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» Order reduction of large scale DAE models
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DAC
2007
ACM
14 years 8 months ago
Beyond Low-Order Statistical Response Surfaces: Latent Variable Regression for Efficient, Highly Nonlinear Fitting
The number and magnitude of process variation sources are increasing as we scale further into the nano regime. Today's most successful response surface methods limit us to lo...
Amith Singhee, Rob A. Rutenbar
ISQED
2006
IEEE
147views Hardware» more  ISQED 2006»
14 years 1 months ago
Compact Reduced Order Modeling for Multiple-Port Interconnects
— In this paper, we propose an efficient model order reduction (MOR) algorithm, called MTermMOR, for modeling interconnect circuits with large number of external ports. The prop...
Pu Liu, Sheldon X.-D. Tan, Bruce McGaughy, Lifeng ...
ICS
2010
Tsinghua U.
13 years 10 months ago
Clustering performance data efficiently at massive scales
Existing supercomputers have hundreds of thousands of processor cores, and future systems may have hundreds of millions. Developers need detailed performance measurements to tune ...
Todd Gamblin, Bronis R. de Supinski, Martin Schulz...
SIAMSC
2010
120views more  SIAMSC 2010»
13 years 5 months ago
Weighted Matrix Ordering and Parallel Banded Preconditioners for Iterative Linear System Solvers
The emergence of multicore architectures and highly scalable platforms motivates the development of novel algorithms and techniques that emphasize concurrency and are tolerant of ...
Murat Manguoglu, Mehmet Koyutürk, Ahmed H. Sa...
KDD
2012
ACM
271views Data Mining» more  KDD 2012»
11 years 10 months ago
GigaTensor: scaling tensor analysis up by 100 times - algorithms and discoveries
Many data are modeled as tensors, or multi dimensional arrays. Examples include the predicates (subject, verb, object) in knowledge bases, hyperlinks and anchor texts in the Web g...
U. Kang, Evangelos E. Papalexakis, Abhay Harpale, ...