NPU

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NPU may refer to:

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Universities

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<span class="mw-page-title-main">Floating-point unit</span> Part of a computer system

A floating-point unit (FPU), numeric processing unit (NPU), colloquially math coprocessor, is a part of a computer system specially designed to carry out operations on floating-point numbers. Typical operations are addition, subtraction, multiplication, division, and square root. Some FPUs can also perform various transcendental functions such as exponential or trigonometric calculations, but the accuracy can be low, so some systems prefer to compute these functions in software.

Floating point operations per second is a measure of computer performance in computing, useful in fields of scientific computations that require floating-point calculations.

A polytechnic is a school, college, or university that qualifies as an institute of technology or vocational university. They are sometimes called universities of applied sciences.

<span class="mw-page-title-main">Digital signal processor</span> Specialized microprocessor optimized for digital signal processing

A digital signal processor (DSP) is a specialized microprocessor chip, with its architecture optimized for the operational needs of digital signal processing. DSPs are fabricated on metal–oxide–semiconductor (MOS) integrated circuit chips. They are widely used in audio signal processing, telecommunications, digital image processing, radar, sonar and speech recognition systems, and in common consumer electronic devices such as mobile phones, disk drives and high-definition television (HDTV) products.

CM or its variants may refer to:

<span class="mw-page-title-main">Coprocessor</span> Type of computer processor

A coprocessor is a computer processor used to supplement the functions of the primary processor. Operations performed by the coprocessor may be floating-point arithmetic, graphics, signal processing, string processing, cryptography or I/O interfacing with peripheral devices. By offloading processor-intensive tasks from the main processor, coprocessors can accelerate system performance. Coprocessors allow a line of computers to be customized, so that customers who do not need the extra performance do not need to pay for it.

IPU may refer to:

DPI may refer to:

ITP may refer to:

<span class="mw-page-title-main">Emotion Engine</span> Central processing unit by Sony Computer Entertainment and Toshiba

The Emotion Engine is a central processing unit developed and manufactured by Sony Computer Entertainment and Toshiba for use in the PlayStation 2 video game console. It was also used in early PlayStation 3 models sold in Japan and North America to provide PlayStation 2 game support. Mass production of the Emotion Engine began in 1999 and ended in late 2012 with the discontinuation of the PlayStation 2.

San Francisco Bay University, formerly Northwestern Polytechnic University, is a private university in Fremont, California. Founded in 1984, the university awards bachelor's and master's degrees in computer science, engineering, technology and management programs.

Processor may refer to:

DPU may refer to:

PPU may refer to:

<span class="mw-page-title-main">Northwestern Polytechnical University</span> Public university in Xian, Shaanxi, China

Northwestern Polytechnical University is a public science and engineering university in Xi'an, Shaanxi, China. It is affiliated with the Ministry of Industry and Information Technology. The university is part of Project 211, Project 985, and the Double First-Class Construction.

HPU may refer to:

FPU may stand for:

In computing, half precision is a binary floating-point computer number format that occupies 16 bits in computer memory. It is intended for storage of floating-point values in applications where higher precision is not essential, in particular image processing and neural networks.

RP, R-P, Rp, R-p, or rp may refer to:

An AI accelerator, deep learning processor or neural processing unit (NPU) is a class of specialized hardware accelerator or computer system designed to accelerate artificial intelligence and machine learning applications, including artificial neural networks and computer vision. Typical applications include algorithms for robotics, Internet of Things, and other data-intensive or sensor-driven tasks. They are often manycore designs and generally focus on low-precision arithmetic, novel dataflow architectures or in-memory computing capability. As of 2024, a typical AI integrated circuit chip contains tens of billions of MOSFETs.