Permutation warping for data parallel volume rendering

Abstract

Volume rendering algorithms visualize sampled three dimensional data. A variety of applications create sampled data, including medical imaging, simulations, animation, and remote sensing. Researchers have sought to speed up volume rendering because of the high run time and wide application. Our algorithm uses permutation warping to achieve linear speedup on data parallel machines. This new algorithm calculates higher quality images than previous distributed approaches, and also provides more view angle freedom. We present permutation warping results on the SIMD MasPar MP-1. The efficiency results from nonconflicting communication. The communication remains efficient with arbitrary view directions, larger data sets, larger parallel machines, and high order filters. We show constant run time versus view angle, tunable filter quality, and efficient memory implementation.