NAA'04
- Numerical Algorithms & Applications
Performance optimization and evaluation for
linear codes
Authors: Ivan Šimeček and Pavel Tvrdík
Keywords
High-performance, Ccahe model, numerical linear algebra.
Abstract
In this paper, we develop a probabilistic models for estimation of the
numbers of cache misses during the sparse matrix-vector multiplication
(for both general and symmetric matrices) and the Conjugate
Gradient algorithm for 3 types of data caches: direct mapped, s-way set
associative with random or with LRU replacement strategies. Using HW
cache monitoring tools, we compare the predicted number of cache misses
with real numbers on Intel x86 architecture with L1 and L2 caches. The
accuracy of our analytical models is above 95%.
Download:
final version (in .PDF format)
BibTex entry:
@inproceedings{JA_NAA,
author = "P. Tvrd\'{\i}k and
I. \v{S}ime\v{c}ek",
title = "Analytical
modeling of sparse linear code",
journal = "Numerical Analysis and
Applications",
volume = "3",
number= "4",
pages = "617-629",
year = "2004",
Address = "Rousse, Bulgaria"
}
