Nvidia

Nvidia Corporation (/ɛnˈvɪdiə/ en-VID-ee-ə)[note 1] is an American multinational technology company incorporated in Delaware and based in Santa Clara, California.[2] It designs graphics processing units (GPUs) for the gaming and professional markets, as well as system on a chip units (SoCs) for the mobile computing and automotive market. Its primary GPU product line, labeled "GeForce", is in direct competition with Advanced Micro Devices' (AMD) "Radeon" products. Nvidia expanded its presence in the gaming industry with its handheld Shield Portable, Shield Tablet, and Shield Android TV.

For the screen reader known as "NVDA", see NonVisual Desktop Access.

Nvidia Corporation
Public
Traded as
ISINUS67066G1040 
Industry
Predecessor3dfx Interactive 
FoundedApril 5, 1993 (1993-04-05)
Founders
HeadquartersSanta Clara, California, U.S.
Area served
Worldwide
Key people
Products
Revenue US$11.716 billion (2018)[1]
US$3.804 billion (2018)[1]
US$4.141 billion (2018)[1]
Total assets US$13.292 billion (2018)[1]
Total equity US$9.342 billion (2018)[1]
Number of employees
13,227 (January 2019)[1]
SubsidiariesNVIDIA Advanced Rendering Center, Mellanox Technologies
Websitewww.nvidia.com
developer.nvidia.com
www.geforce.com

Since 2014, Nvidia has diversified its business focusing on four markets: gaming, professional visualization, data centers, and auto. Nvidia is also now focused on artificial intelligence.[3]

In addition to GPU manufacturing, Nvidia provides parallel processing capabilities to researchers and scientists that allow them to efficiently run high-performance applications. They are deployed in supercomputing sites around the world.[4][5] More recently, it has moved into the mobile computing market, where it produces Tegra mobile processors for smartphones and tablets as well as vehicle navigation and entertainment systems.[6][7][8] In addition to AMD, its competitors include Intel, Qualcomm, and Arm (e.g., because of Denver, while Nvidia also licenses Arm's designs).

Company history
Aerial view of the new Nvidia headquarters building and surrounding campus and area in Santa Clara, California, in 2017. Apple Park is visible in the distance.

Nvidia was founded on April 5, 1993[9][10][11] by Jensen Huang (CEO as of 2020), a Taiwanese American, previously director of CoreWare at LSI Logic and a microprocessor designer at Advanced Micro Devices (AMD), Chris Malachowsky, an electrical engineer who worked at Sun Microsystems, and Curtis Priem, previously a senior staff engineer and graphics chip designer at Sun Microsystems.

In 1993, the three co-founders believed that the proper direction for the next wave of computing is accelerated or graphics-based computing as this model of computing could solve problems that general-purpose computing fundamentally couldn't. They also observed that video games were simultaneously one of the most computationally challenging problems and would have incredibly high sales volume. The two conditions don't happen very often. Video games became the company's flywheel to reach large markets and funding huge R&D to solve massive computational problems. With only $40,000 in the bank, the company was born.[12] The company subsequently received $20 million of venture capital funding from Sequoia Capital and others.[13] Nvidia initially had no name and the co-founders named all their files NV, as in "next version". The need to incorporate the company prompted the co-founders to review all words with those two letters, leading them to "invidia", the Latin word for "envy".[12] Nvidia went public on January 22, 1999.[14][15][16]

Major releases and acquisitions

The release of the RIVA TNT in 1998 solidified Nvidia's reputation for developing capable graphics adapters. In late 1999, Nvidia released the GeForce 256 (NV10), most notably introducing on-board transformation and lighting (T&L) to consumer-level 3D hardware. Running at 120 MHz and featuring four-pixel pipelines, it implemented advanced video acceleration, motion compensation, and hardware sub-picture alpha blending. The GeForce outperformed existing products by a wide margin.

Due to the success of its products, Nvidia won the contract to develop the graphics hardware for Microsoft's Xbox game console, which earned Nvidia a $200 million advance. However, the project took many of its best engineers away from other projects. In the short term this did not matter, and the GeForce2 GTS shipped in the summer of 2000. In December 2000, Nvidia reached an agreement to acquire the intellectual assets of its one-time rival 3dfx, a pioneer in consumer 3D graphics technology leading the field from mid 1990s until 2000.[17][18] The acquisition process was finalized in April 2002.[19]

In July 2002, Nvidia acquired Exluna for an undisclosed sum. Exluna made software-rendering tools and the personnel were merged into the Cg project.[20] In August 2003, Nvidia acquired MediaQ for approximately US$70 million.[21] On April 22, 2004, Nvidia acquired iReady, also a provider of high performance TCP/IP and iSCSI offload solutions.[22] In December 2004, it was announced that Nvidia would assist Sony with the design of the graphics processor (RSX) in the PlayStation 3 game console. On December 14, 2005, Nvidia acquired ULI Electronics, which at the time supplied third-party southbridge parts for chipsets to ATI, Nvidia's competitor.[23] In March 2006, Nvidia acquired Hybrid Graphics.[24] In December 2006, Nvidia, along with its main rival in the graphics industry AMD (which had acquired ATI), received subpoenas from the U.S. Department of Justice regarding possible antitrust violations in the graphics card industry.[25]

Forbes named Nvidia its Company of the Year for 2007, citing the accomplishments it made during the said period as well as during the previous five years.[26] On January 5, 2007, Nvidia announced that it had completed the acquisition of PortalPlayer, Inc.[27] In February 2008, Nvidia acquired Ageia, developer of the PhysX physics engine and physics processing unit. Nvidia announced that it planned to integrate the PhysX technology into its future GPU products.[28][29]

In November 2011, after initially unveiling it at Mobile World Congress, Nvidia released its Tegra 3 ARM system-on-chip for mobile devices. Nvidia claimed that the chip featured the first-ever quad-core mobile CPU.[30][31] In May 2011, it was announced that Nvidia had agreed to acquire Icera, a baseband chip making company in the UK, for $367 million.[32] In January 2013, Nvidia unveiled the Tegra 4, as well as the Nvidia Shield, an Android-based handheld game console powered by the new system-on-chip.[33] On July 29, 2013, Nvidia announced that they acquired PGI from STMicroelectronics.[34]

On May 6, 2016, Nvidia unveiled the first GeForce 10 series GPUs, the GTX 1080 and 1070, based on the company's new Pascal microarchitecture. Nvidia claimed that both models outperformed its Maxwell-based Titan X model; the models incorporate GDDR5X and GDDR5 memory respectively, and use a 16 nm manufacturing process. The architecture also supports a new hardware feature known as simultaneous multi-projection (SMP), which is designed to improve the quality of multi-monitor and virtual reality rendering.[35][36][37] Laptops that include these GPUs and are sufficiently thin – as of late 2017, under 0.8 inches (20 mm) – have been designated as meeting Nvidia's "Max-Q" design standard.[38]

In July 2016, Nvidia agreed to a settlement for a false advertising lawsuit regarding its GTX 970 model, as the models were unable to use all of their advertised 4 GB of RAM due to limitations brought by the design of its hardware.[39] In May 2017, Nvidia announced a partnership with Toyota Motor Corp. Toyota will use Nvidia's Drive PX-series artificial intelligence platform for its autonomous vehicles.[40] In July 2017, Nvidia and Chinese search giant Baidu, Inc. announced a far-reaching AI partnership that includes cloud computing, autonomous driving, consumer devices, and Baidu's open-source AI framework PaddlePaddle. Baidu unveiled that Nvidia 's Drive PX 2 AI will be the foundation of its autonomous-vehicle platform.[41]

Nvidia officially released the NVIDIA TITAN V on December 7, 2017.[42][43]

Nvidia officially released the Nvidia Quadro GV100 on March 27, 2018.[44] Nvidia officially released RTX 2080GPUs September 27, 2018. In 2018, Google announced that Nvidia's Tesla P4 graphic cards would be integrated into Google Cloud service's artificial intelligence.[45]

On March 11, 2019, Nvidia announced a deal to buy Mellanox Technologies for $6.9 billion[46] to substantially expand its footprint in the high-performance computing market. In May 2019, Nvidia announced new RTX Studio laptops. The creators say that the new laptop is going to be seven times faster than a top-end MacBook Pro with a Core i9 and AMD's Radeon Pro Vega 20 graphics in apps like Maya and RedCine-X Pro.[47] In August 2019, Nvidia announced Minecraft RTX, an official Nvidia-developed patch for the game adding real-time DXR raytracing exclusively to the Windows 10 version of the game. The whole game is, in Nvidia's words, "refit" with path tracing, which dramatically affects the way light, reflections and shadows work inside the engine.[48]

In May 2020, Nvidia's top scientists developed an open-source ventilator in order to address the shortage resulting from the global coronavirus pandemic.[49] On May 14, 2020, Nvidia officially announced their Ampere GPU microarchitecture and the Nvidia A100 GPU accelerator.[50][51] In July 2020, it was reported that Nvidia was in talks with SoftBank to buy Arm, a UK-based chip designer for $32 billion.[52]

Class action lawsuit

In July 2008, Nvidia took a write-down of approximately $200 million on its first-quarter revenue, after reporting that certain mobile chipsets and GPUs produced by the company had "abnormal failure rates" due to manufacturing defects. Nvidia, however, did not reveal the affected products. In September 2008, Nvidia became the subject of a class action lawsuit over the defects, claiming that the faulty GPUs had been incorporated into certain laptop models manufactured by Apple Inc., Dell, and HP. In September 2010, Nvidia reached a settlement, in which it would reimburse owners of the affected laptops for repairs or, in some cases, replacement.[53][54] On January 10, 2011, Nvidia signed a six-year, $1.5 billion cross-licensing agreement with Intel, ending all litigation between the two companies.[55]

Apple/Nvidia web driver controversy

In May 2018, on the Nvidia user forum, a thread was started[56] asking the company to update users when they would release web drivers for its cards installed on legacy Mac Pro machines up to mid-2012 5,1 running the macOS Mojave operating system 10.14. Web drivers are required to enable graphics acceleration and multiple display monitor capabilities of the GPU. On its Mojave update info website, Apple stated that macOS Mojave would run on legacy machines with 'Metal compatible' graphics cards[57] and listed Metal compatible GPUs, including some manufactured by Nvidia.[58] However, this list did not include metal compatible cards that currently work in macOS High Sierra using Nvidia developed web drivers. In September, Nvidia responded, "Apple fully control drivers for Mac OS. But if Apple allows, our engineers are ready and eager to help Apple deliver great drivers for Mac OS 10.14 (Mojave)."[59] In October, Nvidia followed this up with another public announcement, "Apple fully controls drivers for Mac OS. Unfortunately, Nvidia currently cannot release a driver unless it is approved by Apple,"[60] suggesting a possible rift between the two companies.[61] By January 2019, with still no sign of the enabling web drivers, Apple Insider weighed into the controversy with a claim that Apple management "doesn't want Nvidia support in macOS".[62] The following month, Apple Insider followed this up with another claim that Nvidia support was abandoned because of "relational issues in the past",[63] and that Apple was developing its own GPU technology.[64] Without Apple approved Nvidia web drivers, Apple users are faced with replacing their Nvidia cards with a competing supported brand, such as AMD Radeon from the list recommended by Apple.[65]

Finances

For the fiscal year 2018, Nvidia reported earnings of US$3.047 billion, with an annual revenue of US$9.714 billion, an increase of 40.6% over the previous fiscal cycle. Nvidia's shares traded at over $245 per share, and its market capitalization was valued at over US$120.6 billion in September 2018.[66]

Year[66] Revenue
in mil. USD$		 Net income
in mil. USD$		 Total assets
in mil. USD$		 Price per share
in USD$		 Employees
2005 2,010 89 1,629 8.81
2006 2,376 301 1,955 16.76
2007 3,069 449 2,675 25.68
2008 4,098 798 3,748 14.77
2009 3,425 −30 3,351 10.97
2010 3,326 −68 3,586 12.56
2011 3,543 253 4,495 15.63
2012 3,998 581 5,553 12.52
2013 4,280 563 6,412 13.38 5,783
2014 4,130 440 7,251 17.83 6,384
2015 4,682 631 7,201 23.20 6,658
2016 5,010 614 7,370 53.33 6,566
2017 6,910 1,666 9,841 149.38 7,282
2018 9,714 3,047 11,241 245.75 11,528

GPU Technology Conference

NVIDIA's GPU Technology Conference (GTC) is a series of technical conferences held around the world.[67] It originated in 2009 in San Jose, California, with an initial focus on the potential for solving computing challenges through GPUs.[68] In recent years, the conference focus has shifted to various applications of artificial intelligence and deep learning, including: self-driving cars, healthcare, high performance computing, and NVIDIA Deep Learning Institute (DLI) training.[69] GTC 2018 attracted over 8400 attendees.[67] Due to the COVID-19 pandemic in 2020, GTC 2020 was converted to a digital event and drew roughly 59,000 registrants. [70]

Product families
An Nvidia Shield Tablet

Nvidia's family includes primarily graphics, wireless communication, PC processors, and automotive hardware/software. Some families are listed below:

  • GeForce, consumer-oriented graphics processing products
  • Quadro, computer-aided design and digital content creation workstation graphics processing products
  • NVS, multi-display business graphics solution
  • Tegra, a system on a chip series for mobile devices
  • Tesla, dedicated general-purpose GPU for high-end image generation applications in professional and scientific fields
  • nForce, a motherboard chipset created by Nvidia for Intel (Celeron, Pentium and Core 2) and AMD (Athlon and Duron) microprocessors
  • Nvidia Grid, a set of hardware and services by Nvidia for graphics virtualization
  • Nvidia Shield, a range of gaming hardware including the Shield Portable, Shield Tablet and, most recently, the Shield Android TV
  • Nvidia Drive automotive solutions, a range of hardware and software products for assisting car drivers. The Drive PX-series is a high performance computer platform aimed at autonomous driving through deep learning,[71] while Driveworks is an operating system for driverless cars.[72]

Open-source software support
See also: Free and open-source graphics device driver, Mesa 3D, nouveau (software), and OpenPOWER Foundation

Until September 23, 2013, Nvidia had not published any documentation for its hardware,[73] meaning that programmers could not write free and open-source device driver for its products without resorting to (clean room) reverse engineering.

Instead, Nvidia provides its own binary GeForce graphics drivers for X.Org and an open-source library that interfaces with the Linux, FreeBSD or Solaris kernels and the proprietary graphics software. Nvidia also provided but stopped supporting an obfuscated open-source driver that only supports two-dimensional hardware acceleration and ships with the X.Org distribution.[74]

The proprietary nature of Nvidia's drivers has generated dissatisfaction within free-software communities.[75] Some Linux and BSD users insist on using only open-source drivers and regard Nvidia's insistence on providing nothing more than a binary-only driver as inadequate, given that competing manufacturers such as Intel offer support and documentation for open-source developers and that others (like AMD) release partial documentation and provide some active development.[76][77]

Because of the closed nature of the drivers, Nvidia video cards cannot deliver adequate features on some platforms and architectures given that the company only provides x86/x64 and ARMv7-A driver builds.[78] As a result, support for 3D graphics acceleration in Linux on PowerPC does not exist, nor does support for Linux on the hypervisor-restricted PlayStation 3 console.

Some users claim that Nvidia's Linux drivers impose artificial restrictions, like limiting the number of monitors that can be used at the same time, but the company has not commented on these accusations.[79]

In 2014, with Maxwell GPUs, Nvidia started to require firmware by them to unlock all features of its graphics cards. Up to now this state did not change and makes writing open-source drivers difficult.[80][81][82]

Deep learning

Nvidia GPUs are used in deep learning, artificial intelligence, and accelerated analytics. The company developed GPU-based deep learning in order to use artificial intelligence to approach problems like cancer detection, weather prediction, and self-driving vehicles.[83] They are included in all Tesla vehicles.[84] The purpose is to help networks learn to “think”.[85] According to TechRepublic, Nvidia GPUs "work well for deep learning tasks because they are designed for parallel computing and do well to handle the vector and matrix operations that are prevalent in deep learning".[86] These GPUs are used by researchers, laboratories, tech companies and enterprise companies.[87] In 2009, Nvidia was involved in what was called the "big bang" of deep learning, "as deep-learning neural networks were combined with Nvidia graphics processing units (GPUs)".[88] That year, the Google Brain used Nvidia GPUs to create Deep Neural Networks capable of machine learning, where Andrew Ng determined that GPUs could increase the speed of deep-learning systems by about 100 times.[89]

DGX

In April 2016, Nvidia produced the DGX-1 supercomputer based on an 8 GPU cluster, to improve the ability of users to use deep learning by combining GPUs with integrated deep learning software.[90] It also developed Nvidia Tesla K80 and P100 GPU-based virtual machines, which are available through Google Cloud, which Google installed in November 2016.[91] Microsoft added GPU servers in a preview offering of its N series based on Nvidia's Tesla K80s, each containing 4992 processing cores. Later that year, AWS's P2 instance was produced using up to 16 Nvidia Tesla K80 GPUs. That month Nvidia also partnered with IBM to create a software kit that boosts the AI capabilities of Watson,[92] called IBM PowerAI.[93][94] Nvidia also offers its own NVIDIA Deep Learning software development kit.[95] In 2017, the GPUs were also brought online at the RIKEN Center for Advanced Intelligence Project for Fujitsu.[96] The company's deep learning technology led to a boost in its 2017 earnings.[97]

In May 2018, researchers at the artificial intelligence department of Nvidia realized the possibility that a robot can learn to perform a job simply by observing the person doing the same job. They have created a system that, after a short revision and testing, can already be used to control the universal robots of the next generation. In addition to GPU manufacturing, Nvidia provides parallel processing capabilities to researchers and scientists that allow them to efficiently run high-performance applications.[98]

Inception Program

Nvidia's Inception Program was created to support startups making exceptional advances in the fields of AI and Data Science. Award winners are announced at Nvidia's GTC Conference. There are currently 2,800 startups in the Inception Program.[99]

2018 winners

Source:[100]

  • Subtle Medical (healthcare)
  • AiFi (enterprise)
  • Kinema Systems (autonomous vehicles)

2017 winners

Source:[100]

  • Genetesis (social innovation)
  • Athelas (hottest emerging)
  • Deep Instinct(most disruptive)
gollark: Also, there are no solutions for "using the items already in the game" for chunkloading.
gollark: Because furnaces are actually an interesting feature.
gollark: Cleverness? How is there cleverness in using resources to make a chunkloader...?
gollark: If we had infinite processing power on all servers, I expect that chunkloading wouldn't exist. Unfortunately we don't so it does, and it seems stupid to spend resources on things to get around, well, unintended features.
gollark: Sure, I don't see why not.

See also

References
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