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Clustering is an important problem, which has been applied in many research areas. However, there is a large variety of clustering algorithms and each could produce quite different results depending on the choice of algorithm and input parameters, so how to evaluate clustering quality and find out the optimal clustering algorithm is important. Various clustering validity indices are proposed under...
We developed a methodology to improve the cache behavior and overall performance of sparse linear algebra kernels used in graph analytics. Large scale graph processing typically has low performance because it cannot effectively use processor caches, resulting in high-latency for memory accesses. This is particularly true in a sparse linear algebra formulations of graph algorithms, which use well known...
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