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Towards a Fast Parallel Sparse Matrix-Vector Multiplication (1999)  (Make Corrections)  (4 citations)
Roman Geus, Stefan Röllin
Parallel Computing: Fundamentals & Applications, Proceedings of the International Conference ParCo'99, 17-20 August 1999, Delft, The Netherlands



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Abstract: The sparse matrix-vector product is an important computational kernel that runs ineffectively on many computers with super-scalar RISC processors. In this paper we analyse the performance of the sparse matrix-vector product with symmetric matrices originating from the FEM and describe techniques that lead to a fast implementation. It is shown how these optimisations can be incorporated into an efficient parallel implementation using messagepassing. We conduct numerical experiments on many... (Update)

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...that best exploits his her sparsity structure in order to maximize cache reuse. This approach is widely used today, as in [31, 11, 37, 45, 47, 28]. The advantage of this solution is that the input format is fixed and assumed to be appropriate to the data structure, just as...

...b. This technique is called software pipelining; we reorganised our source code in such a way that the processor pipelines are better lled. In [7] this technique is analysed together with several other techniques for optimizing the performance of the matrix vector product....

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Performance Optimizations and Bounds for Sparse.. - Vuduc, Demmel, Yelick (2002)   (Correct)
Memory Hierarchy Optimizations and Performance Bounds.. - Vuduc, Gyulassy.. (2003)   (Correct)
Parallel Templates for Numerical Linear Algebra, a.. - Koster (2002)   (Correct)

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0.7:   Towards a Fast Parallel Sparse Matrix-Vector Multiplication - Geus, Röllin (1999)   (Correct)
0.2:   Self-adapting Numerical Software for Next Generation.. - Dongarra, Eijkhout (2002)   (Correct)
0.1:   Self Adapting Software for Numerical Linear Algebra.. - Chen, Dongarra.. (2003)   (Correct)

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3:   Improving memory-system performance of sparse matrix-vector multiplication - Toledo - 1997
3:   FFTW: An adaptive software architecture for the FFT - Frigo, Johnson - 1998
2:   Anwendung von generativen Programmiertechniken am Beispiel der Matrixalgebra (context) - Neubert - 1998

BibTeX entry:   (Update)

Roman Geus and Stefan Rollin. Towards A Fast Parallel Sparse Matrix-Vector Multiplication, Institute Of Scientific Computing. ETH Zurich, Submitted to World Scientific, 1999. http://citeseer.ist.psu.edu/geus99towards.html   More

@inproceedings{ geus00towards,
    author = "S. R{\"o}llin R. Geus",
    title = "Towards a fast parallel sparse matrix-vector multiplication",
    booktitle = "Parallel Computing: Fundamentals & Applications, Proceedings of the International Conference ParCo'99, 17-20 August 1999, Delft, The Netherlands",
    publisher = "Imperial College Press",
    editor = "E. H. D'Hollander and J. R. Joubert and F. J. Peters and H. Sips",
    pages = "308--315",
    year = "2000",
    url = "citeseer.ist.psu.edu/geus99towards.html" }
Citations (may not include all citations):
346   Computer Solution of Large Sparse Positive Definite Systems (context) - George, Liu - 1981
165   SPARSKIT: A basic tool kit for sparse matrix computations - Saad - 1990
157   Automatically Tuned Linear Algebra Software - Whaley, Dongarra - 1998  ACM   DBLP
124   FFTW: An adaptive software architecture for the FFT - Frigo, Johnson - 1998
25   Improving memory-system performance of sparse matrix-vector .. - Toledo - 1997  DBLP
13   Optimizing sparse matrix-vector multiplication on SMPs - Im, Yelick - 1999
11   SPARSLIB: A portable library of distributed memory sparse it.. (context) - Saad, Malevsky - 1995
2   A comparison of solvers for large eigenvalue problems occuri.. (context) - Arbenz, Geus - 1999
1   Advanced optimization for PA-8x00 processors (context) - Wadleigh, Potler - 1998

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Eigenvalue Solvers for Electromagnetic Fields in Cavities - Adam, Arbenz, Geus (1997)   (Correct)
Towards a Fast Parallel Sparse Matrix-Vector Multiplication - Geus, Röllin (1999)   (Correct)
A Comparison of Solvers for Large Eigenvalue Problems.. - Adam, Arbenz, Geus (1997)   (Correct)

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