ČVUT WORKSHOP'06

Cache Misses Analysis by Means of Data Mining Methods
Authors: Ivan Šimeček, Kordík Pavel
Keywords

Bayes classifiers,  cache model, data mining, decision trees, neural networks.


Abstract

It is really difficult to predict the cache behavior even for a simple program because every modern CPU use a complex memory hierarchy, which consists of levels of cache memories. One challenging task is to predict the exact number of cache misses during the sparse matrix-vector multiplication. Due to matrix sparsity, the memory access patterns are irregular and the utilization of a cache suffers from low spatial and temporal locality. It is really difficult to predict the cache behavior for all cases of input parameters. The cache misses data were also analyzed by means of data mining methods. This is the main topic of this paper and we will discuss the data mining analysis bellow in the more detailed form.

 

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BibTex entry:
@inproceedings{JA_WOR_06_NEURAL,
  author =       "I. \v{S}ime\v{c}ek and P.Kord\'{\i}k, ",
  title =        "Cache Misses Analysis by Means of Data Mining Methods",
  journal =      "CTU Workshop",
  pages =        "122-123",
  month =        feb,
  year =         "2006",
  isbn =         "80-01-03439-9",
  Address =      "Prague, Czech Republic"
}

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