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Parallel Colt is a multithreaded version of Colt - a library for high performance scientific computing in Java. It contains efficient algorithms for data analysis, linear algebra, multi-dimensional arrays, Fourier transforms, statistics and histogramming.
The newest version!
Colt Matrix benchmark running on
java.vm.vendor Sun Microsystems Inc.
java.vm.version 1.2.2
java.vm.name Classic VM
os.name Linux
os.version 2.2.12-20
os.arch i386
java.version 1.2.2
java.vendor Sun Microsystems Inc.
java.vendor.url http://java.sun.com/
@x....x....x....x....x....x....
@x....x....x....x....x....x....*
Performance of DoubleMatrix2D assign [Mops/sec]
type=dense
| density
| 0.0010 0.01 0.1 0.999
------------------------------------
s 30 | 72.148 72.856 77.553 65.259
i 33 | 55.993 60.265 66.304 47.264
z 66 | 41.874 41.737 41.502 41.344
e 100 | 40.807 41.364 42.104 41.375
300 | 20.258 20.157 20.429 20.357
1000 | 19.399 19.324 19.342 19.342
Performance of DoubleMatrix2D assign [Mops/sec]
type=sparse
| density
| 0.0010 0.01 0.1 0.999
---------------------------------------------
s 30 | 62.035 28.36 13.683 2.644
i 33 | 95.487 51.332 17.624 1.807
z 66 | 297.188 111.492 21.432 2.31
e 100 | 377.066 150.811 NaN NaN
300 | 1.323E+003 264.146 NaN NaN
1000 | 1.628E+003 275.615 NaN NaN
Speedup of dense over sparse
| density
| 0.0010 0.01 0.1 0.999
-------------------------------------
s 30 | 1.163 2.569 5.668 24.683
i 33 | 0.586 1.174 3.762 26.15
z 66 | 0.141 0.374 1.936 17.898
e 100 | 0.108 0.274 NaN NaN
300 | 0.015 0.076 NaN NaN
1000 | 0.012 0.07 NaN NaN
Run took a total of Time=190.751 secs. End of run.
@x....x....x....x....x....x....
@x....x....x....x....x....x....*
Performance of DoubleMatrix2D assignGetSetQuick [Mops/sec]
type=dense
| density
| 0.0010 0.01 0.1 0.999
---------------------------------
s 30 | 4.927 4.744 4.931 4.958
i 33 | 4.517 4.857 4.868 4.823
z 66 | 5.016 4.938 4.918 4.891
e 100 | 4.912 4.938 4.932 4.926
300 | 4.18 4.176 4.107 4.188
1000 | 4.037 4.039 4.042 4.037
Performance of DoubleMatrix2D assignGetSetQuick [Mops/sec]
type=sparse
| density
| 0.0010 0.01 0.1 0.999
-------------------------------------
s 30 | 1 0.932 0.812 0.445
i 33 | 1.002 0.932 0.764 0.349
z 66 | 0.957 0.938 0.802 0.389
e 100 | 0.964 0.941 NaN NaN
300 | 0.959 0.93 NaN NaN
1000 | 0.954 0.933 NaN NaN
Speedup of dense over sparse
| density
| 0.0010 0.01 0.1 0.999
-------------------------------------
s 30 | 4.927 5.092 6.071 11.138
i 33 | 4.508 5.209 6.369 13.816
z 66 | 5.241 5.266 6.134 12.561
e 100 | 5.098 5.248 NaN NaN
300 | 4.359 4.49 NaN NaN
1000 | 4.231 4.328 NaN NaN
Run took a total of Time=168.947 secs. End of run.
@x....x....x....x....x....x....
@x....x....x....x....x....x....*
Performance of DoubleMatrix2D assignGetSet [Mops/sec]
type=dense
| density
| 0.0010 0.01 0.1 0.999
---------------------------------
s 30 | 2.793 2.767 2.82 2.77
i 33 | 2.812 2.802 2.773 2.805
z 66 | 2.824 2.821 2.825 2.858
e 100 | 2.823 2.78 2.851 2.811
300 | 2.562 2.516 2.512 2.526
1000 | 2.493 2.444 2.441 2.463
Performance of DoubleMatrix2D assignGetSet [Mops/sec]
type=sparse
| density
| 0.0010 0.01 0.1 0.999
-------------------------------------
s 30 | 0.861 0.811 0.716 0.395
i 33 | 0.858 0.81 0.728 0.326
z 66 | 0.829 0.815 0.7 0.362
e 100 | 0.833 0.816 NaN NaN
300 | 0.83 0.81 NaN NaN
1000 | 0.828 0.812 NaN NaN
Speedup of dense over sparse
| density
| 0.0010 0.01 0.1 0.999
-------------------------------------
s 30 | 3.246 3.411 3.941 7.015
i 33 | 3.277 3.46 3.811 8.594
z 66 | 3.407 3.459 4.033 7.883
e 100 | 3.391 3.406 NaN NaN
300 | 3.086 3.105 NaN NaN
1000 | 3.011 3.011 NaN NaN
Run took a total of Time=164.045 secs. End of run.
@x....x....x....x....x....x....
@x....x....x....x....x....x....*
Performance of DoubleMatrix.zMult(B,C) [Mflops/sec]
type=dense
| density
| 0.0010 0.01 0.1 0.999
-------------------------------------------
s 30 | 18.498 18.497 16.814 18.434
i 33 | 75.999 44.205 16.987 19.993
z 66 | 180.208 77.364 24.675 24.234
e 100 | 269.628 107.28 26.316 26.163
300 | 634.321 175.732 20.052 22.059
1000 | 1.238E+003 201.066 18.932 18.935
Performance of DoubleMatrix.zMult(B,C) [Mflops/sec]
type=sparse
| density
| 0.0010 0.01 0.1 0.999
---------------------------------------
s 30 | 1.344 1.306 1.274 1.345
i 33 | 13.965 3.411 1.094 1.101
z 66 | 43.325 5.637 1.057 1.123
e 100 | 62.718 9.634 NaN NaN
300 | 167.183 32.423 NaN NaN
1000 | 392.696 75.25 NaN NaN
Speedup of dense over sparse
| density
| 0.0010 0.01 0.1 0.999
--------------------------------------
s 30 | 13.762 14.163 13.201 13.709
i 33 | 5.442 12.961 15.53 18.162
z 66 | 4.159 13.724 23.345 21.58
e 100 | 4.299 11.136 NaN NaN
300 | 3.794 5.42 NaN NaN
1000 | 3.153 2.672 NaN NaN
Run took a total of Time=391.957 secs. End of run.
@x....x....x....x....x....x....
@x....x....x....x....x....x....*
Performance of DoubleMatrix Elementwise mult [Mflops/sec]
type=dense
| density
| 0.0010 0.01 0.1 0.999
------------------------------------
s 30 | 11.469 11.025 10.981 11.229
i 33 | 11 11.015 11.256 11.643
z 66 | 11.947 11.82 11.874 11.874
e 100 | 12.112 11.981 11.828 11.952
300 | 7.753 6.403 6.547 6.471
1000 | 7.874 6.605 6.605 6.609
Performance of DoubleMatrix Elementwise mult [Mflops/sec]
type=sparse
| density
| 0.0010 0.01 0.1 0.999
-------------------------------------
s 30 | 0.609 0.608 0.6 0.618
i 33 | 0.607 0.601 0.565 0.57
z 66 | 0.603 0.604 0.589 0.565
e 100 | 0.606 0.605 NaN NaN
300 | 0.606 0.591 NaN NaN
1000 | 0.611 0.577 NaN NaN
Speedup of dense over sparse
| density
| 0.0010 0.01 0.1 0.999
--------------------------------------
s 30 | 18.844 18.127 18.317 18.183
i 33 | 18.107 18.319 19.908 20.417
z 66 | 19.815 19.573 20.161 21.021
e 100 | 19.985 19.793 NaN NaN
300 | 12.787 10.84 NaN NaN
1000 | 12.89 11.44 NaN NaN
Run took a total of Time=171.221 secs. End of run.
@x....x....x....x....x....x....
@x....x....x....x....x....x....*
Performance of LUQuick.decompose [Mflops/sec]
type=dense
| density
| 0.0010 0.01 0.1 0.999
--------------------------------------
s 30 | 18.982 17.223 8.871 10.844
i 33 | 21.144 19.34 11.536 11.954
z 66 | 46.86 41.798 20.639 20.001
e 100 | 72.479 62.436 29.51 25.456
300 | 200.101 148.991 43.647 34.466
1000 | 559.754 279.877 32.319 29.631
Performance of LUQuick.decompose [Mflops/sec]
type=sparse
| density
| 0.0010 0.01 0.1 0.999
---------------------------------------
s 30 | 5.005 4.139 1.356 0.4
i 33 | 5.339 4.535 1.282 0.659
z 66 | 11.359 8.552 1.556 0.322
e 100 | 16.029 12.015 NaN NaN
300 | 45.169 25.912 NaN NaN
1000 | 122.752 37.729 NaN NaN
Speedup of dense over sparse
| density
| 0.0010 0.01 0.1 0.999
-------------------------------------
s 30 | 3.792 4.162 6.544 27.083
i 33 | 3.96 4.265 9 18.148
z 66 | 4.126 4.887 13.264 62.116
e 100 | 4.522 5.197 NaN NaN
300 | 4.43 5.75 NaN NaN
1000 | 4.56 7.418 NaN NaN
Run took a total of Time=208.389 secs. End of run.
@x....x....x....x....x....x....
@x....x....x....x....x....x....*
Performance of LUQuick.solve [Mflops/sec]
type=dense
| density
| 0.0010 0.01 0.1 0.999
-------------------------------------------
s 30 | 77.259 75.015 36.129 13.482
i 33 | 88.404 85.518 38.265 13.852
z 66 | 194.44 189.424 27.088 15.565
e 100 | 297.059 288.72 25.301 16.252
300 | 830.455 462.612 17.97 15.271
1000 | 2.592E+003 51.529 14.909 14.416
Performance of LUQuick.solve [Mflops/sec]
type=sparse
| density
| 0.0010 0.01 0.1 0.999
---------------------------------------
s 30 | 17.994 17.379 3.66 1.446
i 33 | 19.73 19.331 3.703 1.463
z 66 | 40.044 36.5 2.477 1.474
e 100 | 60.849 54.269 NaN NaN
300 | 179.829 34.356 NaN NaN
1000 | 596.899 4.884 NaN NaN
Speedup of dense over sparse
| density
| 0.0010 0.01 0.1 0.999
--------------------------------------
s 30 | 4.294 4.316 9.871 9.325
i 33 | 4.481 4.424 10.335 9.465
z 66 | 4.856 5.19 10.937 10.56
e 100 | 4.882 5.32 NaN NaN
300 | 4.618 13.465 NaN NaN
1000 | 4.343 10.55 NaN NaN
Run took a total of Time=955.159 secs. End of run.
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@x....x....x....x....x....x....*
Performance of SOR [Mflops/sec]
type=dense
| density
| 0.0010 0.01 0.1 0.999
------------------------------------
s 30 | 13.27 13.236 13.301 13.264
i 33 | 13.301 13.226 13.112 13.099
z 66 | 12.518 12.526 12.526 12.477
e 100 | 12.208 12.22 12.208 12.227
300 | 10.9 10.942 10.954 10.942
1000 | 10.676 10.7 10.7 10.71
Performance of SOR [Mflops/sec]
type=sparse
| density
| 0.0010 0.01 0.1 0.999
-------------------------------------
s 30 | 2.055 1.972 1.881 2.186
i 33 | 2.042 2.021 1.854 2.066
z 66 | 1.924 1.911 1.657 1.979
e 100 | 1.895 1.807 NaN NaN
300 | 1.848 1.769 NaN NaN
1000 | 1.843 1.752 NaN NaN
Speedup of dense over sparse
| density
| 0.0010 0.01 0.1 0.999
-------------------------------------
s 30 | 6.458 6.712 7.071 6.069
i 33 | 6.512 6.543 7.073 6.34
z 66 | 6.505 6.553 7.557 6.304
e 100 | 6.441 6.764 NaN NaN
300 | 5.9 6.186 NaN NaN
1000 | 5.792 6.108 NaN NaN
Run took a total of Time=165.514 secs. End of run.
@x....x....x....x....x....x....
@x....x....x....x....x....x....*
Performance of Correlation [Mflops/sec]
type=dense
| density
| 0.0010 0.01 0.1 0.999
------------------------------------
s 30 | 11.324 9.106 5.681 10.675
i 33 | 12.262 9.522 6.291 11.842
z 66 | 18.938 13.537 10.745 18.629
e 100 | 23.126 16.525 14.326 22.83
300 | 25.533 21.681 20.007 27.345
1000 | 21.805 24.525 24.658 25.25
Performance of Correlation [Mflops/sec]
type=sparse
| density
| 0.0010 0.01 0.1 0.999
-------------------------------------
s 30 | 0.998 0.975 0.91 1.007
i 33 | 1.008 0.975 0.917 1.011
z 66 | 1.036 1.013 0.976 1.047
e 100 | 1.046 1.023 NaN NaN
300 | 1.063 1.033 NaN NaN
1000 | 1.078 1.052 NaN NaN
Speedup of dense over sparse
| density
| 0.0010 0.01 0.1 0.999
--------------------------------------
s 30 | 11.347 9.344 6.241 10.599
i 33 | 12.163 9.768 6.857 11.717
z 66 | 18.282 13.365 11.013 17.785
e 100 | 22.103 16.154 NaN NaN
300 | 24.029 20.986 NaN NaN
1000 | 20.235 23.322 NaN NaN
Run took a total of Time=2228.253 secs. End of run.
Program execution took a total of 77.4098 minutes.
Good bye.
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