scholarly journals A pipelined data-parallel algorithm for ILP

2005 ◽  
Author(s):  
Nuno A. Fonseca ◽  
Fernando Silva ◽  
Vitor Santos Costa ◽  
Rui Camacho
Keyword(s):  
Parallel Algorithm ◽  
Data Parallel

Data parallel algorithm for kirchhoff 3‐D DMO

1992 ◽  
Author(s):  
Biondo Biondi ◽  
W. D. Moorhead
Keyword(s):  
Parallel Algorithm ◽  
Data Parallel

Gordius: A data parallel algorithm for spatial data conversion

1993 ◽  
Vol 19 (7) ◽  
pp. 1051-1063 ◽  
Author(s):  
Kim Mills ◽  
Ferenc Csillag ◽  
Maher Kaddoura
Keyword(s):  
Parallel Algorithm ◽  
Spatial Data ◽  
Data Conversion ◽  
Data Parallel

PDAC: A data parallel algorithm for the performance analysis of closed queueing networks

1993 ◽  
Vol 19 (12) ◽  
pp. 1345-1358 ◽  
Author(s):  
F.B Hanson ◽  
Jing-Dong Mei ◽  
Charles Tier ◽  
Huihuang Xu
Keyword(s):  
Performance Analysis ◽  
Parallel Algorithm ◽  
Queueing Networks ◽  
Closed Queueing Networks ◽  
Data Parallel

scholarly journals Data-Parallel Algorithm for Contour Tree Construction

2017 ◽  
Author(s):  
Christopher Meyer Sewell ◽  
James Paul Ahrens ◽  
Hamish Carr ◽  
Gunther Weber
Keyword(s):  
Parallel Algorithm ◽  
Data Parallel ◽  
Tree Construction ◽  
Contour Tree

Efficient Data-Parallel Algorithm for Elevation Color Generation in Terrain Rendering

2012 ◽  
Vol 155-156 ◽  
pp. 37-41 ◽  
Author(s):  
Zheng Kang Zhou ◽  
Jian Wang ◽  
Hua Cheng Zhao
Keyword(s):  
Parallel Algorithm ◽  
Three Dimensional ◽  
Terrain Rendering ◽  
Application Performance ◽  
Root Cause ◽  
Data Parallel ◽  
Efficient Data ◽  
Parallel Mode ◽  
Simulation Results ◽  
Modified Algorithm

With the ever increasing resolution of scanned elevations, the efficiency of terrain rendering is still unsatisfactory in three-dimensional visualization. In order to improve the speed of terrain rendering, we had studied the root cause of the undesirable visualization efficiency in Visual Terrain Project, and found that one of the performance limitations was elevation color generation step. Therefore, we proposed a modified algorithm on the basis of data parallel mode, which can be well performed on GPU. Experimental results show that application performance is raised significantly by data parallel algorithm, and the improved algorithm can obtain satisfactory simulation results via CUDA.

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