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» Parallel computing with CUDA
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LCPC
2009
Springer
15 years 10 months ago
MIMD Interpretation on a GPU
Programming heterogeneous parallel computer systems is notoriously difficult, but MIMD models have proven to be portable across multi-core processors, clusters, and massively paral...
Henry G. Dietz, B. Dalton Young
171
Voted
ASPLOS
2009
ACM
16 years 18 days ago
Performance analysis of accelerated image registration using GPGPU
This paper presents a performance analysis of an accelerated 2-D rigid image registration implementation that employs the Compute Unified Device Architecture (CUDA) programming e...
Peter Bui, Jay B. Brockman
147
Voted
OOPSLA
2010
Springer
15 years 4 months ago
Language virtualization for heterogeneous parallel computing
As heterogeneous parallel systems become dominant, application developers are being forced to turn to an incompatible mix of low level programming models (e.g. OpenMP, MPI, CUDA, ...
Hassan Chafi, Zach DeVito, Adriaan Moors, Tiark Ro...
175
Voted
CIARP
2009
Springer
16 years 12 days ago
Optimizations and Performance of a Robotics Grasping Algorithm Described in Geometric Algebra
Abstract. The usage of Conformal Geometric Algebra leads to algorithms that can be formulated in a very clear and easy to grasp way. But it can also increase the performance of an ...
Florian Wörsdörfer, Florian Stock, Eduar...
197
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ICPADS
2010
IEEE
15 years 3 months ago
GMH: A Message Passing Toolkit for GPU Clusters
Driven by the market demand for high-definition 3D graphics, commodity graphics processing units (GPUs) have evolved into highly parallel, multi-threaded, many-core processors, whi...
Jie Chen, William A. Watson III, Weizhen Mao