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Statements

Subject Item
n2:RIV%2F68407700%3A21110%2F06%3A03116279%21RIV07-AV0-21110___
rdf:type
skos:Concept n13:Vysledek
dcterms:description
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. Tento příspěvek popisuje možnosti analýzy počtu výpadků ve skryté paměti pomocí těžby z dat. 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.
dcterms:title
Cache Misses Analysis by Means of Data Mining Methods Analýza počtu výpadků ve skryté paměti pomocí těžby z dat Cache Misses Analysis by Means of Data Mining Methods
skos:prefLabel
Analýza počtu výpadků ve skryté paměti pomocí těžby z dat Cache Misses Analysis by Means of Data Mining Methods Cache Misses Analysis by Means of Data Mining Methods
skos:notation
RIV/68407700:21110/06:03116279!RIV07-AV0-21110___
n3:aktivita
n12:P
n3:aktivity
P(IBS3086102)
n3:dodaniDat
n16:2007
n3:domaciTvurceVysledku
n18:3481131 n18:1266500
n3:druhVysledku
n14:A
n3:duvernostUdaju
n4:S
n3:entitaPredkladatele
n10:predkladatel
n3:idSjednocenehoVysledku
467602
n3:idVysledku
RIV/68407700:21110/06:03116279
n3:jazykVysledku
n19:eng
n3:klicovaSlova
bayes classifiers; cache model; data mining; decision trees; neural networks
n3:klicoveSlovo
n7:bayes%20classifiers n7:cache%20model n7:neural%20networks n7:data%20mining n7:decision%20trees
n3:kodPristupu
n17:L
n3:kontrolniKodProRIV
[64B18BA97F31]
n3:mistoVydani
Praha
n3:nosic
neuvedeno
n3:obor
n9:IN
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
2
n3:projekt
n15:IBS3086102
n3:rokUplatneniVysledku
n16:2006
n3:tvurceVysledku
Kordík, Pavel Šimeček, Ivan
n11:isbn
80-01-03439-9
n6:organizacniJednotka
21110