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PPL
2007
126views more  PPL 2007»
13 years 4 months ago
Challenges in Parallel Graph Processing
Graph algorithms are becoming increasingly important for solving many problems in scientific computing, data mining and other domains. As these problems grow in scale, parallel c...
Andrew Lumsdaine, Douglas Gregor, Bruce Hendrickso...
ICDCN
2011
Springer
12 years 8 months ago
A High-Level Framework for Distributed Processing of Large-Scale Graphs
Distributed processing of real-world graphs is challenging due to their size and the inherent irregular structure of graph computations. We present HIPG, a distributed framework th...
Elzbieta Krepska, Thilo Kielmann, Wan Fokkink, Hen...
IPPS
2007
IEEE
13 years 11 months ago
Challenges in Mapping Graph Exploration Algorithms on Advanced Multi-core Processors
Multi-core processors are a shift of paradigm in computer architecture that promises a dramatic increase in performance. But multi-core processors also bring an unprecedented leve...
Oreste Villa, Daniele Paolo Scarpazza, Fabrizio Pe...
FGCS
2002
138views more  FGCS 2002»
13 years 4 months ago
Armada: a parallel I/O framework for computational grids
High-performance computing increasingly occurs on "computational grids" composed of heterogeneous and geographically distributed systems of computers, networks, and stor...
Ron Oldfield, David Kotz
SIGMOD
2010
ACM
255views Database» more  SIGMOD 2010»
13 years 9 months ago
Large graph processing in the cloud
As the study of graphs, such as web and social graphs, becomes increasingly popular, the requirements of efficiency and programming flexibility of large graph processing tasks c...
Rishan Chen, Xuetian Weng, Bingsheng He, Mao Yang