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000938167 019__ $$a1179000133$$a1182448132$$a1182917097$$a1183933018
000938167 020__ $$a9789811539282$$q(electronic book)
000938167 020__ $$a9811539286$$q(electronic book)
000938167 020__ $$z9811539278
000938167 020__ $$z9789811539275
000938167 0247_ $$a10.1007/978-981-15-3
000938167 035__ $$aSP(OCoLC)on1164100770
000938167 035__ $$aSP(OCoLC)1164100770$$z(OCoLC)1179000133$$z(OCoLC)1182448132$$z(OCoLC)1182917097$$z(OCoLC)1183933018
000938167 040__ $$aYDX$$beng$$cYDX$$dGW5XE$$dLQU
000938167 049__ $$aISEA
000938167 050_4 $$aQA166.245
000938167 08204 $$a518/.1$$223
000938167 1001_ $$aShao, Yingxia.
000938167 24510 $$aLarge-scale graph analysis :$$bsystem, algorithm and optimization /$$cYingxia Shao, Bin Cui, Lei Chen.
000938167 260__ $$aSingapore :$$bSpringer,$$c2020.
000938167 300__ $$a1 online resource
000938167 336__ $$atext$$btxt$$2rdacontent
000938167 337__ $$acomputer$$bc$$2rdamedia
000938167 338__ $$aonline resource$$bcr$$2rdacarrier
000938167 4901_ $$aBig data management
000938167 504__ $$aIncludes bibliographical references.
000938167 5050_ $$a1. Introduction -- 2. Graph Computing Systems for Large-Scale Graph Analysis -- 3. Partition-Aware Graph Computing System -- 4. Efficient Parallel Subgraph Enumeration -- 5. Efficient Parallel Graph Extraction -- 6. Efficient Parallel Cohesive Subgraph Detection -- 7. Conclusions.
000938167 506__ $$aAccess limited to authorized users.
000938167 520__ $$aThis book introduces readers to a workload-aware methodology for large-scale graph algorithm optimization in graph-computing systems, and proposes several optimization techniques that can enable these systems to handle advanced graph algorithms efficiently. More concretely, it proposes a workload-aware cost model to guide the development of high-performance algorithms. On the basis of the cost model, the book subsequently presents a system-level optimization resulting in a partition-aware graph-computing engine, PAGE. In addition, it presents three efficient and scalable advanced graph algorithms - the subgraph enumeration, cohesive subgraph detection, and graph extraction algorithms. This book offers a valuable reference guide for junior researchers, covering the latest advances in large-scale graph analysis; and for senior researchers, sharing state-of-the-art solutions based on advanced graph algorithms. In addition, all readers will find a workload-aware methodology for designing efficient large-scale graph algorithms.
000938167 650_0 $$aGraph algorithms.
000938167 7001_ $$aCui, Bin.
000938167 7001_ $$aChen, Lei.
000938167 77608 $$iPrint version: $$z9811539278$$z9789811539275$$w(OCoLC)1141995987
000938167 830_0 $$aBig data management.
000938167 852__ $$bebk
000938167 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-981-15-3928-2$$zOnline Access$$91397441.1
000938167 909CO $$ooai:library.usi.edu:938167$$pGLOBAL_SET
000938167 980__ $$aEBOOK
000938167 980__ $$aBIB
000938167 982__ $$aEbook
000938167 983__ $$aOnline
000938167 994__ $$a92$$bISE