Whitepaper
* Tegra 3 Whitepaper
* Tegra 2 Whitepaper

* v
* t
* e

Nvidia

GeForce (List of GPUs)

| Fixed pixel pipeline|

| Pre-GeForce|

* NV1
* NV2

* RIVA 128
* RIVA TNT
* TNT2

|

* GeForce 256
* 2
* 4 MX

Vertex and pixel shaders|

* GeForce 3
* 4 Ti
* FX
* 6
* 7

Unified shaders|

* GeForce 8
* 9
* 100
* 200
* 300
* 400
* 500

Unified shaders & NUMA|

* GeForce 600
* 700
* 800M
* 900
* 10
* 16

Ray tracing|

* GeForce 20

Software and technologies

| Multimedia
acceleration|

* NVENC (video encoding)
* PureVideo (video decoding)

|

Software|

* Cg (shading language)
* CUDA
* Gelato (offline renderer)
* Nvidia GameWorks
* OptiX (ray tracing API)
* PhysX (physics SDK)
* Nvidia RTX (ray tracing platform)
* Nvidia System Tools
* VDPAU (video decode API)

Technologies|

* Nvidia 3D Vision (stereo 3D)
* Nvidia G-Sync (variable refresh rate)
* Nvidia Optimus (GPU switching)
* Nvidia Surround (multi-monitor)
* NVLink (protocol)
* Scalable Link Interface (multi-GPU)
* TurboCache (framebuffer in system memory)

GPU microarchitectures|

* Tesla
* Fermi
* Kepler
* Maxwell
* Pascal
* Volta
* Turing
* Ampere
* Hopper

Other products

| Graphics processing|

* Nvidia Quadro
* Quadro Plex

|

GPGPU|

* Nvidia Tesla
* DGX

Console components|

* NV2A (Xbox)
* RSX 'Reality Synthesizer' (PlayStation 3)
* Tegra NX-SoC (Nintendo Switch)

Nvidia Shield|

* Shield Portable
* Shield Tablet
* Shield Android TV
* GeForce Now

SoCs and embedded|

* GoForce
* Drive
* Jetson
* Tegra

CPUs|

* Project Denver

Computer chipsets|

* nForce

Company

| Key people|

* Jen-Hsun Huang
* Chris Malachowsky
* Curtis Priem
* David Kirk
* Bill Dally
* Debora Shoquist
* Ranga Jayaraman
* Jonah M. Alben

|

Acquisitions|

* 3dfx Interactive
* Ageia
* ULi
* Icera
* Mental Images
* PortalPlayer
* Exluna
* MediaQ
* Stexar

ARM-based chips

* v
* t
* e

Application ARM-based chips

* ARM Holdings
* ARM architecture
* List of ARM microarchitectures
* List of applications of ARM cores
* ARM Cortex-A
* ARM Cortex-R
* ARM Cortex-M
* Comparison of ARMv7-A cores
* Comparison of ARMv8-A cores

Application
processors
(32-bit)|

| Cortex-A5|

* Actions ATM702x
* Amlogic M805/S805, T82x
* Atmel SAMA5D3
* InfoTM iMAPx820, iMAPx15
* Qualcomm Snapdragon S4 Play, 200
* RDA RDA8810PL
* Telechips TCC892x

|

Cortex-A7|

* Allwinner A2x, A3x, A83T, H3, H8
* NXP i.MX7, QorIQ LS10xx, NXP i.MX6UL
* Broadcom VideoCore BCM2836, BCM23550
* Leadcore LC1813, LC1860/C, LC1913, LC1960
* Marvell Armada PXA1920, 1500 mini plus
* MediaTek MT65xx
* Qualcomm Snapdragon 200, 400

Cortex-A8|

* Allwinner A1x
* Apple A4
* Freescale i.MX5
* Rockchip RK291x
* Samsung Exynos 3110(S5PC110), S5PV210
* Texas Instruments OMAP 3
* Texas Instruments Sitara AM3xxx
* Texas Instruments DM38x
* ZiiLABS ZMS-08

Cortex-A9|

* Actions ATM702x, ATM703x
* Altera Cyclone V, Arria V/10
* Amlogic AML8726, MX, M6x, M801, M802/S802, S812, T86x
* Apple A5, A5X
* Broadcom VideoCore BCM21xxx, BCM28xxx
* Freescale i.MX6
* HiSilicon K3V2, 910's
* InfoTM iMAPx912
* Leadcore LC1810, LC1811
* Marvell Armada 1500 mini
* MediaTek MT65xx
* Nvidia Tegra, 2, 3, 4i
* Nufront NuSmart 2816M, NS115, NS115M
* Renesas EMMA EV2, R-Car H1, RZ/A
* Rockchip RK292x, RK30xx, RK31xx
* Samsung Exynos 4 421x, 441x
* ST-Ericsson NovaThor
* Telechips TCC8803
* Texas Instruments OMAP 4
* Texas Instruments Sitara AM4xxx
* VIA WonderMedia WM88x0, 89x0
* Xilinx Zynq-7000
* ZiiLABS ZMS-20, ZMS-40

Cortex-A15|

* Allwinner A80
* HiSilicon K3V3
* MediaTek MT8135/V
* Nvidia Tegra 4, K1
* Renesas R-Car H2
* Samsung Exynos 5 52xx, 54xx
* Texas Instruments OMAP 5, DRA7xx, AM57xx
* Texas Instruments Sitara AM5xxx

Cortex-A17|

* MediaTek MT6595, MT5595
* MStar 6A928
* Rockchip RK3288

ARMv7-A
compatible|

* Apple A6, A6X, S1, S1P, S2, S3
* Broadcom Brahma-B15
* Marvell P4J
* Qualcomm Snapdragon S1, S2, S3, S4 Plus, S4 Pro, 600, 800 (Scorpion, Krait)

Others|

* Enhanced Cortex-A8
* Enhanced Cortex-A9
* Cortex-A12
* Cortex-A32

Application
processors
(64-bit)|

| Cortex-A35|

* NXP i.MX8X
* MediaTek MT8516
* Rockchip RK3308

|

Cortex-A53|

* Actions GT7, S900, V700
* Allwinner A64, H5, H64, R18
* Altera Stratix 10
* Amlogic S9 Family, T96x
* Broadcom BCM2837
* EZchip TILE-Mx100
* HiSilicon Kirin 620, 65x, 93x
* Marvell Armada PXA1928, Mobile PXA1908/PXA1936
* MediaTek MT673x, MT675x, MT6795, MT873x, MT8752, MT8163
* NXP ARM S32, QorIQ LS1088, i.MX8M
* Qualcomm Snapdragon 41x, 42x, 43x, 61x, 62x
* Rockchip RK3328, RK3368
* Samsung Exynos 7 75xx, 78xx
* Spreadtrum SC9860/GV, SC9836
* Texas Instruments Sitara AM6xxx
* Xilinx ZynqMP

Cortex-A55|

* Samsung Exynos 9 Series 98xx
* Unisoc SC9863A

Cortex-A57|

* AMD Opteron A1100-series
* NXP QorIQ LS20xx
* Nvidia Tegra X1 and Tegra X2
* Qualcomm Snapdragon 808, 810
* Samsung Exynos 7 5433, 7420
* HiSilicon Kirin Hi1610 and Hi1612

Cortex-A72|

* HiSilicon Kirin 95x, Kunpeng 916
* MediaTek Helio X2x, MT817x
* MStar 6A938
* Qualcomm Snapdragon 65x
* Rockchip RK3399
* NXP QorIQ LS2088, QorIQ LS1046A, i.MX8

Cortex-A73|

* HiSilicon Kirin 960, Kirin 970
* MediaTek Helio X30
* Amlogic S922X

Cortex-A75|

* Qualcomm Snapdragon 71x, Snapdragon 845 and 850
* Samsung Exynos 9820, Exynos 9825

Cortex-A76|

* HiSilicon Kirin 980, Kirin 990
* Qualcomm Snapdragon 855 and 8cx, Snapdragon 675, Snapdragon 730 and 730G
* MediaTek Helio G90

Cortex-A77|

* MediaTek Dimensity 1000

ARMv8-A
compatible|

* Apple A7, A8, A8X, A9, A9X, A10, A10X, A11, A12, A12X, A13
* Applied Micro X-Gene
* Cavium ThunderX, ThunderX2
* HiSilicon TaiShan v110
* Nvidia Tegra K1 (Denver), Tegra X2 (Denver2), Tegra Xavier (Carmel),
* Qualcomm Kryo, Falkor
* Samsung Mongoose

* v
* t
* e

Embedded ARM-based chips

* ARM Holdings
* ARM architecture
* List of ARM cores
* ARM Cortex-A
* ARM Cortex-R
* ARM Cortex-M
* List of ARM Cortex-M development tools

Embedded
microcontrollers|

| Cortex-M0|

* Cypress PSoC 4000, 4100, 4100M, 4200, 4200DS, 4200L, 4200M
* Infineon XMC1000
* Nordic nRF51
* NXP LPC1100, LPC1200
* nuvoTon NuMicro
* Sonix SN32F700
* STMicroelectronics STM32 F0
* Toshiba TX00
* Vorago VA108x0

|

Cortex-M0+|

* Cypress PSoC 4000S, 4100S, 4100S+, 4100PS, 4700S, FM0+
* Holtek HT32F52000
* Microchip (Atmel) SAM C2, D0, D1, D2, DA, L2, R2, R3
* NXP LPC800, LPC11E60, LPC11U60
* NXP (Freescale) Kinetis E, EA, L, M, V1, W0
* Renesas Synergy S1
* Silicon Labs (Energy Micro) EFM32 Zero, Happy
* STMicroelectronics STM32 L0

Cortex-M1|

* Altera FPGAs Cyclone-II, Cyclone-III, Stratix-II, Stratix-III
* Microsemi (Actel) FPGAs Fusion, IGLOO/e, ProASIC3L, ProASIC3/E
* Xilinx FPGAs Spartan-3, Virtex-2-3-4

Cortex-M3|

* Actel SmartFusion, SmartFusion 2
* Analog Devices ADuCM300
* Cypress PSoC 5000, 5000LP, FM3
* Fujitsu FM3
* Holtek HT32F
* Microchip (Atmel) SAM 3A, 3N, 3S, 3U, 3X
* NXP LPC1300, LPC1700, LPC1800
* ON Semiconductor Q32M210
* Silicon Labs Precision32
* Silicon Labs (Energy Micro) EFM32 Tiny, Gecko, Leopard, Giant
* STMicroelectronics STM32 F1, F2, L1
* Texas Instruments F28, LM3, TMS470, OMAP 4
* Toshiba TX03

Cortex-M4|

* Microchip (Atmel) SAM 4L, 4N, 4S
* NXP (Freescale) Kinetis K, W2

Cortex-M4F|

* Cypress 6200, FM4
* Infineon XMC4000
* Microchip (Atmel) SAM 4C, 4E, D5, E5, G5
* Microchip CEC1302
* Nordic nRF52
* NXP LPC4000, LPC4300
* NXP (Freescale) Kinetis K, V3, V4
* Renesas Synergy S3, S5, S7
* Silicon Labs (Energy Micro) EFM32 Wonder
* STMicroelectronics STM32 F3, F4, L4, L4+, WB
* Texas Instruments LM4F/TM4C, MSP432
* Toshiba TX04

Cortex-M7F|

* Microchip (Atmel) SAM E7, S7, V7
* NXP (Freescale) Kinetis KV5x
* STMicroelectronics STM32 F7, H7

Cortex-M23|

* Microchip (Atmel) SAM L10, L11

Real-time
microcontrollers|

| Cortex-R4F|

* Texas Instruments RM4, TMS570

|

Cortex-R5F|

* Scaleo OLEA
* Texas Instruments RM57
* Xilinx ZynqMP

* v
* t
* e

Classic ARM-based chips

* ARM Holdings
* ARM architecture
* List of ARM cores
* ARM Cortex-A
* ARM Cortex-R
* ARM Cortex-M
* List of ARM Cortex-M development tools

Classic
processors|

| ARM7|

* Atmel SAM7L, SAM7S, SAM7SE, SAM7X, SAM7XC, AT91CAP7, AT91M, AT91R
* Cirrus Logic PS7xxx, EP7xxx
* Mediatek MT62xx
* NXP LPC2100, LPC2200, LPC2300, LPC2400, LH7
* STMicroelectronics STR7

|

ARM9|

* Aspeed AST2400
* Atmel SAM9G, SAM9M, SAM9N, SAM9R, SAM9X, SAM9XE, SAM926x, AT91CAP9
* Cirrus Logic EP9xxx
* Freescale i.MX1x, i.MX2x
* Nuvoton NUC900
* NXP LPC2900, LPC3000, LH7A
* Rockchip RK27xx, RK28xx
* Samsung S3C24xx
* ST-Ericsson Nomadik STn881x
* STMicroelectronics STR9
* Texas Instruments OMAP 1, AM1x, DaVinci
* VIA WonderMedia WM8505/8650
* ZiiLABS ZMS-05

ARM11|

* Broadcom BCM2835
* Cavium CNS3xxx
* Freescale i.MX3x
* Infotmic IMAPX210/220
* Mindspeed Comcerto 1000
* Nvidia Tegra APX, 6xx
* Qualcomm MSM7000, Snapdragon S1
* Samsung S3C64xx, S5P64xx
* ST-Ericsson Nomadik STn882x
* Telechips TCC8902
* Texas Instruments OMAP 2
* VIA WonderMedia WM87x0

ARMv2a
compatible|

* Amber (open FPGA core)

ARMv4
compatible|

* Faraday FA526, FA626
* DEC/Intel StrongARM

ARMv5TE
compatible|

* Intel/Marvell XScale
* Marvell Sheeva, Feroceon, Jolteon, Mohawk
* Faraday FA606TE, FA616TE, FA626TE, FA726TE

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