Re: [general][evaluation] I did a performance evaluation using Scimark2

[Aleksey Shipilev]

Wow, Simon :)

Can you align this data? It's completely unreadable - I haven't clue
how Harmony performs looking to these numbers. I'm very interested in
this measurements.

Thanks,
Aleksey.

On Fri, Mar 7, 2008 at 3:39 PM, Simon Chow <[EMAIL PROTECTED]> wrote:
> I use a scientific computing benchmark Scimark2, which has 2 running modes:
>  default and -large.
>  I would like to share it with you. :=)
>
>
>  Platform:
>  Intel(R) Xeon(TM) CPU 2.80GHz*4.
>  arch: x86
>  os: Linux 2.6.18-8.el5xen;
>  Mem:4GB
>
>  Harmony
>
>  -Xms1500m -Xmx1500m -Xem:server jnt.scimark2.commandline
>
>  Composite Score
>
>  FFT
>
>  (1024)
>
>  SOR
>
>  (100*100)
>
>  Monte Carlo
>
>  Sparse matmult
>
>  (N=1000,nz=5000)
>
>  LU
>
>  (100*100)
>
>  193.99
>
>  223.91
>
>  366.62
>
>  28.42
>
>  184.19
>
>  166.83
>
>  194.05
>
>  222.20
>
>  370.43
>
>  28.04
>
>  183.16
>
>  166.42
>
>  193.67
>
>  223.05
>
>  369.72
>
>  28.61
>
>  181.29
>
>  165.70
>
>  193.41
>
>  221.29
>
>  371.28
>
>  27.69
>
>  182.04
>
>  164.74
>
>  194.34
>
>  222.48
>
>  371.00
>
>  28.17
>
>  183.32
>
>  166.75
>
>  -Xms1500m -Xmx1500m -Xem:server jnt.scimark2.commandline -large
>
>  Composite Score
>
>  FFT
>
>  (1048576)
>
>  SOR
>
>  (1000*1000)
>
>  Monte Carlo
>
>  Sparse matmult
>
>  (N=100000,
>
>  nz=1000000)
>
>  LU
>
>  (1000*1000)
>
>  179.31
>
>  37.93
>
>  359.34
>
>  27.18
>
>  289.51
>
>  182.60
>
>  178.31
>
>  35.84
>
>  359.34
>
>  28.08
>
>  288.78
>
>  179.50
>
>  179.35
>
>  37.19
>
>  258.66
>
>  28.08
>
>  289.43
>
>  183.40
>
>  179.02
>
>  35.63
>
>  360.01
>
>  27.14
>
>  289.92
>
>  182.40
>
>  179.80
>
>  37.44
>
>  360.01
>
>  27.25
>
>  290.08
>
>  184.21
>
>
>  Sun sdk1.5
>
>  -Xms1500m -Xmx1500m -server jnt.scimark2.commandline
>
>  Composite Score
>
>  FFT
>
>  (1024)
>
>  SOR
>
>  (100*100)
>
>  Monte Carlo
>
>  Sparse matmult
>
>  (N=1000,nz=5000)
>
>  LU
>
>  (100*100)
>
>  427.30
>
>  252.57
>
>  593.82
>
>  22.51
>
>  321.41
>
>  946.18
>
>  431.48
>
>  272.11
>
>  596.21
>
>  22.16
>
>  322.68
>
>  944.21
>
>  432.80
>
>  273.99
>
>  596.77
>
>  22.54
>
>  322.20
>
>  948.48
>
>  428.75
>
>  256.96
>
>  596.03
>
>  22.58
>
>  323.63
>
>  944.54
>
>  432.90
>
>  276.25
>
>  597.32
>
>  22.59
>
>  323.16
>
>  945.19
>
>
>  -Xms1500m -Xmx1500m –server jnt.scimark2.commandline -large
>
>  Composite Score
>
>  FFT
>
>  (1048576)
>
>  SOR
>
>  (1000*1000)
>
>  Monte Carlo
>
>  Sparse matmult
>
>  (N=100000,
>
>  nz=1000000)
>
>  LU
>
>  (1000*1000)
>
>  243.25
>
>  36.42
>
>  553.20
>
>  34.72
>
>  381.71
>
>  265.18
>
>  278.28
>
>  37.74
>
>  576.72
>
>  39.89
>
>  369.94
>
>  367.11
>
>  266.89
>
>  37.42
>
>  575.21
>
>  41.22
>
>  368.48
>
>  312.11
>
>  271.74
>
>  37.63
>
>  577.16
>
>  39.48
>
>  371.28
>
>  333.17
>
>  269.53
>
>  37.49
>
>  574.99
>
>  41.12
>
>  368.88
>
>  325.20
>
>
>  gcj-4.0.2 –O3
>
>  Composite Score
>
>  FFT
>
>  (1024)
>
>  SOR
>
>  (100*100)
>
>  Monte Carlo
>
>  Sparse matmult
>
>  (N=1000,
>
>  nz=5000)
>
>  LU
>
>  (100*100)
>
>  214.69
>
>  228.30
>
>  360.18
>
>  11.19
>
>  151.84
>
>  321.94
>
>  220.42
>
>  195.46
>
>  338.18
>
>  7.96
>
>  276.17
>
>  284.33
>
>  254.33
>
>  214.59
>
>  360.18
>
>  11.58
>
>  277.23
>
>  408.05
>
>  179.55
>
>  184.54
>
>  355.71
>
>  6.71
>
>  143.22
>
>  227.56
>
>  233.90
>
>  215.02
>
>  360.58
>
>  11.57
>
>  276.41
>
>  305.92
>
>  -large
>
>  Composite Score
>
>  FFT
>
>  (1048576)
>
>  SOR
>
>  (1000*1000)
>
>  Monte Carlo
>
>  Sparse matmult
>
>  (N=100000,
>
>  nz=1000000)
>
>  LU
>
>  (1000*1000)
>
>  192.24
>
>  29.62
>
>  348.23
>
>  11.55
>
>  222.95
>
>  348.86
>
>  177.07
>
>  35.24
>
>  322.72
>
>  8.16
>
>  232.94
>
>  286.25
>
>  174.29
>
>  35.02
>
>  331.95
>
>  9.75
>
>  249.63
>
>  245.09
>
>  196.79
>
>  27.28
>
>  347.29
>
>  11.50
>
>  255.12
>
>  342.76
>
>  179.69
>
>  37.69
>
>  349.346
>
>  10.69
>
>  176.19
>
>  324.57
>
>
>
>  --
>  From : [EMAIL PROTECTED] School of Fudan University
>