||It has been suggested that Vibrante be merged into this article. (Discuss) Proposed since February 2017.|
Headquarters at Santa Clara in 2008
|Headquarters||Santa Clara, California, U.S.|
|Revenue||US$6.91 billion (2016) |
Number of employees
|10,000 (January 2017)|
|Subsidiaries||NVIDIA Advanced Rendering Center|
Nvidia Corporation (// in-VID-eeə) (most commonly referred to as Nvidia, stylized as NVIDIA, nVIDIA or nvidia) is an American technology company based in Santa Clara, California. 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.
Since 2014, Nvidia has shifted to become a platform company focused on four markets – gaming, professional visualization, data centers and auto.
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. 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. In addition to AMD, its competitors include Intel, Qualcomm and ARM (e.g., because of Denver, while Nvidia also licenses ARM's designs).
Founders and initial investment
- Jensen Huang (CEO as of 2017), a Taiwanese-born 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
- Curtis Priem, previously a senior staff engineer and graphics chip designer at Sun Microsystems
Major releases and acquisitions
||This section may be too long and excessively detailed. (December 2016)|
RIVA TNT in 1998 solidified Nvidia's reputation for capable hardware.
Late 1999 saw the release of the GeForce (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 drew the time of 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. The acquisition process was finalized in April 2002.
In July 2002, Nvidia acquired Exluna for an undisclosed sum. Exluna made software rendering tools and the personnel were merged into the Cg project.
In August 2003, Nvidia acquired MediaQ for approximately US$70 million.
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. In March 2006, it emerged that Nvidia would deliver RSX to Sony as an IP core, and that Sony alone would organize the manufacture of the RSX. Under the agreement, Nvidia would provide ongoing support to port the RSX to Sony's fabs of choice (Sony and Toshiba), as well as die shrinks to 65 nm. This practice contrasted with its business arrangement with Microsoft, in which Nvidia managed production and delivery of the Xbox GPU through its usual third-party foundry contracts. Meanwhile, in May 2005 Microsoft chose to license a design by ATI and to make its own manufacturing arrangements for the Xbox 360 graphics hardware, as had Nintendo for the Wii console (which succeeded the ATI-based Nintendo GameCube).
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.
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.
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.
On January 10, 2011, Nvidia signed a six-year, $1.5 billion cross-licensing agreement with Intel, ending all litigation between the two companies.
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.
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.
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.
GPU Technology Conference
The GPU Technology Conference is an annual technical conference started by Nvidia in 2009 which focuses on using the GPU to solve computing challenges. In 2015, the conference attracted over 4000 attendees.
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, while Driveworks is an operating system for driverless cars.
Open-source software support
Until September 23, 2013, Nvidia had not published any documentation for its hardware, meaning that programmers could not write appropriate and effective 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 a thin 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.
The proprietary nature of Nvidia's drivers has generated dissatisfaction within free-software communities. 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 wholly inadequate, given that competing manufacturers (like Intel) offer support and documentation for open-source developers, and that others (like AMD) release partial documentation and provide some active development.
Because of the closed nature of the drivers, Nvidia video cards cannot deliver adequate features on some platforms and architectures given that it only provides x86/x64 driver builds. 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.
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. They are included in all Tesla vehicles. The purpose is to help networks learn to “think”. 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.” These GPUs are used by researchers, laboratories, tech companies and enterprise companies. 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).” 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.
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. It also developed Nvidia Tesla K80 and P100 GPU-based virtual machines, which are available through Google Cloud, which Google installed in November 2016. 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, called IBM PowerAI. Nvidia also offers its own NVIDIA Deep Learning software development kit.  In 2017 the GPUs were also brought online at the RIKEN Center for Advanced Intelligence Project for Fujitsu. The company’s deep learning technology led to a boost in its 2017 earnings.
- Fast approximate anti-aliasing
- General-purpose computing on graphics processing units
- Graphics processing unit
- List of Nvidia 3D Vision Ready games
- List of Nvidia graphics processing units
- Molecular modeling on GPUs
- Nvidia demos
- Nvidia Ion
- Nvidia Shadowplay
- Project Denver
- Shield Android TV
- Shield Portable
- Shield Tablet
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Board of Directors Initiates Cost-Cutting Measures, Recommends to Shareholders Sale of Company Assets to NVIDIA Corporation for $112 million and Dissolution of Company
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