LDR | | 00000nmm u2200205 4500 |
001 | | 000000334277 |
005 | | 20250203142436 |
008 | | 181129s2018 ||| | | | eng d |
020 | |
▼a 9780438135116 |
035 | |
▼a (MiAaPQ)AAI10903686 |
040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 248032 |
049 | 1 |
▼f DP |
082 | 0 |
▼a 004 |
100 | 1 |
▼a Kabir, Humayun. |
245 | 10 |
▼a Hierarchical Sparse Graph Computations on Multicore Platforms. |
260 | |
▼a [S.l.] :
▼b The Pennsylvania State University.,
▼c 2018 |
260 | 1 |
▼a Ann Arbor :
▼b ProQuest Dissertations & Theses,
▼c 2018 |
300 | |
▼a 160 p. |
500 | |
▼a Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B. |
502 | 1 |
▼a Thesis (Ph.D.)--The Pennsylvania State University, 2018. |
520 | |
▼a 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 |
520 | |
▼a 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 |
520 | |
▼a 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 |
590 | |
▼a School code: 0176. |
650 | 4 |
▼a Computer science. |
650 | 4 |
▼a Computer engineering. |
690 | |
▼a 0984 |
690 | |
▼a 0464 |
710 | 20 |
▼a The Pennsylvania State University.
▼b Computer Science and Engineering. |
773 | 0 |
▼t Dissertation Abstracts International
▼g 79-12B(E). |
773 | |
▼t Dissertation Abstract International |
790 | |
▼a 0176 |
791 | |
▼a Ph.D. |
792 | |
▼a 2018 |
793 | |
▼a English |
856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T15000673
▼n KERIS |
980 | |
▼a 201812
▼f 2019 |
990 | |
▼a 관리자
▼b 정현우 |