DocumentCode :
688193
Title :
Large Scale Satellite Imagery Simulations with Physically Based Ray Tracing on Tianhe-1A Supercomputer
Author :
Changmao Wu ; Yunquan Zhang ; Congli Yang
Author_Institution :
Inst. of Software, Beijing, China
fYear :
2013
fDate :
13-15 Nov. 2013
Firstpage :
549
Lastpage :
556
Abstract :
Developing highly scalable algorithms for satellite imagery simulations is becoming increasingly important as scientists inquire to understand the mechanism of satellite imagery before satellites are launched into orbit. Although physically based ray tracing technique for image rendering has produced some of the most realistic images to date, studies on satellite imagery simulations using this technique are still very less to be seen, due in large part to both the complex physical processes and the computational difficulties of the mathematical models. In this paper, we present a highly scalable physically based ray tracer for satellite imagery simulations. Our ray tracer is based on a Master-Worker-Receiver framework which can overcome the performance bottleneck of Master node. Besides, a novel sample distribution strategy is presented by the authors, aiming at removing high additional computation overhead which is introduced by the currently available pixel distribution strategy. Compared to the pixel distribution strategy, our sample distribution strategy drops the computation overhead by 0.25 to 4 times. We also discuss the issue with granularity of assignment partitioning for Inter-Nodes and Intra-Nodes, then a hybrid scheduling strategy combining static and dynamic scheduling strategies is presented. Experiments show that our physically based ray tracer almost reaches to a linear speedup by using 16,800 CPU cores on Tianhe-1A Supercomputer. Our ray tracer is more efficient and highly scalable.
Keywords :
geophysical image processing; parallel machines; ray tracing; remote sensing; rendering (computer graphics); CPU cores; Tianhe-1A supercomputer; assignment partitioning granularity; complex physical processes; image rendering; inter-nodes; intra-nodes; large scale satellite imagery simulations; master node; master-worker-receiver framework; mathematical models; physically based ray tracing technique; pixel distribution strategy; sample distribution strategy; Computational modeling; Distribution strategy; Load management; Ray tracing; Receivers; Rendering (computer graphics); Satellites; assignment partitioning; distributed computing; hybrid scheduling; physically based ray tracing; pixel distribution; sample distribution; satellite imagery simulations;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
High Performance Computing and Communications & 2013 IEEE International Conference on Embedded and Ubiquitous Computing (HPCC_EUC), 2013 IEEE 10th International Conference on
Conference_Location :
Zhangjiajie
Type :
conf
DOI :
10.1109/HPCC.and.EUC.2013.84
Filename :
6831966
Link To Document :
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