Particle animation and rendering using data parallel computation

Author(s):  
Karl Sims
1995 ◽  
Vol 3 (1) ◽  
pp. 12-24 ◽  
Author(s):  
R. Ponnusamy ◽  
Yuan-Shin Hwang ◽  
R. Das ◽  
J.H. Saltz ◽  
A. Choudhary ◽  
...  

2013 ◽  
Vol 385-386 ◽  
pp. 1804-1807
Author(s):  
Shi Ji Yuan ◽  
Ming Feng Sun ◽  
Zhi Hua Liu ◽  
Wen Jing Huang

The classical Montgomery ladder algorithm (MPL) is an effective way to improve the operational efficiency of elliptic curve cryptography. First, an improved MPL is proposed by loop unrolling, and then the Montgomery elliptic curve encryption and decryption process is realized using data parallel and task parallel. The experimental results show that the ratio of acceleration parallel processing efficiency can reach 70%, and the method can effectively improve the speed of elliptic curve encryption algorithm.


Author(s):  
Y. ANSEL TENG ◽  
DANIEL DEMENTHON ◽  
LARRY S. DAVIS

In this paper, we propose a method for solving visibility-based terrain path planning problems for groups of vehicles using data parallel machines. The discussion focuses on path planning for two groups of vehicles so that they move in a bounding overwatch manner. Furthermore, the planned paths for the vehicles themselves are subject to intervisibility constraints, configuration constraints, and different terrain traversabilities due to variations in terrain type and slope. A spatial-temporal sampling approach is adopted to discretize the solution space and facilitate fast computation on a data parallel machine. One of the key computations in the planning is the region-to-region visibility analysis, which is computationally expensive but essential to the choice of subgoals to carry out reconnaissance activities. A parallel algorithm for this analysis is developed. By reducing the communication complexity, our algorithm achieves much faster running time than traditional methods. The algorithms are implemented on a Connection Machine CM-2, and the experimental results show that the planning system effectively generates good paths.


1999 ◽  
Vol 70 (4) ◽  
pp. 197-204 ◽  
Author(s):  
Kuo-Chan Huang ◽  
Feng-Jian Wang ◽  
Jyun-Hwei Tsai

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