Research any topic before you write.
Find related topics. | Discover entities. | See connections. | Build a topical map.
Data-intensive computing is a class of parallel computing applications which use a data parallel approach to process large volumes of data typically terabytes or petabytes in size and typically referred to as big data. Computing applications that devote most of their execution time to computational requirements are deemed compute-intensive, whereas…
Characters, System architectures & Characteristics
Explore the main themes, entities and connections around Data-intensive computing. Start with the topic map, then use the sections below for research and deeper semantic analysis.
Start with a few of the strongest sections from the source topic. These are research directions, not a list of keywords you must use.
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Browse the full topic structure. Each item opens a new analysis centered on that subject.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
See the strongest relationship patterns around the current topic before diving into the raw triples.
Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
data processing computing data-intensive applications parallel system mapreduce hadoop distributed programming nodes execution architecture cluster typically performance systems language large
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Data-intensive computing | is a | class of parallel computing applications which use a data parallel approach to process large volumes of data typically terabytes or petabytes in size and typically referred to a… | 0.90 | text |
| InfiniBand allow data to be stored in a separate repository | instance of | Newer technologies | 0.80 | text |
| provide performance comparable to collocated data.The programming model utilized | instance of | Newer technologies | 0.80 | text |
| sorting.A focus on reliability | instance of | The programming abstraction and language tools allow the processing to be expressed in terms of data flows and transformations incorporating new dataflow programming languages a… | 0.80 | text |
| availability | instance of | The programming abstraction and language tools allow the processing to be expressed in terms of data flows and transformations incorporating new dataflow programming languages a… | 0.80 | text |
| data cleansing | instance of | The Thor platform is a cluster whose purpose is to be a data refinery for processing massive volumes of raw data for applications | 0.80 | text |
| hygiene | instance of | The Thor platform is a cluster whose purpose is to be a data refinery for processing massive volumes of raw data for applications | 0.80 | text |
| extract | instance of | The Thor platform is a cluster whose purpose is to be a data refinery for processing massive volumes of raw data for applications | 0.80 | text |
| transform | instance of | The Thor platform is a cluster whose purpose is to be a data refinery for processing massive volumes of raw data for applications | 0.80 | text |
| load | instance of | The Thor platform is a cluster whose purpose is to be a data refinery for processing massive volumes of raw data for applications | 0.80 | text |
| Data-intensive computing | related to Approach | Data-intensive | 0.60 | section |
| Data-intensive computing | related to Approach | This | 0.60 | section |
These clusters group vocabulary that occurs around closely connected concepts in the source material.
Bridges can reveal useful research angles that are easy to miss in a flat list of related terms.