NVDA

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NVDA

• Preetam Jinka
• Akhil Kolluri
• Pavan  Naik

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Background

• Graphics processing units (GPUs)
• Chipsets
•  
• Workstations
• Personal computers
• Mobile devices
• Servers
• Game consoles

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Product line

• GeForce
• Quadro
• nForce
• Tegra

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Competitors

• Intel
• AMD
• Texas Instruments

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Intel

• Graphics built into the processors
• GPU within CPU
• Fairly new

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AMD

• A semiconductor company - merged with ATI
• Very similar product line
• Nintendo GameCube, Wii, Xbox 360

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Texas Instruments

• Currently make chips in Motorola Droid
•  Rumored to switch to Nvidia chips in Motorola
  phones now
• Motorola still plans to sell 12 to 14 million
  phones in 2010.

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Charts
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Charts
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Charts
Low earnings / Lawsuit
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Charts
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Earnings
Next earnings release 11/12 Expected earnings
0.143
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(No Transcript)
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Seasonal performance
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CAPS

• 5-star rating

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News

• GeForce GTX 580
• 3DTV
• Dell
• Tegra 2
• Fastest Supercomputer

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(No Transcript)
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GeForce GTX 580 release?
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SOCIAL RESPONSIBILITY
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• NVIDIA is at the forefront of solving some of the
  worlds most complex social and scientific
  problems.
• Disease diagnosis, environmental forecasting,
  surveillance for national security purposes, the
  search for clues along the far edge of the known
  universe each is being addressed with tools
  accelerated through NVIDIA technology.
  Facilitating these breakthroughs is our core
  offering, the graphics processing unit, or GPU.
• NVIDIAs GPU works in tandem with a central
  processing unit (CPU), and is a specialized tool
  that breaks down complex computing problems into
  a great many smaller tasks that run concurrently.
  Our parallel processors accelerate a CPU by
  10-100 times, enabling hundreds of billions of
  operations to occur each second. They turbocharge
  a system, rendering it more powerful and more
  efficient than a CPU alone.
• Parallel processing is helping researchers make
  quantum leaps in progress in fields ranging from
  climate modeling to medical tomography, yielding
  advances that were previously impossible due to
  technology limitations. Problems that once took
  days to solve now can be addressed in minutes.
  Computations that previously required large,
  costly, energy intensive CPU clusters can now be
  accomplished more efficiently and less
  expensively by GPUs.
• These advances are possible not only because we
  have invested billions of dollars in RD, but
  also because we develop our products mindful of
  our ecosystemour suppliers, partners and our
  end-customers, who are addressing enormously
  challenging problems.
• Ecosystem Approach NVIDIAs ecosystem revolves
  around parallel processing and brings together a
  network of developers, researchers, students,
  scientists and other companies.
• We employ a substantial number of individuals who
  work with other companies to solve problems and
  develop new functionality.
• We work closely with researchers to understand
  the obstacles that prevent them from making
  progress, and we determine whether parallel
  processing could help.
• We connect researchers through our Fellowship
  programs and our CUDA Zone portal, and make
  software programs, such as Tesla BioWorkbench,
  that are designed to leverage our technology.
• Through technology and financial donations, we
  support a network of universities, professors and
  researchers who are solving important challenges
  through the GPU.
• In addition, we are engaged in efforts to reduce
  the power footprint of the GPU, focusing on
  improving our processors performance per watt of
  consumed power. We have made meaningful
  contributions through the deployment of Optimus,
  which intelligently optimizes a notebook
  computers battery life byshutting down the GPU
  when not in usewith no interference in usability
  or performance. Optimus reduces the GPUs load on
  the battery and helps decrease the number of
  times it must be recharged, allowing for longer
  battery life. In addition, our Tegra
  system-on-a-chip, which is the size of a
  thumbnail, comprises eight separate processors
  that are activated only when required, enabling
  it to sip power. Designed for use in portable
  devices, it uses one-hundredth of the power
  traditionally used by desktop PC processors and
  one-tenth of the power of notebook processors.

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Sources

• http//en.wikipedia.org/wiki/Nvidia
• http//en.wikipedia.org/wiki/Advanced_Micro_Device
  s
• http//en.wikipedia.org/wiki/ATI
• http//www.dailyfinance.com/earnings/nvidia-corpor
  ation/nvda/nas
• http//caps.fool.com/Ticker/NVDA.aspx
• http//www.intel.com/technology/graphics/
• https//docs.google.com/present/view?iddqcvvzc_10
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