Computational Neuroscience is an emerging field that provides unique opportunities to study complex brain structures through realistic neural simulations. However, as biological details are added to models, the execution time for the simulation becomes longer. Graphics Processing Units (GPUs) are now being utilized to accelerate simulations due to their ability to perform computations in parallel. As such, they have shown significant improvement in execution time compared to Central Processing Units (CPUs). Most neural simulators utilize either multiple CPUs or a single GPU for better performance, but still show limitations in execution time when biological details are not sacrificed. Therefore, we present a novel CPU/GPU simulation environment for large-scale biological networks, the NeoCortical Simulator version 6 (NCS6). NCS6 is a free, open-source, parallelizable, and scalable simulator, designed to run on clusters of multiple machines, potentially with high performance computing devices in each of them. It has built-in leaky-integrate-and-fire (LIF) and Izhikevich (IZH) neuron models, but users also have the capability to design their own plug-in interface for different neuron types as desired. NCS6 is currently able to simulate one million cells and 100 million synapses in quasi real time by distributing data across eight machines with each having two video cards.
In order to simulate scientific models in various conditions climate change research involves using large sets of heterogeneous data. In many cases, for model interoperability a dataset from a given model or source needs to be transformed into a different data format required by a subsequent model or processor. This paper presents the SUNPRISM approach and software tools aimed at supporting collaborative scientific exploration via new capabilities for combining data transformations, model simulations, and output visualizations in application scenarios developed for climate change research. The SUNPRISM framework's defining characteristics are a visual object-based interface for scenario configuration, a workflowbased environment that allows code generation and dataflow scenario execution, and data visualization capabilities for 3D environments, including for immersive virtual environments such as CAVE. The paper describes the proposed approach and its supporting tools, the SUNPRISM Scenario Manager and the SUNPRISM Visualizer, and illustrates them on an application scenario in which data from the National Digital Forecast Database is retrieved and visualized in 3D. A brief comparison with related work and an outline of directions for future work are also included in the paper.
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