LINPACK

Use the mouse wheel or two fingers (on touchscreens) to zoom in and out of the map.

Map view:

Zoom: 100%

More settings

Connection length 100% Label size 100% Node size 100% Line width 100% Label width 100%

Export map as:

LINPACK topic overview

The analysis highlights Art and Overview as prominent areas in the source structure around LINPACK.

Related topics: 12
Source areas: 1
Connected nodes: 13
Extracted relationships: 5
Concept neighborhoods: 14
Bridge connections: 13

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.

Overview · 12 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.

Key facts & relationships

High-confidence facts extracted from structured source data. Use them as anchors for further research.

Original authors: Jack Dongarra, Jim Bunch, Cleve Moler, and Gilbert Stewart
Type: Library
Written in: Fortran

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

Library Library (computer science)
Linear algebra
Digital computers
Fortran
Jack Dongarra
Cleve Moler
Supercomputers Supercomputer
LAPACK
BLAS Basic Linear Algebra Subprograms
LINPACK benchmarks
HPL HPL (benchmark)
TOP500

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 LINPACK connects Entity context

The extracted context around LINPACK shows recurring relationship patterns in the source. For example, LINPACK → Jack Dongarra, Jim Bunch, Cleve Moler, and Gilbert Stewart Another extracted example is LINPACK → Library. Use these groups to spot repeated connection types before inspecting the individual relationships.

Top relations

Original authors · 1

LINPACK → Jack Dongarra, Jim Bunch, Cleve Moler, and Gilbert Stewart

Type · 1

LINPACK → Library

Website · 1

LINPACK → netlib.org/linpack/

Written in · 1

LINPACK → Fortran

is a · 1

LINPACK → software library for performing numerical linear algebra on digital computers

Important terminology

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

Important terminology

supercomputers library fortran performing linear algebra use written jack dongarra jim bunch cleve moler gilbert stewart libraries list lapack blas

LINPACK relationships Subject–Predicate–Object triples

TTTA extracted 5 structured relationships around LINPACK. Examples in this analysis include LINPACK → Original authors → Jack Dongarra, Jim Bunch, Cleve Moler, and Gilbert Stewart and LINPACK → Type → Library. The table shows each extracted connection, where it came from and its confidence.

Subject	Predicate	Object	Confidence	Src
LINPACK	Original authors	Jack Dongarra, Jim Bunch, Cleve Moler, and Gilbert Stewart	1.00	infobox
LINPACK	Type	Library	1.00	infobox
LINPACK	Website	netlib.org/linpack/	1.00	infobox
LINPACK	Written in	Fortran	1.00	infobox
LINPACK	is a	software library for performing numerical linear algebra on digital computers	0.90	text

Related concept clusters Concept neighborhoods

The concept neighborhoods around LINPACK bring nearby vocabulary together. In this analysis, examples include Algebra, Libraries and Library. Use the clusters to find adjacent concepts and terminology that may deserve separate research.

LINPACK
- Algebra
- Libraries
- Library
- Linear
- List
- Performing
- Basic
- Blas
- Computers
- Digital
- Hpl
- Makes
linpack
- Algebra
- Libraries
- Library
- Linear
- List
- Performing
- Basic
- Blas
- Computers
- Digital
- Hpl
- Makes
linpack benchmarks
- Algebra
- Libraries
- Library
- Linear
- List
- Performing
- Basic
- Blas
- Computers
- Digital
- Hpl
- Makes
library
- Computers
- Digital
- Numerical
- Software
- Linpack
- Algebra
- Bunch
- Cleve
- Dongarra
- Fortran
- Gilbert
- Jack
jack dongarra
- Bunch
- Cleve
- Dongarra
- Fortran
- Gilbert
- Jack
- Jim
- Moler
- Stewart
- Written
- 1970s
- 1980s
fortran
- Bunch
- Cleve
- Dongarra
- Gilbert
- Jack
- Jim
- Moler
- Stewart
- Written
- 1970s
- 1980s
- Early
cleve moler
- Dongarra
- Fortran
- Gilbert
- Jack
- Jim
- Moler
- Stewart
- Written
- 1970s
- 1980s
- Early
- Intended
linear algebra
- Algebra
- Linear
- Performing
- Basic
- Blas
- Computers
- Digital
- Makes
- Numerical
- Software
- Subprograms
- Linpack

Connections between topic areas Semantic bridges

Bridges highlight paths between different parts of the LINPACK map and can reveal research angles that are easy to miss in a flat list.

Min side: 3

Map overview Semantic statistics

LINPACK

Nodes14

Edges13

Triples5

Avg. degree1.86

Density0.142857

Components1

Source & methodology

TTTA analyzes the structure around LINPACK to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Art & Overview, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.

Source: Wikipedia — LINPACK · EN edition · Analysis: TopicsToTalkAbout