Characterizing Traffic Locality in 3D NoC-Based CMPs Using a Path-Based Partitioning Method
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: 2014DOI: 10.1109/eScience.2014.54
Keyword(s): Image reconstruction,Information retrieval,Measurement,Natural language processing,Prototypes,Semantics,Vectors,data provenance reconstruction,longest common subsequence,semantic analysis,similarity metrics,topic modeling,vector space model
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Characterizing Traffic Locality in 3D NoC-Based CMPs Using a Path-Based Partitioning Method
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| contributor author | Bahrebar, Poona | |
| contributor author | Stroobandt, Dirk | |
| date accessioned | 2020-03-12T21:07:31Z | |
| date available | 2020-03-12T21:07:31Z | |
| date issued | 2014 | |
| identifier other | 6925720.pdf | |
| identifier uri | http://libsearch.um.ac.ir:80/fum/handle/fum/1037825?locale-attribute=en | |
| format | general | |
| language | English | |
| publisher | IEEE | |
| title | Characterizing Traffic Locality in 3D NoC-Based CMPs Using a Path-Based Partitioning Method | |
| type | Conference Paper | |
| contenttype | Metadata Only | |
| identifier padid | 8164233 | |
| subject keywords | Image reconstruction | |
| subject keywords | Information retrieval | |
| subject keywords | Measurement | |
| subject keywords | Natural language processing | |
| subject keywords | Prototypes | |
| subject keywords | Semantics | |
| subject keywords | Vectors | |
| subject keywords | data provenance reconstruction | |
| subject keywords | longest common subsequence | |
| subject keywords | semantic analysis | |
| subject keywords | similarity metrics | |
| subject keywords | topic modeling | |
| subject keywords | vector space model | |
| identifier doi | 10.1109/eScience.2014.54 | |
| journal title | igh-Performance Interconnects (HOTI), 2014 IEEE 22nd Annual Symposium on | |
| filesize | 1186005 | |
| citations | 0 |