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  2. Tensor Processing Unit - Wikipedia

    en.wikipedia.org/wiki/Tensor_Processing_Unit

    TPU v4 improved performance by more than 2x over TPU v3 chips. Pichai said "A single v4 pod contains 4,096 v4 chips, and each pod has 10x the interconnect bandwidth per chip at scale, compared to any other networking technology.” [ 31 ] An April 2023 paper by Google claims TPU v4 is 5-87% faster than an Nvidia A100 at machine learning ...

  3. General-purpose computing on graphics processing units

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

    Microsoft introduced the DirectCompute GPU computing API, released with the DirectX 11 API. Alea GPU, [19] created by QuantAlea, [20] introduces native GPU computing capabilities for the Microsoft .NET languages F# [21] and C#. Alea GPU also provides a simplified GPU programming model based on GPU parallel-for and parallel aggregate using ...

  4. Nvidia Tesla - Wikipedia

    en.wikipedia.org/wiki/Nvidia_Tesla

    Nvidia Tesla C2075. Offering computational power much greater than traditional microprocessors, the Tesla products targeted the high-performance computing market. [4] As of 2012, Nvidia Teslas power some of the world's fastest supercomputers, including Summit at Oak Ridge National Laboratory and Tianhe-1A, in Tianjin, China.

  5. List of Nvidia graphics processing units - Wikipedia

    en.wikipedia.org/wiki/List_of_Nvidia_graphics...

    This number is generally used as a maximum throughput number for the GPU and generally, a higher fill rate corresponds to a more powerful (and faster) GPU. Memory subsection. Bandwidth – Maximum theoretical bandwidth for the processor at factory clock with factory bus width. GHz = 10 9 Hz. Bus type – Type of memory bus or buses used.

  6. SPARC T4 - Wikipedia

    en.wikipedia.org/wiki/SPARC_T4

    The SPARC T4 is a SPARC multicore microprocessor introduced in 2011 by Oracle Corporation. The processor is designed to offer high multithreaded performance (8 threads per core, with 8 cores per chip), as well as high single threaded performance from the same chip. [1] The chip is the 4th generation [2] processor in the T-Series family.

  7. Google Tensor - Wikipedia

    en.wikipedia.org/wiki/Google_Tensor

    Google Tensor is a series of ARM64-based system-on-chip (SoC) processors designed by Google for its Pixel devices. It was originally conceptualized in 2016, following the introduction of the first Pixel smartphone, though actual developmental work did not enter full swing until 2020.

  8. Tegra - Wikipedia

    en.wikipedia.org/wiki/Tegra

    The GPU in Tegra 3 is an evolution of the Tegra 2 GPU, with 4 additional pixel shader units and higher clock frequency. It can also output video up to 2560×1600 resolution and supports 1080p MPEG-4 AVC/h.264 40 Mbit/s High-Profile, VC1-AP, and simpler forms of MPEG-4 such as DivX and Xvid. [30] The Tegra 3 was released on November 9, 2011. [31]

  9. Multidimensional DSP with GPU acceleration - Wikipedia

    en.wikipedia.org/wiki/Multidimensional_DSP_with...

    That is, an M-D DTFT the complexity of GPGPU can be computed on a GPU with a complexity of Θ(n 2). While some GPGPUs are also equipped with hardware FFT accelerators internally, this implementation might be also optimized by invoking the FFT APIs or libraries provided by GPU manufacture.