How Nvidia Becomes One of Most Popular Company

Nvidia Graphics


Nvidia was founded by Jensen Huang, Chris Malachowsky & Curtis Priem in April-1993. It is an American technology company incorporated in Delaware and 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. Nvidia is also now focused on artificial intelligence.In addition to GPU manufacturing, Nvidia provides parallel processing capabilities to researchers and scientists that allow them to efficiently run high-performance applications.

Graphics Card



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. In the early 1990s, the three co-founders hypothesized that the proper direction for the next wave of computing would be accelerated or graphics based. They believed that this model of computing could solve problems that general-purpose computing fundamentally couldn’t. They also observed that video games were some of the most computationally challenging problems, but would have incredibly high sales volume. With a capital of $40,000, the company was born. The company 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”. 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. 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. On April 22, 2004, Nvidia acquired iReady, also a provider of high performance TCP/IP and iSCSI offload solutions. 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 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. On December 14, 2005, Nvidia acquired ULI Electronics, which at the time supplied third-party southbridge parts for chipsets to ATI, Nvidia’s competitor. In March 2006, Nvidia acquired Hybrid Graphics. In December 2006, Nvidia, along with its main rival in the graphics industry AMD, received subpoenas from the U.S. Department of Justice regarding possible antitrust violations in the graphics card industry.


Nvidia Office Inside


Jensen Huang:


He was born February 17, 1963 is a Taiwan-born American entrepreneur and businessman. Jen-Hsun co-founded the graphics-processor company Nvidia and serves as its president and CEO. Huang graduated from Oregon State University before moving to California. He graduated with a masters degree from Stanford University. In 2008, Forbes listed him as the 61st highest paid CEO in a list of U.S. CEOs and one of the wealthiest Asian-Americans in the United States. His family moved to Oneida, Kentucky, and then to Oregon. He graduated from Aloha High School, outside Portland. He received his undergraduate degree in electrical engineering from Oregon State University in 1984, and his master’s degree in electrical engineering from Stanford University in 1992. He gave his alma mater Stanford University US$30 million to build the Jen-Hsun Huang School of Engineering Center. The building is the second of four that make up Stanford’s Science and Engineering Quad. It was designed by Bora Architects of Portland, Oregon. He was the recipient in 2007 of the Silicon Valley Education Foundation’s Pioneer Business Leader Award for his work in both the corporate and philanthropic worlds. In 1999, Jensen Huang was named Entrepreneur of the Year in High Technology by Ernst & Young.In 2003, Huang received the Dr. Morris Chang Exemplary Leadership Award, which recognizes a leader who has made exceptional contributions to driving the development, innovation, growth, and long-term opportunities of the fabless semiconductor industry, from the Fabless Semiconductor Association. He was also a National Finalist for the EY Entrepreneur of the Year Award in 2003 and was an Award Recipient for the Northern California region in 1999. Additionally, Huang is a recipient of the Daniel J. Epstein Engineering Management Award from the University of Southern California and was named an Alumni Fellow by Oregon State University.Huang was awarded an honorary doctorate from Oregon State University at the June 13, 2009, commencement ceremony. In 2018, Huang was listed in the inaugural EDGE 50, naming the world’s top 50 influencers in edge computing.


Mr.Jensen Huang


Chris Malachowsky:


He was born 1958. He is an American electrical engineer, one of the founders of computer graphics company Nvidia.Raised in Oakhurst, Ocean Township, Monmouth County, New Jersey, Malachowsky graduated from Ocean Township High School in 1976. He received a B.S. degree in 1983 in electrical engineering from the University of Florida and an M.S. degree in 1986 from Santa Clara University. In 2008, he received the Distinguished Alumni Award from Santa Clara University and received Distinguished Alumni Award from University of Florida College of Engineering in 2013.


Mr.Chris Malachowsky
Nvidia Founder



Curtis Priem:


He is an American computer scientist.He received a B.S. degree in electrical engineering from Rensselaer Polytechnic Institute in 1982. He designed the first graphics processor for the PC, the IBM Professional Graphics Adapter. From 1986 to 1993, he was a senior staff engineer at Sun Microsystems, where he developed the GX graphics chip. He cofounded NVIDIA with Jen-Hsun Huang and Chris Malachowsky and was its Chief Technical Officer from 1993 to 2003. He retired from NVIDIA in 2003. In 2000, RPI named him Entrepreneur of the Year. From 2003 to 2007 he was a trustee of Rensselaer. In 2004 he announced that he would donate an unrestricted gift of $40 million to the Institute. Rensselaer subsequently created the Curtis R. Priem Experimental Media and Performing Arts Center, named in his honor and usually referred to as “EMPAC” for short.He is also president of the Priem Family Foundation, which he established with his wife Veronica in September, 1999. The foundation is non-operating and exists only to give money to other foundations or charities.


Nvidia Founder



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. On January 5, 2007, Nvidia announced that it had completed the acquisition of PortalPlayer, Inc. 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.


Graphic Card


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.In May 2011, it was announced that Nvidia had agreed to acquire Icera, a baseband chip making company in the UK, for $367 million. 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.On July 29, 2013, Nvidia announced that they acquired PGI from STMicroelectronics.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.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.In 2016, Nvidia leverages NVIDIA-Powered Infotainment in Luxgen. 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. 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. 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.Nvidia officially released the NVIDIA TITAN V on December 7, 2017. Nvidia officially released the Nvidia Quadro GV100 on March 27, 2018.In 2018, Google announced that Nvidia’s Tesla P4 graphic cards would be integrated into Google Cloud service’s artificial intelligence. Until September 23, 2013, Nvidia had not published any documentation for its hardware, meaning that programmers could not write free and open-source device driver for its products without resorting to reverse engineering. 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.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 inadequate, given that competing manufacturers like Intel offer support and documentation for open-source developers and that others release partial documentation and provide some active development. Instead, Nvidia provides its own binary GeForce graphics drivers for X. 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.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. 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.

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