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Commented out the Krki benchmarks.

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git-svn-id: https://yap.svn.sf.net/svnroot/yap/trunk@1837 b08c6af1-5177-4d33-ba66-4b1c6b8b522a
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kostis 2007-03-11 23:30:00 +00:00
parent 9ec9b7fb70
commit 974d481661
1 changed files with 27 additions and 26 deletions
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docs/index/iclp07.tex
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@ -53,8 +53,8 @@
\newcommand{\Choline}{\bench{Choline}\xspace} \newcommand{\Choline}{\bench{Choline}\xspace}
\newcommand{\GeneExpr}{\bench{GeneExpression}\xspace} \newcommand{\GeneExpr}{\bench{GeneExpression}\xspace}
\newcommand{\IEProtein}{\bench{IE-Protein\_Extraction}\xspace} \newcommand{\IEProtein}{\bench{IE-Protein\_Extraction}\xspace}
\newcommand{\Krki}{\bench{Krki}\xspace} %\newcommand{\Krki}{\bench{Krki}\xspace}
\newcommand{\KrkiII}{\bench{Krki~II}\xspace} %\newcommand{\KrkiII}{\bench{Krki~II}\xspace}
\newcommand{\Mesh}{\bench{Mesh}\xspace} \newcommand{\Mesh}{\bench{Mesh}\xspace}
\newcommand{\Pyrimidines}{\bench{Pyrimidines}\xspace} \newcommand{\Pyrimidines}{\bench{Pyrimidines}\xspace}
\newcommand{\Susi}{\bench{Susi}\xspace} \newcommand{\Susi}{\bench{Susi}\xspace}
@ -1129,9 +1129,8 @@ data, so memory consumption is a reasonable concern. We evaluate
JITI's time and space performance on some learning tasks using the JITI's time and space performance on some learning tasks using the
ALEPH system~\cite{ALEPH}. We use the following datasets: ALEPH system~\cite{ALEPH}. We use the following datasets:
% %
% Table~\ref{tab:ilp:time} shows JITI performance. %% \Krki which tries to learn rules from a small database of chess end-games;
The dataset \Krki tries to learn rules from a \GeneExpr which learns rules for
small database of chess end-games; \GeneExpr learns rules for
yeast gene activity given a database of genes, their interactions, and yeast gene activity given a database of genes, their interactions, and
micro-array gene expression data; \BreastCancer processes real-life micro-array gene expression data; \BreastCancer processes real-life
patient reports towards predicting whether an abnormality may be patient reports towards predicting whether an abnormality may be
@ -1160,17 +1159,17 @@ queries in an extensional database.
\cline{2-4} \cline{2-4}
Benchmark & 1st & JITI &{\bf ratio} \\ Benchmark & 1st & JITI &{\bf ratio} \\
\hline \hline
\BreastCancer & 1,450 & 88 & 16 \\ \BreastCancer & 1,450 & 88 & $16$ \\
\Carcino & 17,705 & 192 & 92 \\ \Carcino & 17,705 & 192 & $92$ \\
\Choline & 14,766 & 1,397 & 11 \\ \Choline & 14,766 & 1,397 & $11$ \\
\GeneExpr & 193,283 & 7,483 & 26 \\ \GeneExpr & 193,283 & 7,483 & $26$ \\
\IEProtein & 1,677,146 & 2,909 & 577 \\ \IEProtein & 1,677,146 & 2,909 & $577$ \\
\Krki & 0.3 & 0.3 & 1 \\ %% \Krki & 0.3 & 0.3 & $1$ \\
\KrkiII & 1.3 & 1.3 & 1 \\ %% \KrkiII & 1.3 & 1.3 & $1$ \\
\Mesh & 4 & 3 & 1.3 \\ \Mesh & 4 & 3 & $1.3$ \\
\Pyrimidines & 487,545 & 253,235 & 1.9 \\ \Pyrimidines & 487,545 & 253,235 & $1.9$ \\
\Susi & 105,091 & 307 & 342 \\ \Susi & 105,091 & 307 & $342$ \\
\Thermolysin & 50,279 & 5,213 & 10 \\ \Thermolysin & 50,279 & 5,213 & $10$ \\
\hline \hline
\end{tabular} \end{tabular}
} }
@ -1187,8 +1186,8 @@ queries in an extensional database.
666 & 174 & 3,172 & 174 \\ 666 & 174 & 3,172 & 174 \\
46,726 & 22,629 & 116,463 & 9,015 \\ 46,726 & 22,629 & 116,463 & 9,015 \\
146,033 & 129,333 & 53,423 & 1,531 \\ 146,033 & 129,333 & 53,423 & 1,531 \\
678 & 117 & 2,047 & 24 \\ %% 678 & 117 & 2,047 & 24 \\
1,866 & 715 & 2,055 & 26 \\ %% 1,866 & 715 & 2,055 & 26 \\
802 & 161 & 2,149 & 109 \\ 802 & 161 & 2,149 & 109 \\
774 & 218 & 25,840 & 12,291 \\ 774 & 218 & 25,840 & 12,291 \\
5,007 & 2,509 & 4,497 & 759 \\ 5,007 & 2,509 & 4,497 & 759 \\
@ -1200,12 +1199,14 @@ queries in an extensional database.
%------------------------------------------------------------------------------ %------------------------------------------------------------------------------
We compare times for 10 runs of the saturation/refinement cycle of the We compare times for 10 runs of the saturation/refinement cycle of the
ILP system. Table~\ref{tab:ilp:time} shows time results. The \Krki ILP system. Table~\ref{tab:ilp:time} shows time results.
datasets have small search spaces and small databases, so they achieve %% The \Krki datasets have small search spaces and small databases, so
the same performance under both versions: there is no slowdown. The %% they achieve the same performance under both versions: there is no
\Mesh and \Pyrimidines applications do not benefit much from indexing %% slowdown.
in the database, but they do benefit from indexing in the dynamic The \Mesh and \Pyrimidines applications do not benefit much from
representation of the search space, as their running times halve. indexing in the database, but they do benefit from indexing in the
dynamic representation of the search space, as their running times
halve.
The \BreastCancer and \GeneExpr applications use data in The \BreastCancer and \GeneExpr applications use data in
1NF (that is, unstructured data). The benefit here is mostly from 1NF (that is, unstructured data). The benefit here is mostly from
@ -1234,7 +1235,7 @@ Because dynamic memory expands and contracts, we chose a point where
memory usage should be at a maximum. The first two numbers show data memory usage should be at a maximum. The first two numbers show data
usage on \emph{static} predicates. Static data-base sizes range from usage on \emph{static} predicates. Static data-base sizes range from
146MB (\bench{IE-Protein\_Extraction} to less than a MB 146MB (\bench{IE-Protein\_Extraction} to less than a MB
(\bench{Choline}, \bench{Krki}, \bench{Mesh}). Indexing code can grow (\bench{Choline} and \bench{Mesh}). Indexing code can grow
to be as large as than the original code, as in \Carcino, or to be as large as than the original code, as in \Carcino, or
almost as much, e.g., \bench{IE-Protein\_Extraction}. In most cases almost as much, e.g., \bench{IE-Protein\_Extraction}. In most cases
the YAP \JITI adds at least a third and often a half to the original the YAP \JITI adds at least a third and often a half to the original
@ -1250,7 +1251,7 @@ usage, but is never dominant.
This version of ALEPH uses the internal data-base to store the IDB. This version of ALEPH uses the internal data-base to store the IDB.
The size of reflects the search space, and is to some extent The size of reflects the search space, and is to some extent
independent of the program's static data, although small applications independent of the program's static data, although small applications
such as \bench{Krki} tend to have a small search space. ALEPH's such as \Mesh tend to have a small search space. ALEPH's
author very carefully designed the system to work around overheads in author very carefully designed the system to work around overheads in
accessing the database, so indexing should not be as critical. The accessing the database, so indexing should not be as critical. The
low overheads suggest that \JITI is working well, as confirmed in low overheads suggest that \JITI is working well, as confirmed in