Extensions to permutation warping for parallel volume rendering

Abstract

SIMD, MIMD, MasPar, volume visualization, parallel algorithmsBiomedical volume visualization requires high quality and high performance, but the existing high performance solutions such as the Shear Warp algorithm, 3D texture mapping, and special purpose hardware have problems.Permutation warping achieves high fidelity for biomedical datasets of regular rectilinear volumes, using a one-to-one communication scheme for optimal O(1) communication on massively parallel computers. Extensions are presented including data dependent optimizations using octrees, arbitrary view angles flexibility, and multiple instruction stream multiple data stream (MIMD) implementation. A MasPar MP-2, single instruction stream multiple data stream (SIMD) (16,384 processor), implementation achieves 14 frames/second, using trilinear reconstruction on 128 3 volumes for 400% runtime improvement over our previous result. A Proteus MIMD (32 processor) implementation achieves 1 frame/second on the same data. Additionally the PermWeb software architecture is presented, that has shown as a proof of concept means to provide wide shared access to a powerful centralized rendered. All of these improvements make permutation warping an effective solution for biomedical volume visualization. Abstract Biomedical volume visualization requires high quality and high performance, but the existing high performance solutions such as the Shear Warp algorithm, 3D texture mapping, and special purpose hardware have problems. Permutation warping achieves high delity for biomedical datasets of regular rectilinear volumes, using a one-to-one communication scheme for optimal O1 communication on massively parallel computers. Extensions are presented including data dependent optimizations using octrees, arbitrary view angle exibility, and multiple instruction stream multiple data stream MIMD implementation. A MasPar MP-2, single instruction stream multiple data stream SIMD 16,384 processor, implementation achieves 14 frames second, using trilinear reconstruction on 128 3 volumes for 400 runtime improvement o ver our previous result. A Proteus MIMD 32 processor implementation achieves 1 frame second on the same data. Additionally the PermWeb software architecture is presented, that has been shown as a proof of concept means to provide wide shared access to a powerful centralized renderer. All of these improvements make permutation warping an e ective solution for biomedial volume visualization.

TRLE—an efficient data compression scheme for image composition of volume rendering on distributed memory multicomputers

“…In addition, volume datasets are too large to be stored in the memory of a single processor. One way to solve the above problems is to parallelize the serial volume rendering methods on distributed memory multicomputers [23][24][25][26][27][28][29].…”