Now showing items 1-4 of 4

  • Hybrid kmeans clustering algorithm 

    Authors:Çolakoğlu, Mustafa Alp
    Publisher and Date:(Kadir Has University, 2013)
    From the past up to the present size of the data is rapidly increasing day by day. Growing dimensions of this data can be held in databases is seen as a disadvantage. Companies have seen this information in databases as an excellent resource for increasing profitability. According to this source the profiles of the customers can be clustering and new products can be presented for cluster customers. So data mining algorithms are needed for rapidly examine these sources of information and obtaining ...

  • Hybrid MPI plus UPC parallel programming paradigm on an SMP cluster 

    The symmetric multiprocessing (SMP) cluster system which consists of shared memory nodes with several multicore central processing units connected to a high-speed network to form a distributed memory system is the most widely available hardware architecture for the high-performance computing community. Today the Message Passing Interface (MPI) is the most widely used parallel programming paradigm for SMP clusters in which the MPI provides programming both for an SMP node and among nodes simultaneously. ...

  • Optimizing NEURON Brain Simulator With Remote Memory Access On Distributed Memory Systems 

    The Complex neuronal network models require support from simulation environment for efficient network simulations. To compute the models increasing complexity necessitated the efforts to parallelize the NEURON simulation environment. The computational neuroscientists have extended NEURON by dividing the equations for its subnet among multiple processors for increasing the competence of hardware. For spiking neuronal networks inter-processor spikes exchange consume significant portion of overall ...

  • Optimizing NEURON Brain Simulator with Remote Memory Access On Distributed Memory Systems 

    Authors:Shehzad, Danish; Bozkuş, Zeki
    Publisher and Date:(IEEE, 2015)
    The Complex neuronal network models require support from simulation environment for efficient network simulations. To compute the models increasing complexity necessitated the efforts to parallelize the NEURON simulation environment. The computational neuroscientists have extended NEURON by dividing the equations for its subnet among multiple processors for increasing the competence of hardware. For spiking neuronal networks inter-processor spikes exchange consume significant portion of overall ...