GPUs

Extracted Attributes

• Type

  Specialized electronic circuit

• Forms

  Discrete graphics card, embedded on motherboards, mobile phones, personal computers, workstations, game consoles

• Components

  Silicon wafer, microscopic transistors, microscopic metal wires (interconnects)

• Nvidia Software

  CUDA parallel processing software

• Key Manufacturer

  Nvidia

• Primary Function

  Accelerate digital image processing and computer graphics

• Key Characteristic

  Parallel processing structure

• Non-Graphic Applications

  Artificial intelligence (training neural networks), cryptocurrency mining, scientific computing, machine learning, video editing, high performance computing (HPC), deep learning, advanced visualizations

Timeline

• Originally designed to accelerate the rendering of 3D graphics and process images. (Source: Wikipedia, Web Search - Intel)

  Early Development

• Became more flexible and programmable, enhancing their capabilities for advanced visual effects and realistic scenes. (Source: Web Search - Intel)

  Evolution

• Later found to be useful for non-graphic calculations involving embarrassingly parallel problems due to their parallel structure. (Source: Wikipedia)

  Expansion of Use

• Adopted in diverse fields including artificial intelligence (AI) for training neural networks and cryptocurrency mining, becoming the workhorse of modern AI. (Source: Wikipedia, Web Search - Google Cloud)

  Modern Adoption

Graphics processing unit

A graphics processing unit (GPU) is a specialized electronic circuit designed for digital image processing and to accelerate computer graphics, being present either as a component on a discrete graphics card or embedded on motherboards, mobile phones, personal computers, workstations, and game consoles. GPUs were later found to be useful for non-graphic calculations involving embarrassingly parallel problems due to their parallel structure. The ability of GPUs to rapidly perform vast numbers of calculations has led to their adoption in diverse fields including artificial intelligence (AI) where they excel at handling data-intensive and computationally demanding tasks. Other non-graphical uses include the training of neural networks and cryptocurrency mining.

Web Search Results

• What is a GPU & Its Importance for AI | Google Cloud

  A GPU, short for Graphics Processing Unit, is a specialized electronic circuit originally designed to speed up the creation of images and videos. However, its remarkable ability to perform vast numbers of calculations rapidly has led to its adoption in diverse fields, including artificial intelligence and scientific computing, where it excels at handling data-intensive and computationally demanding tasks. [...] GPUs have become the workhorse of modern artificial intelligence, enabling the training and deployment of complex AI models that power everything from image recognition to natural language processing. Their ability to perform massive numbers of calculations simultaneously makes them well-suited for the computationally demanding tasks at the heart of AI. GPUs accelerate the training of AI models, enabling researchers and developers to iterate on models more quickly and unlock breakthroughs in AI [...] GPUs are built upon a silicon wafer, a thin, circular slice of highly purified silicon. This wafer serves as the base upon which billions of microscopic transistors are etched. These transistors act as miniature gates controlling the flow of electricity, forming the building blocks of the GPU's logic circuits. A complex network of microscopic metal wires, called interconnects, link these transistors, enabling them to communicate and perform calculations. Finally, the entire assembly is encased

• What is a Graphics Processing Unit (GPU)? - Arm

  A graphics processing unit (GPU) is an electronic circuit designed to process images and accelerate the rendering of 3D computer graphics on consumer devices, such as computers, smartphones, and gaming consoles. While both GPUs and CPUs are critical, silicon-based computing engines, GPU architectures are designed specifically for rendering images on a screen. The smaller, more numerous and more highly specialized cores of the GPU are designed to divide processing tasks into multiple sets and [...] While most CPUs can manage the rendering of basic objects, intensive graphics require a dedicated GPU designed to handle more strenuous workloads. Video game graphics, for example, often render each frame individually, which requires immense processing power. While typically associated with high-end video game graphics, many business applications also rely on GPUs for tasks that require powerful processing. GPUs are frequently used in scientific and AI applications due to their ability to [...] Skip to Main Content Skip to Footer Sorry, your browser is not supported. We recommend upgrading your browser. GLOSSARY GPUS # What are GPUs?

• What is a GPU? - Graphics Processing Unit Explained - Amazon AWS

  A graphics processing unit (GPU) is an electronic circuit that can perform mathematical calculations at high speed. Computing tasks like graphics rendering, machine learning (ML), and video editing require the application of similar mathematical operations on a large dataset. A GPU’s design allows it to perform the same operation on multiple data values in parallel. This increases its processing efficiency for many compute-intensive tasks. ## Why are GPUs important? [...] Each GPU works slightly differently depending on its purpose, the manufacturer, the specifics of the chip, and the software used for coordinating the GPU. For instance, Nvidia’s CUDA parallel processing software allows developers to specifically program the GPU with almost any general-purpose parallel processing application in mind. GPUs can be standalone chips, known as discrete GPUs, or integrated with other computing hardware, known as integrated GPUs (iGPUs). ### Discrete GPUs

• What Is a GPU? Graphics Processing Units Defined - Intel

  The graphics processing unit, or GPU, has become one of the most important types of computing technology, both for personal and business computing. Designed for parallel processing, the GPU is used in a wide range of applications, including graphics and video rendering. Although they’re best known for their capabilities in gaming, GPUs are becoming more popular for use in creative production and artificial intelligence (AI). [...] GPUs were originally designed to accelerate the rendering of 3D graphics. Over time, they became more flexible and programmable, enhancing their capabilities. This allowed graphics programmers to create more interesting visual effects and realistic scenes with advanced lighting and shadowing techniques. Other developers also began to tap the power of GPUs to dramatically accelerate additional workloads in high performance computing (HPC), deep learning, and more. [...] What does GPU stand for? Graphics processing unit, a specialized processor originally designed to accelerate graphics rendering. GPUs can process many pieces of data simultaneously, making them useful for machine learning, video editing, and gaming applications. GPUs may be integrated into the computer’s CPU or offered as a discrete hardware unit. By

• What is a GPU? - IBM

  Discrete GPUs, or dGPUs, are graphics processors that are separate from a device's CPU, where information is taken in and processed, allowing a computer to function. Discrete GPUs are typically used in advanced applications with special requirements, such as editing, content creation or high-end gaming. They are distinct chips with connectors to separate circuit boards and attached to the CPU by using an express slot. [...] # What is a graphics processing unit (GPU)? ## Authors Mesh Flinders Staff Writer IBM Think Stephanie Susnjara Staff Writer IBM Think Ian Smalley Staff Editor IBM Think ## What is a graphics processing unit (GPU)? A graphics processing unit (graphical processing unit, GPU) is an electronic circuit designed to speed computer graphics and image processing on various devices. These devices include video cards, system boards, mobile phones and personal computers (PCs). [...] GPUs are in high demand across many industries to enhance the experience and training capabilities of complex, professional applications, including product walkthroughs, CAD drawings and medical and seismic or geophysical imaging. GPUs are critical in advanced visualizations (e.g., professional training of firefighters, astronauts, schoolteachers) with 3D animation, AI and ML, advanced rendering and hyperrealistic virtual reality (VR) and augmented reality (AR) experiences.