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An AI accelerator, deep learning processor or neural processing unit (NPU) 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.
Some other computer architectures use different modules with a different bus width. In a single-channel configuration, only one module at a time can transfer information to the CPU. In multi-channel configurations, multiple modules can transfer information to the CPU at the same time, in parallel.
NPU may refer to: Science and technology. Net protein utilization, the percentage of ingested nitrogen retained in the body; NPU terminology (Nomenclature for ...
Qualcomm announced Hexagon Vector Extensions (HVX). HVX is designed to allow significant compute workloads for advanced imaging and computer vision to be processed on the DSP instead of the CPU. [19] In March 2015 Qualcomm announced their Snapdragon Neural Processing Engine SDK which allow AI acceleration using the CPU, GPU and Hexagon DSP. [20]
A floating-point unit (FPU), numeric processing unit (NPU), [1] colloquially math coprocessor, is a part of a computer system specially designed to carry out operations on floating-point numbers. [2] Typical operations are addition , subtraction , multiplication , division , and square root .
The M4 Neural Engine has been significantly improved compared to its predecessor, with the advertised capability to perform up to 38 trillion operations per second, claimed to be more than double the advertised performance of the M3. The M4 NPU performs over 60× faster than the A11 Bionic, and is approximately 3× faster than the original M1. [9]
Itanium processor featuring an all-new microarchitecture. [26] 8 cores, decoupling in pipeline and in multithreading. 12-wide issue with partial out-of-order execution. [27] Kittson the last Itanium. It has the same microarchitecture as Poulson, but slightly higher clock speed for the top two models.
The idea is having specialized processors offload time-consuming tasks from a computer's CPU, much like how a GPU performs graphics operations in the main CPU's place. The term was coined by Ageia to describe its PhysX chip. Several other technologies in the CPU-GPU spectrum have some features in common with it, although Ageia's product was the ...
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