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General-purpose computing on graphics processing units: History, Applications & Measurement

General-purpose computing on graphics processing units (GPGPU, or less often GPGP) is the use of a graphics processing unit (GPU), which typically handles computation only for computer graphics, to perform computation in applications traditionally handled by the central processing unit (CPU). The use of multiple video cards in one computer, or large…

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General-purpose computing on graphics processing units topic overview

The analysis highlights History, Applications and Measurement as prominent areas in the source structure around General-purpose computing on graphics processing units.

Related topics
209
Source areas
6
Connected nodes
215
Extracted relationships
10
Concept neighborhoods
53
Bridge connections
215

What this topic covers Research coverage

Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.

Applications · 76 topics
Overview · 48 topics
Implementations · 34 topics
GPU vs. CPU · 31 topics
History · 17 topics
Classical GPGPU · 3 topics

Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.

Explore all related topics Closing gaps

Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.

Overview

History

Implementations

GPU vs. CPU

Classical GPGPU

Applications

Advanced semantic analysis

Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.

How General-purpose computing on graphics processing units connects Entity context

See recurring relationship patterns around General-purpose computing on graphics processing units before inspecting the individual extracted relationships.

Important terminology

Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.

Important terminology

gpu gpus gpgpu data processing computing graphics stream used parallel cpu operation using one nvidia operations also computer memory element

General-purpose computing on graphics processing units relationships Subject–Predicate–Object triples

TTTA extracted 10 structured relationships around General-purpose computing on graphics processing units. Examples in this analysis include Sh/RapidMind → instance of → This cumbersome translation was obviated by the advent of general-purpose programming languages and APIs and rack computing → instance of → gigantic-data-level tasks thus may be parallelized even further via specialized setups. The table shows each extracted connection, where it came from and its confidence.

SubjectPredicateObjectConfidenceSrc
Sh/RapidMindinstance ofThis cumbersome translation was obviated by the advent of general-purpose programming languages and APIs0.80text
Brookinstance ofThis cumbersome translation was obviated by the advent of general-purpose programming languages and APIs0.80text
Accelerator.These were followed by Nvidia's CUDAinstance ofThis cumbersome translation was obviated by the advent of general-purpose programming languages and APIs0.80text
which allowed programmers to ignore the underlying graphical concepts in favor of more common high-performance computing conceptsinstance ofThis cumbersome translation was obviated by the advent of general-purpose programming languages and APIs0.80text
rack computinginstance ofgigantic-data-level tasks thus may be parallelized even further via specialized setups0.80text
high-dynamic-range imaginginstance ofto obtain effects0.80text
S3 Graphicsinstance ofother vendors0.80text
XGI supported a mixture of formats up to FP24.The implementations of floating point on Nvidia GPUs are mostly IEEE compliantinstance ofother vendors0.80text
texture coordinatesinstance ofcreates fragments and interpolates per-vertex constants0.80text
colorTexture unitinstance ofcreates fragments and interpolates per-vertex constants0.80text

Related concept clusters Concept neighborhoods

The concept neighborhoods around General-purpose computing on graphics processing units bring nearby vocabulary together. In this analysis, examples include General-purpose, Graphics and Opencl. Use the clusters to find adjacent concepts and terminology that may deserve separate research.

  • General-purpose computing on graphics processing units
    • General-purpose
    • Graphics
    • Opencl
    • Applications
    • Programming
    • Processing
    • Data
    • Gpgpu
    • Gpus
    • Integer
    • Large
    • Per
  • general-purpose computing on graphics processing units
    • General-purpose
    • Processing
    • Graphics
    • Data
    • Using
    • Parallel
    • Image
    • Gpgpu
    • Used
    • Gpu
    • Operations
    • Shaders
  • graphics processing unit
    • Processing
    • Data
    • Image
    • Used
    • Shaders
    • Video
    • Gpus
    • Gpgpu
    • Also
    • Using
    • Cuda
    • Stream
  • computer graphics
    • Video
    • Processing
    • Image
    • Parallel
    • Shaders
    • Data
    • Gpgpu
    • Graphics
    • Example
    • Computing
    • Also
    • Gpus
  • central processing unit
    • Data
    • Image
    • Used
    • Video
    • Gpus
    • Also
    • Using
    • Stream
    • Integer
    • Shaders
    • Many
    • Per
  • video cards
    • Computer
    • Integer
    • Image
    • Processing
    • Cpu
    • Data
    • Gpgpu
    • Used
    • Gpus
    • Many
    • Pixel
    • Applications
  • parallel processing
    • Data
    • Using
    • Processing
    • Image
    • Used
    • Also
    • Video
    • Gpus
    • Many
    • Opencl
    • Cpus
    • Programming
  • processing elements
    • Data
    • Image
    • Used
    • Video
    • Gpus
    • Also
    • Using
    • Stream
    • Integer
    • Shaders
    • Many
    • Per

Connections between topic areas Semantic bridges

For General-purpose computing on graphics processing units, one of the stronger structural bridges in this analysis connects General-purpose computing on graphics processing units with Applications. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.

Min side: 3
General-purpose computing on graphics processing units — Applications · splits 139 ⟂ 77
General-purpose computing on graphics processing units — Overview · splits 167 ⟂ 49
General-purpose computing on graphics processing units — Implementations · splits 181 ⟂ 35
General-purpose computing on graphics processing units — GPU vs. CPU · splits 184 ⟂ 32
General-purpose computing on graphics processing units — History · splits 198 ⟂ 18
General-purpose computing on graphics processing units — Classical GPGPU · splits 212 ⟂ 4

Map overview Semantic statistics

General-purpose computing on graphics processing units

Nodes216
Edges215
Triples10
Avg. degree1.99
Density0.009259
Components1

Source & methodology

TTTA analyzes the structure around General-purpose computing on graphics processing units to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as History, Applications & Measurement, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.

Source: Wikipedia — General-purpose computing on graphics processing units · EN edition · Analysis: TopicsToTalkAbout

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