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» Automatic parallelization for graphics processing units
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EGH
2010
Springer
13 years 5 months ago
Hardware implementation of micropolygon rasterization with motion and defocus blur
Current GPUs rasterize micropolygons (polygons approximately one pixel in size) inefficiently. Additionally, they do not natively support triangle rasterization with jittered samp...
J. S. Brunhaver, Kayvon Fatahalian, Pat Hanrahan
SIGMOD
2008
ACM
116views Database» more  SIGMOD 2008»
14 years 7 months ago
SPADE: the system s declarative stream processing engine
In this paper, we present Spade - the System S declarative stream processing engine. System S is a large-scale, distributed data stream processing middleware under development at ...
Bugra Gedik, Henrique Andrade, Kun-Lung Wu, Philip...
HIPC
2007
Springer
14 years 1 months ago
Accelerating Large Graph Algorithms on the GPU Using CUDA
Abstract. Large graphs involving millions of vertices are common in many practical applications and are challenging to process. Practical-time implementations using high-end comput...
Pawan Harish, P. J. Narayanan
CIDM
2011
IEEE
12 years 11 months ago
A GPU-based interactive bio-inspired visual clustering
Abstract—In this work, we present an interactive visual clustering approach for the exploration and analysis of vast volumes of data. The proposed approach is based on a bio-insp...
Ugo Erra, Bernardino Frola, Vittorio Scarano
ISCA
2010
IEEE
232views Hardware» more  ISCA 2010»
13 years 6 months ago
Evolution of thread-level parallelism in desktop applications
As the effective limits of frequency and instruction level parallelism have been reached, the strategy of microprocessor vendors has changed to increase the number of processing ...
Geoffrey Blake, Ronald G. Dreslinski, Trevor N. Mu...