[pypy-commit] extradoc extradoc: update the correct paper

fijal noreply at buildbot.pypy.org
Thu Aug 16 17:45:17 CEST 2012


Author: Maciej Fijalkowski <fijall at gmail.com>
Branch: extradoc
Changeset: r4627:b833da3744be
Date: 2012-08-16 17:44 +0200
http://bitbucket.org/pypy/extradoc/changeset/b833da3744be/

Log:	update the correct paper

diff --git a/talk/dls2012/paper.tex b/talk/dls2012/paper.tex
--- a/talk/dls2012/paper.tex
+++ b/talk/dls2012/paper.tex
@@ -929,35 +929,95 @@
 \begin{figure}
 \begin{center}
 {\smaller
-\begin{tabular}{|l|r|r|r|r|r|r|}
+\begin{tabular}{|l|r|r|r|r|r|r|r|}
 \hline
- & CPython & Psyco & PyPy  & PyPy & GCC \\
- &         &       & no LP &      & -O3 \\
+ & CPython & PyPy  & PyPy & GCC & luajit & luajit \\
+ &        & no LP &       & -O3 &        & no LP \\
+FFT(1024, 32768) & 469.07 & 20.83 +- 0.02 & 12.73 +- 0.01 & - & 2.76 +- 0.01 & 4.42 +- 0.01\\
 \hline
-conv3(1e5) & 77.89 & 9.52 & 1.77  & 0.68 &  0.59 \\
+FFT(1024,32768) & - & - & - & 1.40 +- 0.04 & - & -\\
 \hline
-conv3(1e6) & 77.15 & 9.58 & 1.69  & 0.77 &  0.74 \\
+FFT(1048576, 2) & 58.93 & 4.12 +- 0.01 & 2.05 +- 0.00 & - & 1.08 +- 0.01 & 1.33 +- 0.01\\
 \hline
-conv3x3(1000) & 233.54 & 125.40 & 0.57 & 0.27 & 0.25 \\
+FFT(1048576,2) & - & - & - & 0.83 +- 0.02 & - & -\\
 \hline
-conv3x3(3) & 234.45 & 126.28 & 0.60 & 0.31 & 0.28 \\
+LU(100, 4096) & 1974.14 & 32.22 +- 0.14 & 13.39 +- 0.03 & - & 1.52 +- 0.01 & 8.57 +- 0.01\\
 \hline
-conv5(1e5) & 122.54 & 16.67 & 1.86  & 1.05 &  0.65\\
+LU(100,4096) & - & - & - & 1.33 +- 0.04 & - & -\\
 \hline
-conv5(1e6) & 125.77 & 16.80 & 1.92 & 1.09 &  0.80 \\
+LU(1000, 2) & 955.31 & 14.98 +- 0.22 & 5.99 +- 0.21 & - & 0.67 +- 0.01 & 3.99 +- 0.01\\
 \hline
-dilate3x3(1000) & 232.51 & 125.85 & 3.89 & 3.69 & 0.25 \\
+LU(1000,2) & - & - & - & 0.65 +- 0.04 & - & -\\
 \hline
-sobel(1000) & 181.49 & 95.05 & 0.71 & 0.42 & 0.20 \\
+MonteCarlo(268435456) & 618.89 & 20.60 +- 0.05 & 15.33 +- 0.08 & 1.69 +- 0.05 & 2.82 +- 0.00 & 3.92 +- 0.01\\
 \hline
-sqrt(Fix16) & 744.35 & 421.65 & 3.93  & 2.14  & 0.96 \\
+SOR(100, 32768) & 1458.12 & 8.24 +- 0.00 & 2.66 +- 0.00 & - & 1.31 +- 0.01 & 2.02 +- 0.00\\
 \hline
-sqrt(float) & 24.21 & 5.52 & 1.36 & 1.00 & 0.98\\
+SOR(100,32768) & - & - & - & 1.76 +- 0.04 & - & -\\
 \hline
-sqrt(int) & 20.84 & 1.78 & 2.26 & 1.82  & 0.80 \\
+SOR(1000, 256) & 1210.45 & 6.48 +- 0.00 & 2.10 +- 0.00 & - & 1.08 +- 0.01 & 1.63 +- 0.00\\
 \hline
+SOR(1000,256) & - & - & - & 1.49 +- 0.02 & - & -\\
 \hline
-Variations & - & - & $\pm 0.03$ & $\pm 0.01$ & $\pm 0.01$ \\
+SparseMatMult(1000, 5000, 262144) & 371.66 & 24.25 +- 0.04 & 16.52 +- 0.04 & - & - & -\\
+\hline
+SparseMatMult(1000,5000,262144) & - & - & - & 1.84 +- 0.03 & 4.53 +- 0.02 & 9.64 +- 0.02\\
+\hline
+SparseMatMult(100000, 1000000, 1024) & 236.93 & 17.01 +- 0.01 & 8.75 +- 0.08 & - & - & -\\
+\hline
+SparseMatMult(100000,1000000,1024) & - & - & - & 1.20 +- 0.03 & 2.42 +- 0.01 & 7.19 +- 0.01\\
+\hline
+conv3(100, nil) & - & - & - & - & 0.18 +- 0.00 & 0.70 +- 0.00\\
+\hline
+conv3(1000, nil) & - & - & - & - & 0.12 +- 0.01 & 0.67 +- 0.01\\
+\hline
+conv3(1e5) & - & - & - & 0.52 +- 0.04 & - & -\\
+\hline
+conv3(1e6) & - & - & - & 0.60 +- 0.03 & - & -\\
+\hline
+conv3(array(1e5)) & 50.14 & 1.09 +- 0.01 & 0.49 +- 0.01 & - & - & -\\
+\hline
+conv3(array(1e6)) & 49.20 & 1.13 +- 0.02 & 0.51 +- 0.00 & - & - & -\\
+\hline
+conv3x3(1000) & - & - & - & 0.17 +- 0.04 & - & -\\
+\hline
+conv3x3(1000, 1000) & - & - & - & - & 0.09 +- 0.01 & 0.49 +- 0.01\\
+\hline
+conv3x3(1000000, 3) & - & - & - & - & 0.13 +- 0.00 & 0.53 +- 0.00\\
+\hline
+conv3x3(3) & - & - & - & 0.19 +- 0.03 & - & -\\
+\hline
+conv3x3(Array2D(1000000x3)) & 139.81 & 0.70 +- 0.00 & 0.21 +- 0.00 & - & - & -\\
+\hline
+conv3x3(Array2D(1000x1000)) & 138.95 & 0.70 +- 0.00 & 0.20 +- 0.00 & - & - & -\\
+\hline
+conv5(100, nil) & - & - & - & - & 0.21 +- 0.01 & 0.87 +- 0.01\\
+\hline
+conv5(1000, nil) & - & - & - & - & 0.17 +- 0.01 & 0.84 +- 0.00\\
+\hline
+conv5(1e5) & - & - & - & 0.55 +- 0.02 & - & -\\
+\hline
+conv5(1e6) & - & - & - & 0.58 +- 0.03 & - & -\\
+\hline
+conv5(array(1e5)) & 74.65 & 1.22 +- 0.00 & 0.64 +- 0.00 & - & - & -\\
+\hline
+conv5(array(1e6)) & 77.94 & 1.26 +- 0.00 & 0.68 +- 0.01 & - & - & -\\
+\hline
+dilate3x3(1000) & - & - & - & 0.17 +- 0.03 & - & -\\
+\hline
+dilate3x3(1000, 1000) & - & - & - & - & 0.09 +- 0.00 & 0.48 +- 0.01\\
+\hline
+dilate3x3(Array2D(1000x1000)) & 137.52 & 4.35 +- 0.01 & 3.91 +- 0.02 & - & - & -\\
+\hline
+sobel(Array2D(1000x1000)) & 104.02 & 0.49 +- 0.00 & 0.21 +- 0.00 & 0.17 +- 0.03 & - & -\\
+\hline
+sobel\_magnitude(1000, 1000) & - & - & - & - & 0.24 +- 0.01 & 0.60 +- 0.01\\
+\hline
+sqrt(Fix16) & 463.46 & 5.12 +- 0.00 & 2.96 +- 0.00 & 1.34 +- 0.03 & 1.14 +- 0.00 & 12.80 +- 0.04\\
+\hline
+sqrt(float) & 14.99 & 1.37 +- 0.00 & 0.89 +- 0.00 & 0.85 +- 0.04 & 0.83 +- 0.01 & 1.06 +- 0.01\\
+\hline
+sqrt(int) & 13.91 & 3.22 +- 0.02 & 2.65 +- 0.00 & 1.25 +- 0.03 & 0.83 +- 0.01 & 1.06 +- 0.00\\
 \hline
 \end{tabular}
 }
@@ -1073,16 +1133,16 @@
 \item {\bf FFT}$\left(n, c\right)$: Fast Fourier Transform of a vector with $n$ elements, represented as an array, repeated $c$ times.
 \end{itemize}
 
-Benchmarks were run on Intel i7 M620 @2.67GHz with 4M cache and 8G of RAM
-using Ubuntu Linux 11.4 in 32bit mode.
+Benchmarks were run on Intel Xeon X5680 @3.33GHz with 12M cache and 16G of RAM
+using Ubuntu Linux 11.4 in 64bit mode.
 The machine was otherwise unoccupied. We use the following software
 for benchmarks:
 
 \begin{itemize}
-\item PyPy 1.5
-\item CPython 2.7.2
-\item Psyco 1.6 with CPython 2.6.6
-\item GCC 4.4.5 shipped with Ubuntu 11.4
+\item PyPy 1.9
+\item CPython 2.7.1
+\item GCC 4.5.2 shipped with Ubuntu 11.4
+\item LuaJIT 2.0 beta, commit ID 0dd175d9e711f039c663d35e96c149b705bcf450
 \end{itemize}
 
 We run GCC with -O3 -march=native, disabling the


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