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• W2158167310 abstract "Visualizing large molecular data requires efficient means of rendering millions of data elements that combine glyphs, geometry and volumetric techniques. The geometric and volumetric loads challenge traditional rasterization-based vis methods. Ray casting presents a scalable and memory- efficient alternative, but modern techniques typically rely on GPU-based acceleration to achieve interactive rendering rates. In this paper, we present bnsView, a molecular visualization ray tracing framework that delivers fast volume rendering and ball-and-stick ray casting on both multi-core CPUs and many-core Intel® Xeon Phi™ co-processors, implemented in a SPMD language that generates efficient SIMD vector code for multiple platforms without source modification. We show that our approach running on co- processors is competitive with similar techniques running on GPU accelerators, and we demonstrate large-scale parallel remote visualization from TACC's Stampede supercomputer to large-format display walls using this system." @default.
• W2158167310 created "2016-06-24" @default.
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• W2158167310 date "2013-11-17" @default.
• W2158167310 modified "2023-09-27" @default.
• W2158167310 title "Ray tracing and volume rendering large molecular data on multi-core and many-core architectures" @default.
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• W2158167310 doi "https://doi.org/10.1145/2535571.2535594" @default.
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