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  2. Tensor Processing Unit - Wikipedia

    en.wikipedia.org/wiki/Tensor_Processing_Unit

    Tensor Processing Unit (TPU) is an AI accelerator application-specific integrated circuit (ASIC) developed by Google for neural network machine learning, using Google's own TensorFlow software. [2] Google began using TPUs internally in 2015, and in 2018 made them available for third-party use, both as part of its cloud infrastructure and by ...

  3. Nvidia Jetson - Wikipedia

    en.wikipedia.org/wiki/Nvidia_Jetson

    384-core Nvidia Volta architecture GPU with 48 Tensor cores 2 6-core Nvidia Carmel ARMv8.2 64-bit CPU 6MB L2 + 4MB L3 8 GiB 10–20 W 2023 Jetson Orin Nano [21] 34–67 Sparse INT8 TOPS up to 1024-core Nvidia Ampere architecture GPU with 32 Tensor cores — 6-core ARM Cortex-A78AE v8.2 64-bit CPU 1.5MB L2 + 4MB L3 4–8 GiB 7–25 W 2023

  4. Volta (microarchitecture) - Wikipedia

    en.wikipedia.org/wiki/Volta_(microarchitecture)

    Tensor cores: A tensor core is a unit that multiplies two 4×4 FP16 matrices, ... NVLink 2.0: a high-bandwidth bus between the CPU and GPU, and between multiple GPUs.

  5. Graphics processing unit - Wikipedia

    en.wikipedia.org/wiki/Graphics_processing_unit

    Components of a GPU. A graphics processing unit (GPU) is a specialized electronic circuit initially designed for digital image processing and to accelerate computer graphics, being present either as a discrete video card or embedded on motherboards, mobile phones, personal computers, workstations, and game consoles.

  6. Turing (microarchitecture) - Wikipedia

    en.wikipedia.org/wiki/Turing_(microarchitecture)

    Turing is the codename for a graphics processing unit (GPU) microarchitecture developed by Nvidia. It is named after the prominent mathematician and computer scientist Alan Turing . The architecture was first introduced in August 2018 at SIGGRAPH 2018 in the workstation-oriented Quadro RTX cards, [ 2 ] and one week later at Gamescom in consumer ...

  7. Tegra - Wikipedia

    en.wikipedia.org/wiki/Tegra

    The second generation Tegra SoC has a dual-core ARM Cortex-A9 CPU, an ultra low power (ULP) GeForce GPU, [17] a 32-bit memory controller with either LPDDR2-600 or DDR2-667 memory, a 32 KB/32 KB L1 cache per core and a shared 1 MB L2 cache. [18] Tegra 2's Cortex A9 implementation does not include ARM's SIMD extension, NEON. There is a version of ...

  8. 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.

  9. RDNA 3 - Wikipedia

    en.wikipedia.org/wiki/RDNA_3

    The decision to move to a chiplet-based GPU microarchitecture was led by AMD Senior Vice President Sam Naffziger who had also lead the chiplet initiative with Ryzen and Epyc. [6] The development of RDNA 3's chiplet architecture began towards the end of 2017 with Naffziger leading the AMD graphics team in the effort. [ 7 ]