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» Sparse matrix factorization on massively parallel computers
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SIAMSC
2010
210views more  SIAMSC 2010»
14 years 4 months ago
On Two-Dimensional Sparse Matrix Partitioning: Models, Methods, and a Recipe
We consider two-dimensional partitioning of general sparse matrices for parallel sparse matrix-vector multiply operation. We present three hypergraph-partitioning-based methods, ea...
Ümit V. Çatalyürek, Cevdet Aykana...
TCSV
2010
14 years 4 months ago
High Performance Stereo Vision Designed for Massively Data Parallel Platforms
Abstract--Real-time stereo vision is attractive in many applications like robot navigation and 3D scene reconstruction. Data parallel platforms, e.g. GPU, is often used for real-ti...
Wei Yu, Tsuhan Chen, Franz Franchetti, James C. Ho...
EMMCVPR
2005
Springer
15 years 3 months ago
Reverse-Convex Programming for Sparse Image Codes
Abstract. Reverse-convex programming (RCP) concerns global optimization of a specific class of non-convex optimization problems. We show that a recently proposed model for sparse ...
Matthias Heiler, Christoph Schnörr
CVPR
2007
IEEE
15 years 11 months ago
Nonnegative Tucker Decomposition
Nonnegative tensor factorization (NTF) is a recent multiway (multilinear) extension of nonnegative matrix factorization (NMF), where nonnegativity constraints are imposed on the C...
Yong-Deok Kim, Seungjin Choi
HPCC
2005
Springer
15 years 3 months ago
Fast Sparse Matrix-Vector Multiplication by Exploiting Variable Block Structure
Abstract. We improve the performance of sparse matrix-vector multiplication (SpMV) on modern cache-based superscalar machines when the matrix structure consists of multiple, irregu...
Richard W. Vuduc, Hyun-Jin Moon