2015 IEEE 5th Symposium on Large Data Analysis and Visualization (LDAV) 2015
DOI: 10.1109/ldav.2015.7348072
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A visual analytics paradigm enabling trillion-edge graph exploration

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Cited by 9 publications
(6 citation statements)
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“…Today, researchers use computer clusters with as much as 1 TB of memory (or more) per computer node for high dimensional, in-memory database queries in interactive response time. For example, T-Rex (Wong et al, 2015) is able to query billions of data records in interactive response time using a Resource Description Framework 1 RDF 2014 database and the SPARQL (2008) query language running on a Linux cluster with 32 nodes of Intel Xeon processors and ∼24.5 TB of memory installed across the 32 nodes. Because such a large amount of information can be queued from a database in interactive time, the role of data warehouses continues to diminish in the big data era and as cloud computing becomes the norm.…”
Section: In-memory Computationmentioning
confidence: 99%
“…Today, researchers use computer clusters with as much as 1 TB of memory (or more) per computer node for high dimensional, in-memory database queries in interactive response time. For example, T-Rex (Wong et al, 2015) is able to query billions of data records in interactive response time using a Resource Description Framework 1 RDF 2014 database and the SPARQL (2008) query language running on a Linux cluster with 32 nodes of Intel Xeon processors and ∼24.5 TB of memory installed across the 32 nodes. Because such a large amount of information can be queued from a database in interactive time, the role of data warehouses continues to diminish in the big data era and as cloud computing becomes the norm.…”
Section: In-memory Computationmentioning
confidence: 99%
“…These are used for multiple tasks such as network performance monitoring and used as a means of security evaluation when an incident has been detected. Visualization of the NetFlow has also proven to be of tangible benefit [23]. Using this aggregated data for anomaly detection has numerous benefits, such as data size being reduced for processing purposes and storage.…”
Section: Cisco Netflowmentioning
confidence: 99%
“…Moreover, if any u, w neighbors, to be merged into a vertex v, having degrees at most ffiffiffiffi m p , were instead tested for fu, wg 2 E, which is possible in O(1) time, the runtime would be O(m 3 2 ), which is optimal. 24 Recent development is now encroaching on trillionedge scale graph exploration, 27 which could admit the navigation of trillions of triangles in a graph. The multiscale layout algorithm of Wong et al 27 is reported to be similar to the merging algorithm in GreenHornet and could therefore be extended in the aforementioned merging proposal of neighboring vertices to identify triangles.…”
Section: Visualizing Trillions Of Trianglesmentioning
confidence: 99%