GraphTensor: Comprehensive GNN-Acceleration Framework for Efficient Parallel Processing of Massive Datasets
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Jang, Junhyeok | ko |
| dc.contributor.author | Kwon, Miryeong | ko |
| dc.contributor.author | Gouk, Donghyun | ko |
| dc.contributor.author | BAE, HANYEOREUM | ko |
| dc.contributor.author | Jung, Myoungsoo | ko |
| dc.date.accessioned | 2023-06-02T03:00:30Z | - |
| dc.date.available | 2023-06-02T03:00:30Z | - |
| dc.date.created | 2023-04-05 | - |
| dc.date.issued | 2023-05-16 | - |
| dc.identifier.citation | 37th IEEE International Parallel & Distributed Processing Symposium (IPDPS), 2023 | - |
| dc.identifier.uri | http://hdl.handle.net/10203/307027 | - |
| dc.language | English | - |
| dc.publisher | IEEE | - |
| dc.title | GraphTensor: Comprehensive GNN-Acceleration Framework for Efficient Parallel Processing of Massive Datasets | - |
| dc.type | Conference | - |
| dc.type.rims | CONF | - |
| dc.citation.publicationname | 37th IEEE International Parallel & Distributed Processing Symposium (IPDPS), 2023 | - |
| dc.identifier.conferencecountry | US | - |
| dc.identifier.conferencelocation | St. Petersburg, Florida | - |
| dc.contributor.localauthor | Jung, Myoungsoo | - |
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