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» Automatic parallelization for graphics processing units
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AIPR
2008
IEEE
13 years 9 months ago
Low-cost, high-speed computer vision using NVIDIA's CUDA architecture
In this paper, we introduce real time image processing techniques using modern programmable Graphic Processing Units (GPU). GPUs are SIMD (Single Instruction, Multiple Data) device...
Seung In Park, Sean P. Ponce, Jing Huang, Yong Cao...
SIGMOD
2010
ACM
255views Database» more  SIGMOD 2010»
14 years 13 days ago
Large graph processing in the cloud
As the study of graphs, such as web and social graphs, becomes increasingly popular, the requirements of efficiency and programming flexibility of large graph processing tasks c...
Rishan Chen, Xuetian Weng, Bingsheng He, Mao Yang
TIP
2010
90views more  TIP 2010»
13 years 2 months ago
Fast Query for Exemplar-Based Image Completion
In this paper, we present a fast algorithm for filling unknown regions in an image using the strategy of exemplarmatching. Unlike the original exemplar-based method using exhaustiv...
Tsz-Ho Kwok, Hoi Sheung, Charlie C. L. Wang
ASPDAC
1995
ACM
116views Hardware» more  ASPDAC 1995»
13 years 11 months ago
A datapath synthesis system for the reconfigurable datapath architecture
Abstract — A datapath synthesis system (DPSS) for the reconfigurable datapath architecture (rDPA) is presented. The DPSS allows automatic mapping of high level descriptions onto...
Reiner W. Hartenstein, Rainer Kress
ICFP
2012
ACM
11 years 10 months ago
Nested data-parallelism on the gpu
Graphics processing units (GPUs) provide both memory bandwidth and arithmetic performance far greater than that available on CPUs but, because of their Single-Instruction-Multiple...
Lars Bergstrom, John H. Reppy