Solving a large scale radiosity problem on GPU-based parallel computers

被引:2
|
作者
D'Azevedo, Eduardo [1 ]
Hu, Zhiang [2 ]
Su, Shi-Quan [3 ]
Wong, Kwai [3 ]
机构
[1] Comp Sci & Math Div, Oak Ridge, TN 37831 USA
[2] Chinese Univ Hong Kong, Shatin, Hong Kong, Peoples R China
[3] Univ Tennessee, Joint Inst Computat Sci, Knoxville, TN 37996 USA
基金
美国国家科学基金会;
关键词
Radiosity; View factor calculation; Cholesky decomposition; Out-of-core algorithm; Hybrid multicore/GPU system; LU FACTORIZATION; ACCELERATORS; CLUSTER; LINPACK;
D O I
10.1016/j.cam.2014.02.011
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
The radiosity equation has been used widely in computer graphics and thermal engineering applications. The equation is simple to formulate but is challenging to solve when the number of Lambertian surfaces associated with an application becomes large. In this paper, we present the algorithms to compute the view factors and solve the set of radiosity equations using an out-of-core Cholesky decomposition method. This work details the algorithmic procedures of the computation of the view factors and the Cholesky solver. The data layout of the radiosity matrix follows the block cyclic decomposition scheme used in ScaLAPACK. The parallel computation of the view factors on the GPUs extends the algorithms based on a serial community code called view3d. To handle large matrices that exceed the device memory on GPU, an out-of-core algorithm for parallel Cholesky factorization is implemented. A performance study conducted on Keeneland, a hybrid CPU/GPU cluster at the National Institute for Computational Sciences, composed of 264 nodes of multicore CPU and GPU are shown and discussed. (C) 2014 Elsevier B.V. All rights reserved.
引用
收藏
页码:109 / 120
页数:12
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