Nvidia Drive

Last updated

Nvidia Drive is a computer platform by Nvidia, aimed at providing autonomous car and driver assistance functionality powered by deep learning. [1] [2] The platform was introduced at the Consumer Electronics Show (CES) in Las Vegas in January 2015. [3] An enhanced version, the Drive PX 2 was introduced at CES a year later, in January 2016. [4]

Contents

The closely platform related software release program at some point in time was branded NVIDIA DRIVE Hyperion along with a revision number helping to match with the generation of hardware it is created for - and also creating ready to order bundles under those term. In former times there were only the terms Nvidia Drive SDK for the developer package and sub-included Nvidia Drive OS for the system software (aka OS) that came with the evaluation platforms or could be downloaded for OS switching and updating later on.

Hardware and semiconductors

Maxwell based

The first of Nvidia's autonomous chips was announced at CES 2015, based on the Maxwell GPU microarchitecture. [5] The line-up consisted of two platforms:

Drive CX

The Drive CX was based on a single Tegra X1 SoC (System on a Chip) and was marketed as a digital cockpit computer, providing a rich dashboard, navigation and multimedia experience. Early Nvidia press releases reported that the Drive CX board will be capable of carrying either a Tegra K1 or a Tegra X1. [6]

Drive PX

Drive PX NVIDIA Drive PX, Computex Taipei 20150601.jpg
Drive PX

The first version of Drive PX is based on two Tegra X1 SoCs, and was an initial development platform targeted at (semi-)autonomous driving cars.

Pascal based

Drive PX platforms based on the Pascal GPU microarchitecture were first announced at CES 2016. [7] This time only a new version of Drive PX was announced, but in multiple configurations.

Drive PX 2

The Nvidia Drive PX 2 is based on one or two Tegra X2 SoCs where each SoC contains 2 Denver cores, 4 ARM A57 cores and a GPU from the Pascal generation. [8] There are two real world board configurations:

  • for AutoCruise: 1× Tegra X2 + 1 Pascal GPU
  • for AutoChauffeur: 2× Tegra X2 + 2 Pascal GPU's

There is further the proposal from Nvidia for fully autonomous driving by means of combining multiple items of the AutoChauffeur board variant and connecting these boards using e.g. UART, CAN, LIN, FlexRay, USB, 1 Gbit Ethernet or 10 Gbit Ethernet. For any derived custom PCB design the option of linking the Tegra X2 Processors via some PCIe bus bridge is further available, according to board block diagrams that can be found on the web.

All Tesla Motors vehicles manufactured from mid-October 2016 include a Drive PX 2, which will be used for neural net processing to enable Enhanced Autopilot and full self-driving functionality. [9] Other applications are Roborace. [10] Disassembling the Nvidia-based control unit from a recent Tesla car showed that a Tesla was using a modified single-chip Drive PX 2 AutoCruise, with a GP106 GPU added as a MXM Module. The chip markings gave strong hints for the Tegra X2 Parker as the CPU SoC. [11] [12]

Volta based

Systems based on the Volta GPU microarchitecture were first announced at CES 2017 [13]

Drive PX Xavier

The first Volta based Drive PX system was announced at CES 2017 as the Xavier AI Car Supercomputer. [13] It was re-presented at CES 2018 as Drive PX Xavier. [14] [15] Initial reports of the Xavier SoC suggested a single chip with similar processing power to the Drive PX 2 Autochauffeur system. [16] However, in 2017 the performance of the Xavier-based system was later revised upward, to 50% greater than Drive PX 2 Autochauffeur system. [13] Drive PX Xavier is supposed to deliver 30 INT8 TOPS of performance while consuming only 30 watts of power. [17] This spreads across two distinct units, the iGPU with 20 INT8 TOPS as published early and the somewhat later on announced, newly introduced DLA that provided an additional 10 INT8 TOPS.

Drive PX Pegasus

In October 2017 Nvidia and partner development companies announced the Drive PX Pegasus system, based upon two Xavier CPU/GPU devices and two post-Volta (Turing) generation GPUs. The companies stated the third generation Drive PX system would be capable of Level 5 autonomous driving, with a total of 320 INT8 TOPS of AI computational power and a 500 Watts TDP. [18] [19]

Ampere based

Drive AGX Orin

The Drive AGX Orin board family was announced on December 18, 2019, at GTC China 2019. [20] On May 14, 2020, Nvidia announced that Orin would be utilizing the new Ampere GPU microarchitecture and would begin sampling for manufacturers in 2021 and be available for production in 2022. [21] Follow up variants are expected to be further equipped with chip models and/or modules from the Tegra Orin SoC.

Ada Lovelace based

DRIVE Atlan (Cancelled)

Nvidia announced the SoC codenamed Atlan on April 12, 2021 at GTC 2021. [22]

Nvidia announced the cancellation of Atlan on September 20, 2022, which was supposed to be equipped with a Grace-Next CPU, and an Ada Lovelace based GPU, and Nvidia announced that their next SoC was called Thor. [23]

Blackwell based

DRIVE Thor

Announced on September 20, 2022, [24] Nvidia DRIVE Thor comes equipped with an Arm Neoverse V3AE CPU, [25] and a Blackwell based GPU, which was announced on March 18, 2024. [26] It features 8-bit floating point support (FP8) and delivers 1000 INT8 TOPS, 1000 FP8 FLOPS or 500 FP16 TFLOPS of performance. [27] Two Thor SoCs can be connected via NVLink-C2C. [24]

BYD, Hyper, XPENG, Li Auto and ZEEKR have said to be use DRIVE Thor in their vehicles. [28]

Software and bundling

With the label Hyperion [29] added to their reference platform [30] series Nvidia promotes their mass products so that others can easily test drive and then create their own automotive grade products on top. Especially the feature rich software part of the base system is meant to be a big help for these others to quickly go ahead into developing their application specific solutions. Third-party companies, such as DeepRoute.ai, have publicly indicated using these software platform as their base of choice. [31] The whole design is concentrating on UNIX/Posix compatible or derived runtime environments (Linux, [32] Android, [33] QNX - aka the Drive OS variants) with special support for the semiconductors mentioned before in form of internal (CUDA, Vulkan) and external support (special interfaces and drivers for camera, lidar, CAN and many more) of the respective reference boards. For clearness Nvidia bundles the core of the developer needed software as Drive SDK that is sub-divided into DRIVE OS, DriveWorks, DRIVE AV, and DRIVE IX components. [34]

Hyperion
Version		AnnouncedLatest
Chip Launch		Start of
Road Usage		Target Use CaseSemiconductorsReference Platforms / Developer KitsDrive OS VersionSensor Support
7.1 [35] 2020Level 2+ autonomous drivingXavier, Turing GPUDRIVE AGX Xavier Developer Kit,
DRIVE AGX Pegasus Developer Kit		vehicle external: 7x camera, 8x radar;
vehicle internal: 1x camera
8 [36] [32] 2020Xavier, Turing GPUDRIVE™ AGX Pegasus GV100,
DRIVE™ AGX Xavier		5.0.13.2 (linux)vehicle external: 12x camera, 9x radar, 1x lidar
8.1 [37] 2022estimated for 2024Orin, Xavier, Turing GPUNVIDIA DRIVE AGX Orin™,
DRIVE AGX Pegasus,
DRIVE Hyperion 8.1 Developer Kits [38] 		Orin: 6.0 (latest: 6.0.4)
Xavier/Pegasus:5.2.6 [34] 		vehicle external: 12x camera, 9x radar, 1x lidar
9 [39] [40] March 20222024estimated for 2026Atlan (Cancelled)vehicle external: 14x camera, 9x radar, 3x lidar, 20x ultrasonic;
vehicle internal: 3x camera, 1x radar

Note: As of now the above table is still 'fresh' and thus might be incomplete.

Reference board comparison

Nvidia provided
reference board		Drive CXDrive PXDrive PX 2

(AutoCruise)

Drive PX 2

(Tesla)

Drive PX 2

(AutoChauffeur)

Drive PX 2

(Tesla 2.5)

Drive PX Xavier [15] Drive PX Pegasus [18] Drive AGX Orin [20] Drive AGX Pegasus OA [41] Drive Atlan (Cancelled)Drive Thor
GPU Microarchitecture Maxwell (28 nm) Pascal (16 nm) Volta (12 nm) Ampere (8 nm [42] ) Ada Lovelace (TSMC 4N) Blackwell (TSMC 4NP [43] )
AnnouncedJanuary 2015September 2016 [44] October 2016 [45] January 2016August 2017 [46] January 2017October 2017December 2019April 2021 [47] September 2022 [48]
LaunchedN/AN/AN/AN/AN/AN/AN/A2022 [49] Cancelled [23] 2025 [48]
Chips1x Tegra X12x Tegra X11x Tegra X2 (Parker)

+ 1x Pascal GPU

2x Tegra X2 (Parker)

+ 2x Pascal GPU

2x Tegra X2 (Parker)

+ 1x Pascal GPU [50]

1x Tegra Xavier [51] 2x Tegra Xavier

+ 2x Turing GPU

2x Tegra Orin2x Tegra Orin

+ 2x Ampere GPU

?x Grace-Next CPU [47]

+ ?x Ada Lovelace GPU [23]

?x Arm Neoverse Poseidon AE CPU [52]

+ ?x Blackwell GPU [53]

CPU4x Cortex A57

4x Cortex A53

8x Cortex A57

8x Cortex A53

2x Denver

4x Cortex A57

4x Denver

8x Cortex A57

4x Denver

8x Cortex A57

8x Carmel ARM64 [51] 16x Carmel ARM64 12x Cortex A78AE24x Cortex A78AE?x Grace-Next [47] ?x Arm Neoverse Poseidon AE [54]
GPU2 SMM Maxwell

256 CUDA cores

4 SMM Maxwell

512 CUDA cores

1x Parker GPGPU

(1x 2 SM Pascal,
256 CUDA cores)

1x Parker GPGPU

(1x 2 SM Pascal,
256 CUDA cores
on a MXM slot [11] )

2x Parker GPGPU

(2x 2 SM Pascal,
512 CUDA cores)
+ 2x dedicated MXM modules [55]

1x Parker GPGPU

1x 2 SM Pascal,
256 CUDA cores [46] [50]

1x Volta iGPU

(512 CUDA cores) [51]

2x Volta iGPU

(512 CUDA cores)
2x Turing dGPUs
(? CUDA cores)

2x Ampere iGPU

(?CUDA cores)

2x Ampere iGPU

(? CUDA cores)
2x Ampere dGPU
(? CUDA cores)

?x Ada Lovelace [23] ?x Blackwell GPU [56]
Accelerator1x DLA

1x PVA [51]

2x DLA

2x PVA

2x DLA

2x PVA

2x DLA

2x PVA

??
Memory8 GB LPDDR4 [57] 16 GB LPDDR4 [57] 16 GB LPDDR4 [51] 32 GB LPDDR5??
Storage64 GB eMMC [57] 128 GB eMMC [57] ??
Performance4 FP32 TFLOPS

10-12 DL TOPS [58] [59]

4 FP32 TFLOPS

10-12 DL TOPS [58] [59]

16 FP16 TFLOPS

8 FP32 TFLOPS

20-24 DL TOPS [58] [59]

4 FP32 TFLOPS

10-12 DL TOPS [58] [59]

20 INT8 TOPS, 1.3 FP32 TFLOPS (GPU)
10 INT8 TOPS, 5 FP16 TFLOPS (DLA) [51] 		320 INT8 TOPS (total) [60] 400 INT8 TOPS (total)2000 INT8 TOPS (total)1000 INT8 TOPS [23] 2000 FP8 TOPS [48]
TDP20 W [59] 40 W

SoC portion: 10 W [44]

40 W

SoC portion: 10 W [44]

80 W [61] [62] [59] [63]

SoC portion: 20 W [44]

60 W [61] [62] [59]

SoC portion: 20 W [44]

30 W [51] 500 W [60] 130 W750 W??

Note: dGPU and memory are stand-alone semiconductors; all other components, especially ARM cores, iGPU and DLA are integrated components of the listed main computing device(s)

Related Research Articles

<span class="mw-page-title-main">Nvidia</span> American multinational technology company

Nvidia Corporation is an American multinational corporation and technology company headquartered in Santa Clara, California, and incorporated in Delaware. Founded in 1993 by Jensen Huang, Chris Malachowsky, and Curtis Priem, it is a software and fabless company which designs and supplies graphics processing units (GPUs), application programming interfaces (APIs) for data science and high-performance computing, as well as system on a chip units (SoCs) for mobile computing and the automotive market. Nvidia is also a dominant supplier of artificial intelligence (AI) hardware and software.

<span class="mw-page-title-main">Free and open-source graphics device driver</span> Software that controls computer-graphics hardware

A free and open-source graphics device driver is a software stack which controls computer-graphics hardware and supports graphics-rendering application programming interfaces (APIs) and is released under a free and open-source software license. Graphics device drivers are written for specific hardware to work within a specific operating system kernel and to support a range of APIs used by applications to access the graphics hardware. They may also control output to the display if the display driver is part of the graphics hardware. Most free and open-source graphics device drivers are developed by the Mesa project. The driver is made up of a compiler, a rendering API, and software which manages access to the graphics hardware.

<span class="mw-page-title-main">Tegra</span> System on a chip by Nvidia

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 within e.g. robots or drones, and for various smart high level automation purposes.

Atlan may refer to:

Momenta Global Limited is a developer of intelligent driving technologies, based in Beijing and Suzhou, China.

Project Denver is the codename of a central processing unit designed by Nvidia that implements the ARMv8-A 64/32-bit instruction sets using a combination of simple hardware decoder and software-based binary translation where "Denver's binary translation layer runs in software, at a lower level than the operating system, and stores commonly accessed, already optimized code sequences in a 128 MB cache stored in main memory". Denver is a very wide in-order superscalar pipeline. Its design makes it suitable for integration with other SIPs cores into one die constituting a system on a chip (SoC).

<span class="mw-page-title-main">Mobileye</span> Israeli information technology company

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Nvidia Tesla is the former name for a line of products developed by Nvidia targeted at stream processing or general-purpose graphics processing units (GPGPU), named after pioneering electrical engineer Nikola Tesla. Its products began using GPUs from the G80 series, and have continued to accompany the release of new chips. They are programmable using the CUDA or OpenCL APIs.

<span class="mw-page-title-main">Volta (microarchitecture)</span> GPU microarchitecture by Nvidia

Volta is the codename, but not the trademark, for a GPU microarchitecture developed by Nvidia, succeeding Pascal. It was first announced on a roadmap in March 2013, although the first product was not announced until May 2017. The architecture is named after 18th–19th century Italian chemist and physicist Alessandro Volta. It was Nvidia's first chip to feature Tensor Cores, specially designed cores that have superior deep learning performance over regular CUDA cores. The architecture is produced with TSMC's 12 nm FinFET process. The Ampere microarchitecture is the successor to Volta.

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<span class="mw-page-title-main">SXM (socket)</span> High performance computing socket

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References

  1. ↑ Umar Zakir Abdul, Hamid; et al. (2016). "Current Collision Mitigation Technologies for Advanced Driver Assistance Systems–A Survey". PERINTIS eJournal. 6 (2). Retrieved 14 June 2017.
  2. ↑ NVIDIA DRIVE
  3. ↑ "Cars drive autonomously with Nvidia X1-based computer". CNET. CNET. 5 January 2015. Retrieved 29 March 2016.
  4. ↑ "Nvidia Announces Another Car 'Supercomputer' at CES". The Wall Street Journal. 4 January 2016. Retrieved 29 March 2016.
  5. ↑ Smith, Joshua Ho, Ryan. "NVIDIA Tegra X1 Preview & Architecture Analysis" . Retrieved 2016-09-18.{{cite web}}: CS1 maint: multiple names: authors list (link)
  6. ↑ NVIDIA ebnet den Weg für die Autos von Morgen mit den NVIDIA-DRIVE-Automotive-Computern
  7. ↑ Smith, Ryan. "NVIDIA Announces DRIVE PX 2 – Pascal Power For Self-Driving Cars" . Retrieved 2016-09-18.
  8. ↑ "Autonomous Car Development Platform from NVIDIA DRIVE PX2". www.nvidia.com. Retrieved 2016-09-18.
  9. ↑ Lambert, Fred (21 October 2016). "All new Teslas are equipped with NVIDIA's new Drive PX 2 AI platform for self-driving". Electrek. Retrieved 25 January 2017.
  10. ↑ Dow, Jameson (20 May 2017). "Roborace debuts their driverless "Robocar" on track at the Paris ePrix". Electrek. Retrieved 21 May 2017.
  11. 1 2 Look inside Tesla’s onboard Nvidia supercomputer for self-driving
  12. ↑ Why Tesla’s Nvidia Supercomputer for Self-Driving is not as Powerful as Expected
  13. 1 2 3 Cutress, Ian; Tallis, Billy (4 January 2016). "CES 2017: Nvidia Keynote Liveblog". Anandtech.com. Retrieved 9 January 2017.
  14. ↑ Baldwin, Roberto (8 January 2018). "NVIDIA unveils its powerful Xavier SOC for self-driving cars". Engadget. Retrieved 8 January 2018.
  15. 1 2 Autonomous Car Development Platform from NVIDIA DRIVE PX2
  16. ↑ Smith, Ryan (28 September 2016). "Nvidia Teases Xavier, A High Performance SoC for Drive PX & AI". Anandtech. Retrieved 22 June 2017.
  17. ↑ "Autonomous Car Development Platform from NVIDIA DRIVE PX2". NVIDIA. Retrieved 2017-12-01.
  18. 1 2 Oh, Nate (October 10, 2017). "NVIDIA Announces Drive PX Pegasus at GTC Europe 2017: Level 5 Self-Driving Hardware, Feat. Post-Volta GPUs". AnandTech. Retrieved 2017-10-10.
  19. ↑ Auchard, Eric (10 October 2017). "NVIDIA unveils next-generation platform for fully autonomous cars". Reuters. Archived from the original on Oct 18, 2017. Retrieved 17 October 2017.
  20. 1 2 Smith, Ryan (December 18, 2019). "NVIDIA Details DRIVE AGX Orin: A Herculean Arm Automotive SoC For 2022". AnandTech. Retrieved 2019-12-21.
  21. ↑ Eric Abent (May 14, 2020). "NVIDIA Drive upshifts to Ampere GPUs for a smoother self-driving roadmap". Slash Gear.
  22. ↑ Tomazin, Tom (12 April 2021). "A Data Center on Wheels: NVIDIA Unveils DRIVE Atlan Autonomous Vehicle Platform". NVIDIA. Retrieved 18 March 2024.
  23. 1 2 3 4 5 Smith, Ryan (20 September 2022). "NVIDIA Drops DRIVE Atlan SoC, Introduces 2 PFLOPS DRIVE Thor for 2025 Autos". Anandtech. Retrieved 18 March 2024.
  24. 1 2 Kani, Ali (20 September 2022). "DRIVE Thor Unites AV and Cockpit on a Single SoC". NVIDIA. Retrieved 6 January 2023.
  25. ↑ Kani, Ali (20 September 2022). "DRIVE Thor Unites AV and Cockpit on a Single SoC". NVIDIA. Retrieved 6 January 2023.
  26. ↑ Labrie, Marie (18 March 2024). "NVIDIA DRIVE Powers Next Generation of Transportation — From Cars and Trucks to Robotaxis and Autonomous Delivery Vehicles". NVIDIA. Retrieved 18 March 2024.
  27. ↑ "NVIDIA DRIVE In-Vehicle Computing for Autonomous Vehicles". NVIDIA. Retrieved 2024-06-05.
  28. ↑ Shapiro, Danny (2024-03-18). "All Eyes on AI: Automotive Tech on Full Display at GTC 2024". NVIDIA Blog. Retrieved 2024-06-05.
  29. ↑ "Drive-faq". 3 November 2021.
  30. ↑ presentation from December 2019: https://on-demand.gputechconf.com/gtc-cn/2019/pdf/CN9618/presentation.pdf
  31. ↑ "DeepRoute.ai to Integrate NVIDIA DRIVE Hyperion into L4 Autonomous Driving Solutions". 22 March 2022.
  32. 1 2 "Nvidia Drive Archives". 27 July 2017.
  33. ↑ "Android installation on DRIVE AGX". 3 September 2021.
  34. 1 2 "Nvidia Drive SDK". 20 February 2019.
  35. ↑ "NVIDIA DRIVE Hyperion 7.1". 10 March 2022.
  36. ↑ "Nvidia Drive Hyperion 9: Plattform für autonomes Fahren mit Atlan startet 2026". 22 March 2022.
  37. ↑ "Nvidia Drive Hyperion 9: Plattform für autonomes Fahren mit Atlan startet 2026". 22 March 2022.
  38. ↑ "DRIVE Hyperion Autonomous Vehicle Development Platform". 31 January 2019.
  39. ↑ "Nvidia Drive Hyperion 9: Plattform für autonomes Fahren mit Atlan startet 2026". 22 March 2022.
  40. ↑ "NVIDIA Unveils Next-Gen DRIVE Hyperion Autonomous Vehicle Platform". 24 March 2022.
  41. ↑ "DRIVE AGX Pegasus OA Developer Kit". NVIDIA Developer. 2022-05-26. Retrieved 2022-05-26.
  42. ↑ Kennedy, Patrick (23 August 2022). "NVIDIA Orin Brings Arm and Ampere to the Edge at Hot Chips 34". ServeTheHome. Retrieved 6 January 2023.
  43. ↑ Uchiyama, Kristin (18 March 2024). "NVIDIA Blackwell Platform Arrives to Power a New Era of Computing". NVIDIA. Retrieved 18 March 2024.
  44. 1 2 3 4 5 Nvidia unveils palm-sized single SoC version of the DRIVE PX2
  45. ↑ "All Tesla Cars Being Produced Now Have Full Self-Driving Hardware". www.tesla.com. Retrieved 2017-12-01.
  46. 1 2 "Tesla has a new Autopilot '2.5' hardware suite with more computing power for autonomous driving". Electrek. 2017-08-09. Retrieved 2018-10-26.
  47. 1 2 3 Labrie, Marie. "NVIDIA Unveils NVIDIA DRIVE Atlan, an AI Data Center on Wheels for Next-Gen Autonomous Vehicles". nvidianews.nvidia.com. NVIDIA. Retrieved 6 January 2023.
  48. 1 2 3 Labrie, Marie. "NVIDIA Unveils DRIVE Thor — Centralized Car Computer Unifying Cluster, Infotainment, Automated Driving, and Parking in a Single, Cost-Saving System". NVIDIA. Retrieved 6 January 2023.
  49. ↑ Abuelsamid, Sam. "Nvidia Launches 1,000 TOPS Automated Driving Chip, Volvo To Launch Orin-Powered System In 2022". Forbes. Retrieved 2021-09-10.
  50. 1 2 "First look at Tesla's latest Autopilot (2.5) computer in Model 3, S, and X vehicles". Electrek. 2018-03-28. Retrieved 2018-10-26.
  51. 1 2 3 4 5 6 7 NVIDIA Xavier SOC Is The Most Biggest and Complex SOC To Date
  52. ↑ Kani, Ali (20 September 2022). "DRIVE Thor Unites AV and Cockpit on a Single SoC". NVIDIA. Retrieved 6 January 2023.
  53. ↑ Labrie, Marie (18 March 2024). "NVIDIA DRIVE Powers Next Generation of Transportation — From Cars and Trucks to Robotaxis and Autonomous Delivery Vehicles". NVIDIA. Retrieved 18 March 2024.
  54. ↑ Kani, Ali (20 September 2022). "DRIVE Thor Unites AV and Cockpit on a Single SoC". NVIDIA. Retrieved 6 January 2023.
  55. ↑ NVIDIA Announces Pascal GPU Powered Drive PX 2 – 16nm FinFET Based, Liquid Cooled AI Supercomputer With 8 TFLOPs Performance
  56. ↑ Labrie, Marie (18 March 2024). "NVIDIA DRIVE Powers Next Generation of Transportation — From Cars and Trucks to Robotaxis and Autonomous Delivery Vehicles". NVIDIA. Retrieved 18 March 2024.
  57. 1 2 3 4 "Hardware". NVIDIA Developer. 2017-03-30. Retrieved 2017-12-01.
  58. 1 2 3 4 Ho, Joshua. "Hot Chips 2016: NVIDIA Discloses Tegra Parker Details" . Retrieved 2018-10-26.
  59. 1 2 3 4 5 6 7 Pirzada, Usman (2016-04-05). "Nvidia Drive PX 2 Uses Integrated and Discrete Pascal GPU Cores - 24 DL TOPS, 8 TFLOPs and Up To 4GB GDDR5 [Updated]". Wccftech. Retrieved 2018-10-26.
  60. 1 2 "Nvidia AI and multi-petaOps chips for class 5 automated cars within 4 years - NextBigFuture.com". NextBigFuture.com. 2017-10-27. Retrieved 2018-10-26.
  61. 1 2 Oberman, Stuart (October 2017). "Nvidia GPU computing: a journey from PC gaming to deep learning" (PDF). Stanford University Colloquium on Computer Systems EE380. Archived (PDF) from the original on Sep 26, 2023.
  62. 1 2 SteveNV (19 April 2017). "Thermal Design Power". NVIDIA Developer Forums. Archived from the original on Nov 19, 2018. Retrieved 2018-10-26.
  63. ↑ Altavilla, Dave (Sep 28, 2016). "NVIDIA Doubles Down On Self-Driving Cars With Xavier AI Chip And A Hat Tip To Next Gen Volta GPU" . Forbes. Archived from the original on Sep 29, 2016. Retrieved 2018-10-26.
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