{"title":"Parallel approximate computation of projections for animated volume rendered displays","authors":"Tung-Kuang Wu, M. Brady","doi":"10.1145/166181.166190","DOIUrl":"https://doi.org/10.1145/166181.166190","url":null,"abstract":"We present an approximate volume rendering algorithm that can compute multiple views of a 3D voxel-based data set concurrently. The approach employs a unique new method for combining partial results from neighboring objections to compute a sequence of rotated views, in fewer instructions than would be required for independent computations. For instance, the algorithm can compute a set of N projections through an N/spl times/N/spl times/N data set in only O(log N) parallel steps, using only O(N/sup 3/) total operations (work), matching the bounds for computing a single projection by conventional methods.","PeriodicalId":394370,"journal":{"name":"Proceedings of 1993 IEEE Parallel Rendering Symposium","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129516249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Segmented ray casting for data parallel volume rendering","authors":"William M. Hsu","doi":"10.1145/166181.166182","DOIUrl":"https://doi.org/10.1145/166181.166182","url":null,"abstract":"Interactive volume rendering is important to the timely analysis of three-dimensional data, but workstations take seconds to minutes to render data sets of a few megabytes. We have developed a parallel ray-casting technique, called Segmented Ray Casting, which can render a 128/spl times/128/spl times/128 data set at 2-3 frames per second on a 4K processor DECmpp 1200/Sx Model 100. Pixel values in the image plane are computed by casting rays through the volume data. The rays are segmented based on the intersection with the data sublocks in the processors. Each processor computes the color and opacity of the ray segments which pass through its subblock, which are then sent to the appropriate processor for composition with other segment values. Unlike other data-parallel volume renderers, Segmented Ray Casting does not require the transposition of volume data between processors at any time, nor does it suffer from resampling artifacts due to shearing.","PeriodicalId":394370,"journal":{"name":"Proceedings of 1993 IEEE Parallel Rendering Symposium","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127614155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Parallel volume rendering and data coherence","authors":"B. Corrie, P. Mackerras","doi":"10.1145/166181.166184","DOIUrl":"https://doi.org/10.1145/166181.166184","url":null,"abstract":"The two key issues in implementing a parallel ray-casting volume renderer are the work distribution and the data distribution. We have implemented such a renderer on the Fujitsu AP1000 using an adaptive image-space subdivision algorithm based on the worker-farm paradigm for the work distribution, and a distributed virtual memory, implemented in software, to provide the data distribution. Measurements show that this scheme works efficiently and effectively utilizes the data coherence that is inherent in volume data.","PeriodicalId":394370,"journal":{"name":"Proceedings of 1993 IEEE Parallel Rendering Symposium","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123905009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A pyramid-based approach to interactive terrain visualization","authors":"James K. Tam, J. Peters","doi":"10.1145/166181.166191","DOIUrl":"https://doi.org/10.1145/166181.166191","url":null,"abstract":"This paper describes a multiresolution approach to the visualization of surface data. The algorithms discussed allow the generation of arbitrary views of 3-dimensional surfaces. Image processing and texture mapping techniques are combined in a new 3-pass scanline algorithm to achieve smooth and continuous translations, rotations, and scale changes of large data sets. The implementation of the algorithms on a massively parallel SIMD video supercomputer, the Princeton Engine, allows the scenes to be generated interactively at video rates.","PeriodicalId":394370,"journal":{"name":"Proceedings of 1993 IEEE Parallel Rendering Symposium","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126747795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Permutation warping for data parallel volume rendering","authors":"C. Wittenbrink, Arun Kumar Somani","doi":"10.1145/166181.166189","DOIUrl":"https://doi.org/10.1145/166181.166189","url":null,"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.","PeriodicalId":394370,"journal":{"name":"Proceedings of 1993 IEEE Parallel Rendering Symposium","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133962567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}