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  2. Nvidia - Wikipedia

    en.wikipedia.org/wiki/Nvidia

    Nvidia is also a dominant supplier of artificial intelligence (AI) hardware and software. [6] [7] [8] Nvidia's professional line of GPUs are used for edge-to-cloud computing and in supercomputers and workstations for applications in fields such as architecture, engineering and construction, media and entertainment, automotive, scientific ...

  3. CUDA - Wikipedia

    en.wikipedia.org/wiki/CUDA

    When it was first introduced, the name was an acronym for Compute Unified Device Architecture, [3] but Nvidia later dropped the common use of the acronym and now rarely expands it. [4] CUDA is a software layer that gives direct access to the GPU's virtual instruction set and parallel computational elements for the execution of compute kernels. [5]

  4. PhysX - Wikipedia

    en.wikipedia.org/wiki/PhysX

    PhysX is an open-source [1] realtime physics engine middleware SDK developed by Nvidia as part of the Nvidia GameWorks software suite. Initially, video games supporting PhysX were meant to be accelerated by PhysX PPU (expansion cards designed by Ageia).

  5. Nvidia's new software tools meant for companies adding AI to ...

    www.aol.com/news/nvidias-software-tools-meant...

    Nvidia's tools offer a potential revenue boost for the chipmaker: They are part of its existing software suite that costs $4,500 a year for each Nvidia chip if used on in a private data center or ...

  6. Nvidia highlights AI software and services at D.C. AI Summit

    www.aol.com/finance/nvidia-highlights-ai...

    Nvidia says companies ranging from AT&T , Deloitte, and Quantiphi to research centers like the National Cancer Institute and the SETI Institute are using its software technologies to do everything ...

  7. Nvidia RTX - Wikipedia

    en.wikipedia.org/wiki/Nvidia_RTX

    Nvidia RTX (also known as Nvidia GeForce RTX under the GeForce brand) is a professional visual computing platform created by Nvidia, primarily used in workstations for designing complex large-scale models in architecture and product design, scientific visualization, energy exploration, and film and video production, as well as being used in mainstream PCs for gaming.

  8. The Future According to Nvidia's Jensen Huang - AOL

    www.aol.com/future-according-nvidias-jensen...

    That's what Nvidia wants to do. It still wants to have that brand cachet, if you will. Plus, you're exactly right, $3 billion is nothing to sneeze at. ... They're going to make their entire next ...

  9. General-purpose computing on graphics processing units

    en.wikipedia.org/wiki/General-purpose_computing...

    The dominant proprietary framework is Nvidia CUDA. [13] Nvidia launched CUDA in 2006, a software development kit (SDK) and application programming interface (API) that allows using the programming language C to code algorithms for execution on GeForce 8 series and later GPUs. ROCm, launched in 2016, is AMD's open-source response to CUDA.

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