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A neural processing unit (NPU), also known as AI accelerator or deep learning processor, is a class of specialized hardware accelerator [1] or computer system [2] [3] designed to accelerate artificial intelligence (AI) and machine learning applications, including artificial neural networks and computer vision.
Download as PDF; Printable version; ... Network processing unit, hardware for networking; Neural processing unit, hardware for artificial intelligence;
Hexagon is the brand name for a family of digital signal processor (DSP) and later neural processing unit (NPU) products by Qualcomm. [2] Hexagon is also known as QDSP6, standing for “sixth generation digital signal processor.”
Huawei launched its Kirin 970 at IFA this year, calling it the first chipset with a dedicated neural processing unit (NPU). Then, Apple unveiled the A11 Bionic chip, which powers the iPhone 8, 8 ...
XDNA is the name for AMD's neural processing unit microarchitecture. It is based on IP blocks from Xilinx, a company which was acquired by AMD in 2023. [1] As of 2024, XDNA is implemented in AMD's consumer PC processors (branded as Ryzen AI), as well as the AMD Alveo V70 AI accelerator.
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 ...
The RK1808 is Rockchip's first chip with Neural Processing Unit (NPU) for artificial intelligence applications. [10] The RK1808 specifications include: Dual-core ARM Cortex-A35 CPU; Neural Processing Unit (NPU) with up to 3.0 TOPs supporting INT8/INT16/FP16 hybrid operation; 22 nm FD-SOI process; VPU supporting 1080p video codec
It is based around a neural processing unit (NPU) AI accelerator chip and a software API to interact with the platform. It makes a form of machine learning known as deep learning available to mobile devices. It is used for image and sound processing, including speech recognition. The software operates locally rather than as a cloud application. [1]