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Wikipedia / 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.

History

The Tegra APX 2500 was announced on February 12, 2008. The Tegra 6xx product line was revealed on June 2, 2008, 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).

The first product to use the Tegra was Microsoft's Zune HD media player in September 2009, followed by the Samsung M1. Microsoft's Kin was the first cellular phone to use the Tegra; 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. 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. 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.

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, 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. The processor will be integrated into Audi's entire line of vehicles worldwide, beginning in 2013. The process is ISO 26262-certified.

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."

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. On March 15, 2017, TechInsights revealed the Nintendo Switch is powered by a custom Tegra X1 (model T210), with lower clockspeeds.

Models

Tegra APX

  1. Tegra APX 2500

Processor: ARM11 600MHz MPCore (originally GeForce ULV)

  • Suffix: APX (formerly CSX)

  • Memory: NOR or NAND flash, Mobile DDR

Graphics: Image processor (FWVGA 854×480 pixels)

Video codecs:

  • 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

  1. Tegra 600

  2. Targeted for GPS segment and automotive

  3. Processor: ARM11 700MHz MPCore

  4. Memory: low-power DDR (DDR-333, 166MHz)

  5. SXGA, HDMI, USB, stereo jack

  6. HD camera 720p

  7. Tegra 650

  8. Targeted for GTX of handheld and notebook

  9. Processor: ARM11 800MHz MPCore

  10. Low power DDR (DDR-400, 200MHz)

  11. Less than 1watt envelope

  12. HD image processing for advanced digital still camera and HD camcorder functions

  13. Display supports 1080p at 24 frame/s, HDMI v1.3, WSXGA+ LCD and CRT, and NTSC/PAL TV output

  14. Direct support for Wi-Fi, disk drives, keyboard, mouse, and other peripherals

  15. A complete board support package (BSP) to enable fast time to market for Windows Mobile-based designs

Tegra 2

The second generation Tegra SoC has a dual-core ARM Cortex-A9 CPU, an ultra low power (ULP) GeForce GPU, a 32-bit memory controller with either LPDDR2-600 or DDR2-667 memory, a 32KB/32KB L1 cache per core and a shared 1MB L2 cache. 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. The lack of support for high-profile H.264 is particularly troublesome when using online video streaming services.

Common features:

  • CPU cache: L1: 32KB instruction + 32KB data, L2: 1MB

  • 40 nm semiconductor technology

Modelnumber

CPU

GPU

Memory

Adoption

Processor

Cores

Frequency

Micro-architecture

Coreconfig1

Frequency

Type

Amount

Buswidth

Band-width

Availability

AP20H (Ventana/Unknown)

Cortex-A9

2

1.0GHz

VLIW-basedVEC4 units

4:4:4:4

300MHz

LPDDR2300MHzDDR2333MHz

?

32bitsingle-channel

2.4 GB/s2.7 GB/s

Q1 2010

T20 (Harmony/Ventana)

333MHz

AP25

1.2GHz

400MHz

Q1 2011

T25

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

Devices

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, Sony Tablet S, Dell Streak Pro, Toshiba Thrive tablet, T-Mobile G-Slate

AP215

Fusion Garage Grid 10

T20

Avionic Design Tamonten Processor Board, 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

Tesla Motors Model S 2012~2017 and Model X 2015~2017 instrument cluster (IC)

Tegra 3

NVIDIA's Tegra 3 (codenamed "Kal-El") 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". 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 40Mbit/s High-Profile, VC1-AP, and simpler forms of MPEG-4 such as DivX and Xvid.

The Tegra 3 was released on November 9, 2011.

Common features:

  • CPU cache: L1: 32KB instruction + 32KB data, L2: 1MB

  • 40 nm LPG semiconductor technology by TSMC

Modelnumber

CPU

GPU

Memory

Adoption

Processor

Cores

Frequency(multi-/single-core mode)

Micro-architecture

Coreconfig1

Frequency

Type

Amount

Buswidth

Band-width

Availability

T30L

Cortex-A9

4+1

1.2GHz/up to 1.3GHz

VLIW-basedVEC4 units

8:4:8:8

416MHz

DDR3-1333

?

32 bitsingle-channel

5.3 GB/s

Q1 2012

T30

1.4GHz/up to 1.5GHz

520MHz

LPDDR2-1066DDR3-L-1500

?

4.3 GB/s6.0 GB/s

Q4 2011

AP33

T33

1.6GHz/up to 1.7GHz

DDR3-1600

?

6.4 GB/s

Q2 2012

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

Devices

Model

Devices

AP33

LG Optimus 4X HD, HTC One X, XOLO Play T1000, Coolpad 8735

T30

Asus Eee Pad Transformer Prime (TF201), IdeaTab K2 / LePad K2, Acer Iconia Tab A510, Fuhu Inc. nabi 2 Tablet, Microsoft Surface RT, Lenovo IdeaPad Yoga 11,

T30I

Tesla Model S 2012~2017 and Model X 2015~2017 media control unit (MCU)

T30L

Asus Transformer Pad TF300T, Microsoft Surface, Nexus 7 (2012), Sony Xperia Tablet S, Acer Iconia Tab A210, Toshiba AT300 (Excite 10), BLU Quattro 4.5, Coolpad 9070

T33

Asus Transformer Pad Infinity (TF700T), Fujitsu ARROWS X F-02E, HTC One X+, Ouya (T33-P-A3)

Tegra 4

The Tegra4 (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 Tegra3.

The GeForce GPU in Tegra4 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 Tegra4 GPU is typically several times faster than that of Tegra3. Additionally, the Tegra4 video processor has full support for hardware decoding and encoding of WebM video (up to 1080p 60Mbit/s @ 60fps).

Along with Tegra4, 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 (100Mbit/s) LTE but will later be updated to Category 4 (150Mbit/s).

Common features:

  • CPU cache: L1: 32KB instruction + 32KB data, L2: 2MB

  • 28 nm HPL semiconductor technology

Modelnumber

CPU

GPU

Memory

Adoption

Processor(Cores/Freq)

Micro-architecture

Core config1

Frequency

Type

Amount

Buswidth

Band-width

Availability

T114

4+1×1.9GHz Cortex-A15

VLIW-based VEC4 units

72(48:24:4)

672MHz

DDR3L or LPDDR3

?

32-bit dual-channel

up to 14.9GB/s (1866MT/s data rate)

Q2 2013

  1. 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, HP Slate 7 Beats Special Edition, HP Slate 8 Pro, HP SlateBook x2, HP SlateBook 14, HP Slate 21, 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), Coolpad 8970L ( 4), Audi Tablet, Le Pan TC1020 10.1", Matrimax iPLAY 7, Kobo Arc 10HD

Tegra 4i

The Tegra4i (codenamed "Grey") was announced on February 19, 2013. With hardware support for the same audio and video formats, but using Cortex-A9 cores instead of Cortex-A15, the Tegra4i is a low-power variant of the Tegra4 and is designed for phones and tablets. Unlike its Tegra4 counterpart, the Tegra4i also integrates the Icerai500 LTE/HSPA+ baseband processor onto the same die.

Common features:

  • 28 nm HPM semiconductor technology

  • CPU cache: L1: 32KB instruction + 32KB data, L2: 1MB

Modelnumber

CPU

GPU

Memory

Adoption

Processor(Cores/Freq)

Micro-architecture

Core config1

Frequency

Type

Amount

Buswidth

Band-width

Availability

T148?

4+1×2.0GHz Cortex-A9 "R4"

VLIW-based VEC4 units

60(48:12:2)

660MHz

LPDDR3

32-bit single-channel

6.4–7.5GB/s (800–933MHz)

Q1 2014

  1. 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, Explay 4Game, Wiko Wax QMobile Noir LT-250

Tegra K1

Nvidia's Tegra K1 (codenamed "Logan") features ARM Cortex-A15 cores in a 4+1 configuration similar to Tegra4, 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. Nvidia claims that it outperforms both the Xbox 360 and the PS3, whilst consuming significantly less power.

Support Adaptive Scalable Texture Compression.

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

Processor:

Model

CPU

GPU

Memory

Adoption

Processor(Cores/Freq)

Micro-architecture

Coreconfig1

Frequency

GFLOPS(FP32)

Type

Amount

Buswidth

Band-width

Availability

T124

4+1×2.3GHzCortex-A15 R3 (32-bit)

GK20A(Kepler)

192:8:4

756–951MHz

290–365

DDR3L,LPDDR3

max 8GB(with40-bitaddressextension2)

64-bit

17GB/s

Q2 2014

T132

2x2.5GHzDenver(64-bit)

max 8GB

?

?

Q3 2014

  1. 1 Unified Shaders : Texture mapping units : Render output units

  2. 2 ARM Large Physical Page Extension (LPAE) supports 1TiB (240 bytes).

  3. The 8GiB limitation is part-specific.

Devices

Model

Devices

T124

Jetson TK1 development board, Nvidia Shield Tablet, Acer Chromebook 13, HP Chromebook 14 G3, Xiaomi MiPad, Snail Games OBox, UTStarcom MC8718, Google Project Tango tablet, Fuze Tomahawk F1, Apalis TK1 System on Module, JXD Singularity S192

T132

HTC Nexus 9

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. 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

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. It supports Adaptive scalable texture compression (ASTC). 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 A57 cores. The four cores from the A53 cluster cannot be accessed without first powering down the A57 ones (both clusters must be in the CC6 off state). Nvidia has removed the A53 cores from later versions of technical documentation, implying that they may have been removed from the die. 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.

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

TDP:

  • T210: 15W, with average power consumption less than 10W

  • Jetson Nano: 10W (mode 0); mode 1: 5W (only 2 CPU cores @ 918MHz, GPU @ 640MHz)

Modelnumber

SoC/Variant

Process

CPU

GPU

Memory

Adoption

Processor(Cores/Freq1)

Micro-architecture

Frequency(Coreconfig2)

GFLOPS(FP32)

GFLOPS(FP16)

Type

Amount3

Buswidth

Band-width4

Availability

T210

ODNX02-A2 TM670D-A1 TM670M-A2 TM671D-A2

TSMC20nm

4×2.2GHz Cortex-A57 +4×1.3GHz Cortex-A53

GM20B(Maxwell)

1000MHz(256:16:16)

512

1024

LPDDR3LPDDR4

8GB

64-bit

25.6GB/s

Q2 2015

TM660M-A2

4×1.4GHz Cortex-A57 +4×1.0GHz Cortex-A53

921MHz(128:16:16)

236

472

LPDDR3?LPDDR4

4GB

March 2019

T214 /T210b01

ODNX10-A1 TM675M-A1

TSMC 16nm

4×2.1GHz Cortex-A57

GM21B (Maxwell)

1267MHz(256:16:16)

649

1298

LPDDR4LPDDR4X

8GB

34.1GB/s

Q2 2019

  1. 1 CPU frequencymaybeclockeddifferentlythanthemaximumvalidatedbyNvidiaattheOEM'sdiscretion

  2. 2 Unified Shaders : Texture mapping units : Render output units

  3. 3 Maximumvalidatedamountofmemory,implementationisboardspecific

  4. 4 Maximumvalidatedmemorybandwidth,implementationisboardspecific

Devices

Model

SoC / Variant

Devices

T210

ODNX02-A2

Nintendo Switch (2017, HAC-001)

TM670D-A1

Nvidia Shield Android TV (2015)

TM670M-A2

Nvidia Shield Android TV (2017)

TM660M-A2

Jetson Nano 4GB, Jetson Nano 2GB

TM671D-A2

Google Pixel C

TM670D-A2

Nvidia Jetson TX1 development board, 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 (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. The chips are made using FinFET process technology using TSMC's 16nm FinFET+ manufacturing process.

  • CPU: Nvidia Denver2 ARMv8 (64-bit) dual-core + ARMv8 ARM Cortex-A57 quad-core (64-bit)

  • RAM: up to 8GB LPDDR4

  • GPU: Pascal-based, 256 CUDA cores; type: GP10B

  • TSMC 16nm, FinFET process

  • TDP: 7.5–15W

Modelnumber

SoCVariant

CPU

GPU

Memory

Adoption

Processor(Cores/Freq)

Micro-architecture

Frequency(Coreconfig1)

GFLOPS(FP32)

GFLOPS(FP16)

Type

Amount

Buswidth

Band-width

Availability

T186

TegraX2(Parker)

2×1.4–2.0GHzDenver2 +4×1.2–2.0GHzCortex-A57

GP10B(Pascal)

854–1465MHz256:16:16(2)

437–750

874–1500

LPDDR4

8GB

128-bit

59.7 GB/s

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

Devices

Model

Devices

T186

Nvidia Drive PX2 (variants),ZF ProAI 1.1

T186

Nvidia Jetson TX2

Mercedes-Benz MBUX (infotainment system)

1 unit along with 1 GPU semiconductor is part of the ECU for "Tesla vision" functionality in all Tesla vehicles since October 2016

T186

Magic Leap One (mixed environment glasses)

Skydio 2 (drone)

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. 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). It is able to encode and decode 8K Ultra HD (7680×4320). Users can configure operating modes at 10W, 15W, and 30W TDP as needed and the die size is 350mm2. Nvidia confirmed the fabrication process to be 12 nm FinFET at CES 2018.

  • CPU: Nvidia custom Carmel ARMv8.2-A (64-bit), 8 cores 10-wide superscalar

  • GPU: Volta-based, 512 CUDA cores with 1.4 TFLOPS; type: GV11B

  • TSMC 12 nm, FinFET process

20 TOPS DL and 160 SPECint @ 20 W; 30 TOPS DL @ 30 W (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)

  • 1.6 TOPS in the PVA unit (Programmable Vision Accelerator, 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 including 8k video support

  • MIPI-CSI-3 with 16 lanes

  • 1Gbit/s Ethernet

  • 10Gbit/s Ethernet

Module (Model)

SoC Variant

CPU

GPU

Deep Learning

Memory

Adoption

TDP (W)

Processor(Cores/Freq)

Micro-architecture

Frequency(Coreconfig1)

TFLOPS(FP32)

TFLOPS(FP16)

TOPS (INT8)

Type

Amount

Buswidth

Band-width

Availability

Xavier AGX

64GB

Carmel (12MBcache)8x2.2GHz

GV11B (Volta)

1377MHz 512:64 (8, 4, 1)

1.41

2.82

32

LPDDR4X

64 GB

256-bit

136.5 GB/s

Jan 2022

10-30

Xavier AGX

32GB

32 GB

Apr 2020

Xavier AGX

Industrial

Carmel (12MBcache)8x2.0GHz

1221MHz 512:64 (8, 4, 1)

1.24

2.48

30

LPDDR4X

32 GB

256-bit

136.5 GB/s

Jul 2021

20-40

Xavier NX

16GB

Carmel (10MBcache)6x1.9GHz

Volta

1100MHz 384:48 (6, 3, 1)

0.84

1.69

21

LPDDR4X

16 GB

128-bit

59.7 GB/s

Jan 2022

10-20

Xavier NX

8GB

8 GB

May 2020

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

Devices

Model

SoC Variant

Devices

T194

Nvidia Drive Xavier (Drive PX-series)(formerly named Xavier AI Car Supercomputer)

Nvidia Drive Pegasus (Drive PX-series)

Nvidia Drive AGX Xavier Developer Kit

Nvidia Jetson AGX Xavier Developer Kit

Nvidia Jetson Xavier

TE860M-A2

Nvidia Jetson Xavier NX

Nvidia Clara AGX "Clara AGX is based on NVIDIA Xavier and NVIDIA Turing GPUs."

Bosch and Nvidia designed Self Driving System

ZF ProAI

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

  1. The board consists of the P2888 compute module and the P2822 baseboard.

Orin

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

  1. It contains 17 billion transistors and 12 ARM Hercules cores and is capable of 200 INT8 TOPs @ 65W.

  2. 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

  1. and by pairing multiple such chips a wider range of application can be realized with the thus resulting board concepts.

  2. In early 2021, Nvidia announced the Chinese vehicle company NIO will be using an Orin-based chip in their cars.

The so far published specifications for Orin are:

GPU: Ampere-based, 2048 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."

  • 5.3 CUDA TFLOPs (FP32)

  • 10.6 CUDA TFLOPs (FP16)

  • Samsung 8N process (derived from 8LPU)

275 TOPS (INT8) DL

  • 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)

  • 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× 10Gbit/s Ethernet, 1× 1Gbit/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.

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)

SoCVariant

CPU

GPU

DeepLearning

Memory

Adoption

TDP (W)

Processor(Cores×Freq)

Micro-architecture

Frequency(Coreconfig1)

TFLOPS(FP32)

TFLOPS(FP16)

TOPS(INT8)

Type

Amount

Buswidth

Band-width

Availability

OrinAGX 64GB

Cortex-A78AE(9MBcache)12×2.2GHz

Ampere

1300MHz2048:64:8(16, 8, 2)

5.32

10.649

275

LPDDR5

64 GB

256-bit

204.8 GB/s

Sample: 2021, Dev-Kit: Q1 2022, Prod: Dec 2022

15-60

OrinAGX 32GB

Cortex-A78AE(6MBcache)8×2.2GHz

930MHz1792:56:7(14, 7, 2)

3.365

6.73

200

32 GB

Oct 2022

15-40

OrinNX 16GB

TE980-M

Cortex-A78AE(6MBcache)8×2.0GHz

918MHz1024:32:4(8, 4, 1)

1.88

3.76

100

16 GB

128-bit

102.4 GB/s

Dec 2022

10-25

OrinNX 8GB

TE980-M

Cortex-A78AE(5.5MBcache)6×2.0GHz

765MHz1024:32:4(8, 4, 1)

1.57

3.13

70

8 GB

Jan 2023

10-20

OrinNano 8GB

Cortex-A78AE(5.5MBcache)6×1.5GHz

625MHz1024:32:4(8, 4, 1)

1.28

2.56

40

68 GB/s

7-15

OrinNano 4GB

625MHz512:16:2(4, 2, 1)

0.64

1.28

20

4 GB

64-bit

34 GB/s

5-10

Module(Model)

SoCVariant

CPU

GPU

DeepLearning

Memory

Adoption

TDP (W)

Processor(Cores×Freq)

Micro-architecture

Frequency(Coreconfig1)

TFLOPS(FP32)

TFLOPS(FP16)

TOPS(INT8)

Type

Amount

Buswidth

Band-width

Availability

OrinNanoSuper8GB

Cortex-A78AE(5.5MBcache)6×1.7GHz

Ampere

1020MHz1024:32:4(8, 4, 1)

2.09

4.18

67

LPDDR5

8 GB

128-bit

102.4 GB/s

Dec 2024

7-25

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

Devices

Model

Devices

Comments

T234

Nvidia Jetson AGX Orin

comes in 32GB and 64GB RAM configurations, available as standalone module or devkit;intended for industrial robotics and/or embedded HPC applications

Nvidia Jetson Orin NX

mid-power SODIMM-form factor Orin-series module, available only as standalone module; pin-compatible with Xavier NX carrier

Nvidia Jetson Orin Nano

low-power, cost-effective SODIMM-form factor Orin-series module, available as standalone module or devkit; intended for entry-level usage

Nvidia DRIVE AGX Orin

used in automotive ADAS applications. 1×Orin 12×A78AE 32GB LPDDR5 @100W, 167+87 INT8 TOPS

Nio Adam

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, 1536 Ampere CUDA cores, 102.4 GB/s LPDDR5X

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.

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

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).

Modelnumber

CPU

Memory

Adoption

Processor(Cores/Frequency)

Cache

TFLOPS(FP64)

Type

Amount

Buswidth

Band-width

Availability

T241

Grace - 72x ARM Neoverse V2 cores (ARMv9)

L1: 64KB I-cache + 64KB D-cache per coreL2: 1MB per coreL3: 117MB shared

3.551

LPDDR5X ECC

Up to 480GB1

?

500 GB/s

H2 2023

1Figures cut in half from full Grace Superchip specification

Atlan

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

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

Functional units known so far are:

  • Grace Next CPU

  • Ada Lovelace GPU

  • Bluefield DPU (Data Processing Unit)

  • other Accelerators

  • Security Engine

  • Functional Safety Island

  • On-Chip-Memory

  • External Memory Interface(s)

  • High-Speed-IO Interfaces

Modelnumber

CPU

GPU

DeepLearning

Memory

Adoption

Processor(Cores/Freq)

Micro-architecture

Coreconfig1

Freq

GFLOPS(FP32)

GFLOPS(FP16)

TOPS(INT8)

Type

Amount

Buswidth

Band-width

Availability

T254?

Grace-Next(?/?)

AdaLovelace

?

?

?

?

>1000

?

?

?

?

CancelledSept.2022

Thor

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

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

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

Modelnumber

CPU

GPU

Deep Learning

Memory

Adoption

TDP (W)

Processor(Cores/Freq)

Micro-architecture

Coreconfig1

Freq.

TFLOPS(FP32)

TFLOPS(FP16)

TOPS(FP8)

Type

Amount

Buswidth

Band-width

Availability

T264

12x Neoverse V3AE(2.6 GHz)

Blackwell

1536:64:? (12, 6, 2)

1575 MHz

4.838

?

600

LPDDR5X

64 GB

256-bit

273 GB/s

2025

40-70

14×Neoverse V3AE(2.6 GHz)

2560:96:? (20, 10, 3)

8.064

500

1035

128 GB

40-130

Devices

Comparison

Generation

Tegra 2(Ventana)

Tegra 3(Kal-El)

Tegra 4(Wayne)

Tegra 4i(Grey)

Tegra K1 (Logan)

Tegra X1(Erista)

TegraX1+(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

Cores

2× Cortex-A9

4+1× Cortex-A9

4+1× Cortex-A15

4+1× Cortex-A9

4+1× Cortex-A15

2× Denver

4× Cortex-A53+ 4× Cortex-A57

2× Denver2+ 4× Cortex-A57

8× Carmel

12× Cortex-A78AEAE

14× 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)

32/32KB

128/64KB

32/32KB + 64/32KB

128/64KB+ 48/32KB

128/64KB

64/64KB

L2 cache

1MB

2MB

128KB + 2MB

2MB+2MB

8MB

3MB

14MB

L3 cache

N/A

4MB

6MB

16MB

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

RAM

Protocol

DDR2/LPDDR2

DDR3/LPDDR2

DDR3/LPDDR3

LPDDR3/LPDDR4

LPDDR4/LPDDR4X

LPDDR5

LPDDR5X

Max. size

1GB

2GB

4GB

8GB

64GB

128GB

Bandwidth

2.7GB/s

6.4GB/s

7.5GB/s

14.9GB/s

25.6GB/s

34.1GB/s

59.7GB/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, to Tegra 210.

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.

, 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. Nvidia co-founder & CEO laid out the Tegra processor roadmap using Ubuntu Unity in GPU Technology Conference 2013.

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.

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).

QNX

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

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:

See also

References