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Hierarchical Sparse Graph Computations on Multicore Platforms
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Hierarchical Sparse Graph Computations on Multicore Platforms. |
| 개인저자 | Kabir, Humayun. |
| 단체저자명 | The Pennsylvania State University. Computer Science and Engineering. |
| 발행사항 | [S.l.]: The Pennsylvania State University., 2018. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
| 형태사항 | 160 p. |
| 기본자료 저록 | Dissertation Abstracts International 79-12B(E). Dissertation Abstract International |
| ISBN | 9780438135116 |
| 학위논문주기 | Thesis (Ph.D.)--The Pennsylvania State University, 2018. |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
|
| 요약 | Graph analysis is widely used to study connectivity, centrality, community and path analysis of social networks, biological networks, communication networks and any interacting objects that can be represented as graphs. Graphs are ubiquitous and |
| 요약 | To analyze connectivity, centrality and robustness of a graph, it is useful to find the densely connected subgraphs (cohesive subgraphs) of a graph. One of the contributions of this thesis is to design parallel algorithms for computing cohesive |
| 요약 | In centrality analysis and scientific computing, an important kernel is sparse matrix-vector multiplication (SpMV). Another contribution of this thesis, is to develop a multi-level data structure (CSR-k) to store sparse matrices/graphs to speedu |
| 일반주제명 | Computer science. Computer engineering. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
