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» Run-Time Techniques for Parallelizing Sparse Matrix Problems
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CORR
2004
Springer
152views Education» more  CORR 2004»
13 years 7 months ago
Non-negative matrix factorization with sparseness constraints
Non-negative matrix factorization (NMF) is a recently developed technique for finding parts-based, linear representations of non-negative data. Although it has successfully been a...
Patrik O. Hoyer
WCE
2007
13 years 8 months ago
Sparse Matrix Multiplication Using UPC
—Partitioned global address space (PGAS) languages, such as Unified Parallel C (UPC) have the promise of being productive. Due to the shared address space view that they provide,...
Hoda El-Sayed, Eric Wright
FPGA
2005
ACM
195views FPGA» more  FPGA 2005»
14 years 1 months ago
Sparse Matrix-Vector multiplication on FPGAs
Floating-point Sparse Matrix-Vector Multiplication (SpMXV) is a key computational kernel in scientific and engineering applications. The poor data locality of sparse matrices sig...
Ling Zhuo, Viktor K. Prasanna
ACPC
1999
Springer
13 years 12 months ago
Non-standard Parallel Solution Strategies for Distributed Sparse Linear Systems
Abstract. A number of techniques are described for solving sparse linear systems on parallel platforms. The general approach used is a domaindecomposition type method in which a pr...
Yousef Saad, Masha Sosonkina
SIAMSC
2011
140views more  SIAMSC 2011»
12 years 10 months ago
A Fast Parallel Algorithm for Selected Inversion of Structured Sparse Matrices with Application to 2D Electronic Structure Calcu
Abstract. An efficient parallel algorithm is presented and tested for computing selected components of H−1 where H has the structure of a Hamiltonian matrix of two-dimensional la...
Lin Lin, Chao Yang, Jianfeng Lu, Lexing Ying, Wein...