Our work describes the simulation of a planar network of spiking IfF neurons on graphics processing hardware. The described approach adds to the fast-growing field of general-purpose computation on GPUs (GPGPU). We provide an in-depth explanation of the steps involved in implementing the network using programmable shading hardware. We replicated simulation results by Hopfield et al. [1] and Maida et al. [2] and give qualitative and quantitative measures of our implementation.
We present a new 3D lens rendering technique and a new spatiotemporal lens. Interactive 3D lenses, often called volumetric lenses, provide users with alternative views of data sets within 3D lens boundaries while maintaining the surrounding overview (context). In contrast to previous multipass rendering work, we discuss the strengths, limitations, and performance costs of a single-pass technique especially suited to fragment-level lens effects, such as color mapping, lighting, and clipping. Some object-level effects, such as a data set selection lens, are also incorporated, with each object's geometry being processed once by the graphics pipeline. For a substantial range of effects, our approach supports several composable lenses at interactive frame rates without performance loss during increasing lens intersections or manipulation by a user. Other cases, for which this performance cannot be achieved, are also discussed. We illustrate possible applications of our lens system, including Time Warp lenses for exploring time-varying data sets.
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