10.1016/j.jpdc.2012.09.010Journal of Parallel and Distributed Computing733303-316JPDC
Implementing a graph traversal (GT) algorithm for GPUs is a very challenging task. It is a core prim...
A novel parallel algorithm is presented for generating random scale-free networks using the preferen...
This article presents parallel algorithms for component decomposition of graph structures on general...
The widespread usage of random graphs has been highlighted in the context of database applications...
Random Graphs evolved as a major tool for modelling the complex net works. Random Graphs have wide r...
The future of high-performance computing is aligning itself towards the efficient use of highly para...
The implementation of Monte Carlo simulation on the CUDA Fortran requires a fast random number gener...
International audienceParallel stochastic simulations tend to exploit more and more computing power ...
Abstract EFFICIENT RANDOM NUMBER GENERATION FOR FERMI CLASS GPUs by NIRODHA ABEYWARDANA JAN 2012 Adv...
Abstract—Random networks are widely used for modeling and analyzing complex processes. Many mathemat...
Abstract. Random networks are widely used for modeling and analyz-ing complex processes. Many mathem...
Greedy graph matching provides us with a fast way to coarsen a graph during graph partitioning. Dire...
International audienceWe examine the requirements and the available methods and software to provide ...
International audienceRandom number generation is a key element of stochastic simulations. It has be...
Graphs are de facto data structures for many applications, and efficient graph processing is a must ...
Implementing a graph traversal (GT) algorithm for GPUs is a very challenging task. It is a core prim...
A novel parallel algorithm is presented for generating random scale-free networks using the preferen...
This article presents parallel algorithms for component decomposition of graph structures on general...
The widespread usage of random graphs has been highlighted in the context of database applications...
Random Graphs evolved as a major tool for modelling the complex net works. Random Graphs have wide r...
The future of high-performance computing is aligning itself towards the efficient use of highly para...
The implementation of Monte Carlo simulation on the CUDA Fortran requires a fast random number gener...
International audienceParallel stochastic simulations tend to exploit more and more computing power ...
Abstract EFFICIENT RANDOM NUMBER GENERATION FOR FERMI CLASS GPUs by NIRODHA ABEYWARDANA JAN 2012 Adv...
Abstract—Random networks are widely used for modeling and analyzing complex processes. Many mathemat...
Abstract. Random networks are widely used for modeling and analyz-ing complex processes. Many mathem...
Greedy graph matching provides us with a fast way to coarsen a graph during graph partitioning. Dire...
International audienceWe examine the requirements and the available methods and software to provide ...
International audienceRandom number generation is a key element of stochastic simulations. It has be...
Graphs are de facto data structures for many applications, and efficient graph processing is a must ...
Implementing a graph traversal (GT) algorithm for GPUs is a very challenging task. It is a core prim...
A novel parallel algorithm is presented for generating random scale-free networks using the preferen...
This article presents parallel algorithms for component decomposition of graph structures on general...
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