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ICML
2009
IEEE
16 years 5 months ago
Large-scale deep unsupervised learning using graphics processors
The promise of unsupervised learning methods lies in their potential to use vast amounts of unlabeled data to learn complex, highly nonlinear models with millions of free paramete...
Rajat Raina, Anand Madhavan, Andrew Y. Ng
HPCA
2008
IEEE
16 years 4 months ago
Roughness of microarchitectural design topologies and its implications for optimization
Recent advances in statistical inference and machine learning close the divide between simulation and classical optimization, thereby enabling more rigorous and robust microarchit...
Benjamin C. Lee, David M. Brooks
ISORC
2008
IEEE
15 years 10 months ago
A Hierarchical Resource Management Scheme Enabled by the TMO Programming Scheme
Abstract: For cost-effective realization of sizable realtime distributed computing application systems, significant advances in resource allocation are in critical needs. An advanc...
K. H. (Kane) Kim, Yuqing Li, Kee-Wook Rim, Eltefaa...
EGPGV
2004
Springer
143views Visualization» more  EGPGV 2004»
15 years 9 months ago
Massive Data Pre-Processing with a Cluster Based Approach
Data coming from complex simulation models reach easily dimensions much greater than available computational resources. Visualization of such data still represents the most intuit...
Rita Borgo, Valerio Pascucci, Roberto Scopigno
IPPS
2009
IEEE
15 years 11 months ago
Singular value decomposition on GPU using CUDA
Linear algebra algorithms are fundamental to many computing applications. Modern GPUs are suited for many general purpose processing tasks and have emerged as inexpensive high per...
Sheetal Lahabar, P. J. Narayanan