Ray tracing and volume rendering large molecular data on multi-core and many-core architectures

  • Authors:
  • Aaron Knoll;Ingo Wald;Paul A. Navrátil;Michael E. Papka;Kelly P. Gaither

  • Affiliations:
  • Texas Advanced Computing Center;Intel Corporation;Texas Advanced Computing Center;Argonne National Laboratory;Texas Advanced Computing Center

  • Venue:
  • UltraVis '13 Proceedings of the 8th International Workshop on Ultrascale Visualization
  • Year:
  • 2013

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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.