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» Multi-dimensional Sparse Matrix Storage
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KDD
2012
ACM
271views Data Mining» more  KDD 2012»
11 years 7 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, ...
IAJIT
2011
13 years 6 days ago
Blocked-based sparse matrix-vector multiplication on distributed memory parallel computers
: The present paper discusses the implementations of sparse matrix-vector products, which are crucial for high performance solutions of large-scale linear equations, on a PC-Cluste...
Rukhsana Shahnaz, Anila Usman
ICCS
2005
Springer
13 years 10 months ago
Vectorized Sparse Matrix Multiply for Compressed Row Storage Format
Abstract. The innovation of this work is a simple vectorizable algorithm for performing sparse matrix vector multiply in compressed sparse row (CSR) storage format. Unlike the vect...
Eduardo F. D'Azevedo, Mark R. Fahey, Richard Tran ...
ICS
1997
Tsinghua U.
13 years 9 months ago
Sparse Code Generation for Imperfectly Nested Loops with Dependences
Standard restructuring compiler tools are based on polyhedral algebra and cannot be used to analyze or restructure sparse matrix codes. We have recently shown that tools based on ...
Vladimir Kotlyar, Keshav Pingali
PARA
2004
Springer
13 years 10 months ago
Optimization of a Statically Partitioned Hypermatrix Sparse Cholesky Factorization
The sparse Cholesky factorization of some large matrices can require a two dimensional partitioning of the matrix. The sparse hypermatrix storage scheme produces a recursive 2D par...
José R. Herrero, Juan J. Navarro