GP-GPU and Multi-Core Architectures for Computing Clustering Coefficients of Irregular Graphs
نویسندگان
چکیده
Network science makes heavy use of simulation models and calculations based upon graph-oriented data structures that are intrinsically highly irregular in nature. The key to efficient use of data-parallel and multi-core parallelism on graphical processing units (GPUs) and CPUs is often to optimise the data layout and to exploit distributed memory locality with processing elements. We describe work using hybrid multi-core and many-core devices and architectures for implementing and optimising applications based upon irregular graph and network algorithms.
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