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Quantum Monte Carlo (QMC) applications perform simulation with respect to an initial state of the quantum mechanical system, which is often captured by using a cubic B‐spline basis. This representation is stored as a read‐only table of coefficients and accesses to the table are generated at random as part of the Monte Carlo simulation. Current QMC applications, such as QWalk and QMCPACK, replicate...
Widespread use of stochastic flow based graph clustering algorithms, e.g. Markov Clustering (MCL), has been hampered by their lack of scalability and fragmentation of output. Multi-Level Regularized Markov Clustering (MLR-MCL) is an improvement over Markov Clustering (MCL), providing faster performance and better quality of clusters for large graphs. However, a closer look at MLR-MCL's performance...
Quantum Monte Carlo (QMC) applications perform simulation with respect to an initial state of the quantum mechanical system, which is often captured by using a cubic B-spline basis. This representation is stored as a read-only table of coefficients, and accesses to the table are generated at random as part of the Monte Carlo simulation. Current QMC applications such as QWalk and QMCPACK, replicate...
Reuse distance is a well established approach to characterizing data cache locality based on the stack histogram model. This analysis so far has been restricted to offline use due to the high cost, often several orders of magnitude larger than the execution time of the analyzed code. This paper presents the first parallel algorithm to compute accurate reuse distances by analysis of memory address...
Blog provides a simple way for people to share personal experiences and ideas, and has already become an important tool for people to communicate with each other. This fact turns blog into one of the most important information providers of the World Wide Web, but also makes how to find useful blogs for people to read an urgent problem. In this paper, we propose a blog clustering algorithm BCBSM (Blog...
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