[pypy-commit] extradoc extradoc: more consistent and descriptive naming of the benachmarks

[hakanardo]

Author: Hakan Ardo <hakan at debian.org>
Branch: extradoc
Changeset: r3757:40ec1352ad94
Date: 2011-06-20 19:33 +0200
http://bitbucket.org/pypy/extradoc/changeset/40ec1352ad94/

Log:	more consistent and descriptive naming of the benachmarks

diff --git a/talk/iwtc11/paper.tex b/talk/iwtc11/paper.tex
--- a/talk/iwtc11/paper.tex
+++ b/talk/iwtc11/paper.tex
@@ -826,12 +826,64 @@
 its use.
 
 XXX we either need to explain that we use C++ or consistently use C
+\begin{figure*}
+\begin{center}
+{\smaller
+\begin{tabular}{|l|r|r|r|r|r|r|}
+\hline
+ & CPython & Psyco & PyPy no LP & PyPy & GCC -O2 & GCC -O3\\
+\hline
+%NoBorder & 537.31 & 329.98 & 2.22 $\pm$ 0.03 & 2.17 $\pm$ 0.02 & - & -\\
+%\hline
+%NoBorder(iter) & 548.32 & 304.13 & 1.45 $\pm$ 0.03 & 1.47 $\pm$ 0.02 & - & -\\
+%\hline
+%NoBorder(range) & 534.64 & 317.34 & 1.34 $\pm$ 0.03 & 1.40 $\pm$ 0.04 & - & -\\
+%\hline
+conv3x3(NoBorderPadded(1000x1000)) & 543.73 & 333.20 & 2.09 $\pm$ 0.12 & 1.93 $\pm$ 0.05 & - & -\\
+\hline
+%NoBorderPadded(iter) & 546.70 & 309.32 & 1.21 $\pm$ 0.02 & 0.49 $\pm$ 0.02 & - & -\\
+%\hline
+%NoBorderPadded(range) & 550.92 & 318.33 & 1.12 $\pm$ 0.03 & 0.48 $\pm$ 0.01 & - & -\\
+%\hline
+conv3(array(1e5)) & 77.89 & 9.52 & 1.77 $\pm$ 0.06 & 0.68 $\pm$ 0.02 & 0.70 $\pm$ 0.05 & 0.59 $\pm$ 0.01\\
+\hline
+conv3(array(1e6)) & 77.15 & 9.58 & 1.69 $\pm$ 0.01 & 0.77 $\pm$ 0.01 & 0.84 $\pm$ 0.05 & 0.74 $\pm$ 0.01\\
+\hline
+conv3x3(Array2D(1000x1000)) & 23.72 & 12.77 & 0.07 $\pm$ 0.00 & 0.05 $\pm$ 0.03 & 0.24 $\pm$ 0.00 & 0.25 $\pm$ 0.01\\
+\hline
+conv3x3(Array2D(1000x3)) & 23.85 & 12.77 & 0.10 $\pm$ 0.00 & 0.07 $\pm$ 0.00 & 0.27 $\pm$ 0.01 & 0.27 $\pm$ 0.01\\
+\hline
+conv5(array(1e5)) & 122.54 & 16.67 & 1.86 $\pm$ 0.02 & 1.05 $\pm$ 0.03 & 1.03 $\pm$ 0.05 & 0.65 $\pm$ 0.01\\
+\hline
+conv5(array(1e6)) & 125.77 & 16.80 & 1.92 $\pm$ 0.03 & 1.09 $\pm$ 0.02 & 1.07 $\pm$ 0.05 & 0.80 $\pm$ 0.01\\
+\hline
+dilate3x3(Array2D(1000x1000)) & 23.29 & 12.99 & 0.41 $\pm$ 0.04 & 0.39 $\pm$ 0.01 & 0.26 $\pm$ 0.00 & 0.26 $\pm$ 0.01\\
+\hline
+sobel(NoBorderPadded(1000x1000)) & 461.14 & 258.02 & 1.01 $\pm$ 0.03 & 0.48 $\pm$ 0.03 & - & -\\
+\hline
+sobel(Array2D(1000x1000)) & - & - & - & - & 0.19 $\pm$ 0.01 & 0.20 $\pm$ 0.01\\
+\hline
+%sobel\_uint8(NoBorderPadded) & 476.72 & 275.50 & 1.05 $\pm$ 0.01 & 0.51 $\pm$ 0.00 & - & -\\
+%\hline
+sqrt(Fix16) & 744.35 & 421.65 & 3.93 $\pm$ 0.11 & 2.14 $\pm$ 0.02 & 0.97 $\pm$ 0.02 & 0.96 $\pm$ 0.01\\
+\hline
+sqrt(float) & 24.21 & 5.52 & 1.36 $\pm$ 0.03 & 1.00 $\pm$ 0.00 & 0.98 $\pm$ 0.00 & 0.98 $\pm$ 0.00\\
+\hline
+sqrt(int) & 20.84 & 1.78 & 2.26 $\pm$ 0.01 & 1.82 $\pm$ 0.01 & 0.81 $\pm$ 0.01 & 0.80 $\pm$ 0.01\\
+\hline
+
+\end{tabular}
+}
+\end{center}
+\label{fig:benchmarks}
+\caption{XXX}
+\end{figure*}
 
 \subsection{Python}
 The Python interpreter of the PyPy framework is a complete Python
 version 2.7 compatible interpreter. A set of numerical
 calculations were implemented in both Python and in C and their
-runtimes compared. The benchmarks are
+runtimes are compared in Figure~\ref{fig:benchmarks}. The benchmarks are
 \begin{itemize}
 \item {\bf sqrt}: approximates the square root of $y$ as $x_\infty$
   with $x_0=y/2$ and $x_k = \left( x_{k-1} + y/x_{k-1} \right) /
@@ -906,56 +958,6 @@
 the relative immaturity of PyPy's JIT assembler backend as well as missing
 optimizations, like instruction scheduling. Results:
 
-\begin{figure}
-\begin{center}
-{\smaller
-\begin{tabular}{|l|r|r|r|r|r|r|}
-\hline
- & CPython & Psyco & PyPy no LP & PyPy & GCC -O2 & GCC -O3\\
-\hline
-NoBorder & 537.31 & 329.98 & 2.22 $\pm$ 0.03 & 2.17 $\pm$ 0.02 & - & -\\
-\hline
-NoBorder(iter) & 548.32 & 304.13 & 1.45 $\pm$ 0.03 & 1.47 $\pm$ 0.02 & - & -\\
-\hline
-NoBorder(range) & 534.64 & 317.34 & 1.34 $\pm$ 0.03 & 1.40 $\pm$ 0.04 & - & -\\
-\hline
-NoBorderPadded & 543.73 & 333.20 & 2.09 $\pm$ 0.12 & 1.93 $\pm$ 0.05 & - & -\\
-\hline
-NoBorderPadded(iter) & 546.70 & 309.32 & 1.21 $\pm$ 0.02 & 0.49 $\pm$ 0.02 & - & -\\
-\hline
-NoBorderPadded(range) & 550.92 & 318.33 & 1.12 $\pm$ 0.03 & 0.48 $\pm$ 0.01 & - & -\\
-\hline
-conv3(1e5) & 77.89 & 9.52 & 1.77 $\pm$ 0.06 & 0.68 $\pm$ 0.02 & 0.70 $\pm$ 0.05 & 0.59 $\pm$ 0.01\\
-\hline
-conv3(1e6) & 77.15 & 9.58 & 1.69 $\pm$ 0.01 & 0.77 $\pm$ 0.01 & 0.84 $\pm$ 0.05 & 0.74 $\pm$ 0.01\\
-\hline
-conv3x3(1000) & 23.72 & 12.77 & 0.07 $\pm$ 0.00 & 0.05 $\pm$ 0.03 & 0.24 $\pm$ 0.00 & 0.25 $\pm$ 0.01\\
-\hline
-conv3x3(3) & 23.85 & 12.77 & 0.10 $\pm$ 0.00 & 0.07 $\pm$ 0.00 & 0.27 $\pm$ 0.01 & 0.27 $\pm$ 0.01\\
-\hline
-conv5(1e5) & 122.54 & 16.67 & 1.86 $\pm$ 0.02 & 1.05 $\pm$ 0.03 & 1.03 $\pm$ 0.05 & 0.65 $\pm$ 0.01\\
-\hline
-conv5(1e6) & 125.77 & 16.80 & 1.92 $\pm$ 0.03 & 1.09 $\pm$ 0.02 & 1.07 $\pm$ 0.05 & 0.80 $\pm$ 0.01\\
-\hline
-dilate3x3(1000) & 23.29 & 12.99 & 0.41 $\pm$ 0.04 & 0.39 $\pm$ 0.01 & 0.26 $\pm$ 0.00 & 0.26 $\pm$ 0.01\\
-\hline
-sobel(NoBorderPadded) & 461.14 & 258.02 & 1.01 $\pm$ 0.03 & 0.48 $\pm$ 0.03 & - & -\\
-\hline
-sobel\_magnitude & - & - & - & - & 0.19 $\pm$ 0.01 & 0.20 $\pm$ 0.01\\
-\hline
-%sobel\_uint8(NoBorderPadded) & 476.72 & 275.50 & 1.05 $\pm$ 0.01 & 0.51 $\pm$ 0.00 & - & -\\
-\hline
-sqrt(Fix16) & 744.35 & 421.65 & 3.93 $\pm$ 0.11 & 2.14 $\pm$ 0.02 & 0.97 $\pm$ 0.02 & 0.96 $\pm$ 0.01\\
-\hline
-sqrt(float) & 24.21 & 5.52 & 1.36 $\pm$ 0.03 & 1.00 $\pm$ 0.00 & 0.98 $\pm$ 0.00 & 0.98 $\pm$ 0.00\\
-\hline
-sqrt(int) & 20.84 & 1.78 & 2.26 $\pm$ 0.01 & 1.82 $\pm$ 0.01 & 0.81 $\pm$ 0.01 & 0.80 $\pm$ 0.01\\
-\hline
-
-\end{tabular}
-}
-\end{center}
-\end{figure}
 
 
 XXX add a small note somewhere that numpy and prolog are helped by this