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  2. NVDLA - Wikipedia

    en.wikipedia.org/wiki/NVDLA

    The NVIDIA Deep Learning Accelerator (NVDLA) is an open-source hardware neural network AI accelerator created by Nvidia. [1] The accelerator is written in Verilog and is configurable and scalable to meet many different architecture needs. NVDLA is merely an accelerator and any process must be scheduled and arbitered by an outside entity such as ...

  3. Deep Learning Super Sampling - Wikipedia

    en.wikipedia.org/wiki/Deep_learning_super_sampling

    [25] [failed verification] Tensor Cores are available since the Nvidia Volta GPU microarchitecture, which was first used on the Tesla V100 line of products. [37] They are used for doing fused multiply-add (FMA) operations that are used extensively in neural network calculations for applying a large series of multiplications on weights, followed ...

  4. NVIDIA (NVDA) Gaming Drives the Deep Learning-AI Revolution

    www.aol.com/news/nvidia-nvda-gaming-drives-deep...

    NVIDIA (NASDAQ:NVDA) is not only reinventing industries but actually creating new industries with its GPU-based deep learning and artificial intelligence technologies. Source: via Nvidia Today’s ...

  5. Neural processing unit - Wikipedia

    en.wikipedia.org/wiki/Neural_processing_unit

    During the 2010s, GPU manufacturers such as Nvidia added deep learning related features in both hardware (e.g., INT8 operators) and software (e.g., cuDNN Library). Over the 2010s GPUs continued to evolve in a direction to facilitate deep learning, both for training and inference in devices such as self-driving cars.

  6. Cerebras launches AI inference tool to challenge Nvidia

    www.aol.com/news/cerebras-launches-ai-inference...

    Cerebras Systems launched on Tuesday a tool for AI developers that allows them to access the startup's outsized chips to run applications, offering what it says is a much cheaper option than ...

  7. CUDA - Wikipedia

    en.wikipedia.org/wiki/CUDA

    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. [6] In addition to drivers and runtime kernels, the CUDA platform includes compilers, libraries and developer tools to help programmers accelerate their applications.

  8. 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 ...

  9. Nvidia - Wikipedia

    en.wikipedia.org/wiki/Nvidia

    In April 2016, Nvidia produced the DGX-1 based on an 8 GPU cluster, to improve the ability of users to use deep learning by combining GPUs with integrated deep learning software. [190] Nvidia gifted its first DGX-1 to OpenAI in August 2016 to help it train larger and more complex AI models with the capability of reducing processing time from ...