Topic orientation
GotoBLAS at a glance
Research this topic
Explore the main themes, entities and connections around GotoBLAS. Start with the topic map, then use the sections below for research and deeper semantic analysis.
Explore this topic
Start with a few of the strongest sections from the source topic. These are research directions, not a list of keywords you must use.
Overview
Key facts & relationships
High-confidence facts extracted from structured source data. Use them as anchors for further research.
- Final release
- 2-1.13 / 5 February 2010; 16 years ago (2010-02-05)
- License
- BSD License
- Original author
- Kazushige Goto
- Type
- Linear algebra library; implementation of BLAS
Topics to explore
A structured outline of related entities, concepts and subtopics. Open any item to build a new map centered on it.Browse the full topic structure. Each item opens a new analysis centered on that subject.
Overview
- Scientific computing Computational science
- Open source Open source software
- BLAS
- API Application programming interface
- Processor Central processing unit
- Kazushige Goto
- Texas Advanced Computing Center
- Nehalem Nehalem (microarchitecture)
- OpenBLAS
- ISCAS Institute of Software, Chinese Academy of Sciences
- Sabbatical
- Japan Patent Office
- Pentium 4
- Supercomputer
- TFLOPS
- BSD license
- Matrix-matrix multiplication routine Matrix multiplication algorithm
- X86
- AMD64 X86-64
- Assembly code Assembly language
- L1 processor cache CPU cache
- L2 cache
- BLIS BLIS (software)
- MKL Intel Math Kernel Library
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 this topic connects Entity context
Quick relationship hints grouped by predicate. Useful for spotting recurring semantic connections around the current entity.See the strongest relationship patterns around the current topic before diving into the raw triples.
GotoBLAS
Top relations
Important terminology Word statistics
Frequent words and multi-word phrases across the lead, headings, infobox and body. Useful for terminology coverage.Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
Important terminology
blas processor goto computing use terms gemm kernel linear algebra library open source implementations developed texas advanced center used available
Entity relationships Subject–Predicate–Object triples
Extracted RDF-like relationships with confidence and source. The table includes structured facts and lower-confidence contextual relations.| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| GotoBLAS | Final release | 2-1.13 / 5 February 2010; 16 years ago (2010-02-05) | 1.00 | infobox |
| GotoBLAS | License | BSD License | 1.00 | infobox |
| GotoBLAS | Original author | Kazushige Goto | 1.00 | infobox |
| GotoBLAS | Type | Linear algebra library; implementation of BLAS | 1.00 | infobox |
Related concept clusters Concept neighborhoods
Clusters of nearby vocabulary surrounding the topic. Scan them for adjacent concepts and language you may have missed.These clusters group vocabulary that occurs around closely connected concepts in the source material.
Connections between topic areas Semantic bridges
Bridge nodes connect otherwise separate parts of the map. Expand a row to inspect the topic groups on each side.Bridges can reveal useful research angles that are easy to miss in a flat list of related terms.