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Exascale computing refers to computing systems capable of calculating at least 1018 IEEE 754 double precision (64-bit) operations (multiplications and/or additions) per second (exaFLOPS)"; it is a measure of supercomputer performance.
The analysis highlights History, Technology and Science as prominent areas in the source structure around Exascale computing. 1 topic appears in more than one source area, which can help identify connections that are less obvious in a linear reading.
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.
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.
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The extracted context around Exascale computing shows recurring relationship patterns in the source. For example, Exascale computing → Applications, Centre, Cheshire, Cluster Vision, Collaborative Research, DEEP, Dynamical ExaScale Entry Platform, Energy-Efficient, EoCoE, EPSRC, European, European Union, Exascale, Exascale Systemware, Excellence, Future II, Manchester, March, Materials, MaX Another extracted example is Exascale computing → Floating, FLOPS, Frontier, High Performance LINPACK, HPLinpack, Supercomputers, TOP500, Whilst. Use these groups to spot repeated connection types before inspecting the individual relationships.
Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
exascale supercomputer exaflops computing computer project announced research national performance june frontier united 2020 supercomputing development top500 energy science technology
TTTA extracted 61 structured relationships around Exascale computing. Examples in this analysis include Exascale computing → is a → significant achievement in computer engineering and weather forecasting → instance of → it allows improved scientific applications and better prediction accuracy in domains. The table shows each extracted connection, where it came from and its confidence.
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Exascale computing | is a | significant achievement in computer engineering | 0.90 | text |
| weather forecasting | instance of | it allows improved scientific applications and better prediction accuracy in domains | 0.80 | text |
| climate modeling | instance of | it allows improved scientific applications and better prediction accuracy in domains | 0.80 | text |
| personalised medicine | instance of | it allows improved scientific applications and better prediction accuracy in domains | 0.80 | text |
| Exascale computing | related to Definitions | Floating | 0.60 | section |
| Exascale computing | related to Definitions | FLOPS | 0.60 | section |
| Exascale computing | related to Definitions | TOP500 | 0.60 | section |
| Exascale computing | related to Definitions | High Performance LINPACK | 0.60 | section |
| Exascale computing | related to Definitions | HPLinpack | 0.60 | section |
| Exascale computing | related to Definitions | Whilst | 0.60 | section |
| Exascale computing | related to Definitions | Frontier | 0.60 | section |
| Exascale computing | related to Definitions | Supercomputers | 0.60 | section |
The concept neighborhoods around Exascale computing bring nearby vocabulary together. In this analysis, examples include Exascale, Supercomputer and Computer. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
For Exascale computing, one of the stronger structural bridges in this analysis connects Exascale computing with Development. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.
TTTA analyzes the structure around Exascale computing to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as History, Technology & Science, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — Exascale computing · EN edition · Analysis: TopicsToTalkAbout
