|
Title:
|
INFORMATION-ENTROPY BASED LOAD BALANCING IN PARALLEL ADAPTIVE VOLUME RENDERING |
|
Author(s):
|
Huawei Wang, Zhiwei Ai, Yi Cao |
|
ISBN:
|
978-989-8533-38-8 |
|
Editors:
|
Katherine Blashki and Yingcai Xiao |
|
Year:
|
2015 |
|
Edition:
|
Single |
|
Keywords:
|
Load Balancing, Information Entropy, Parallel Volume Rendering, View Independence. |
|
Type:
|
Full Paper |
|
First Page:
|
163 |
|
Last Page:
|
169 |
|
Language:
|
English |
|
Cover:
|
|
|
Full Contents:
|
click to dowload 
|
|
Paper Abstract:
|
Aiming at TB-scale time-varying scientific datasets, this paper presents a novel static load balancing scheme based on information entropy to enhance the efficiency of the parallel adaptive volume rendering algorithm. An information-theory model is proposed firstly, and then the information entropy is calculated for each data patch, which is taken as a pre-estimation of the computational amount of ray sampling. According to their computational amounts, the data patches are distributed to the processing cores balancedly, and accordingly load imbalance in parallel rendering is decreased. Compared with the existing methods such as random assignment and ray estimation, the proposed entropy-based load balancing scheme can achieve a rendering speedup ratio of 1.23~2.84. It is the best choice in interactive volume rendering due to its speedup performance and view independence. |
|
|
|
|
|
|
