cern.colt.matrix.doc-files.perfIBM118Linux.txt Maven / Gradle / Ivy
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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 ?
java.vm.version ?
java.vm.name ?
os.name Linux
os.version #1 Mon Sep 27 10:40:35 EDT 1999.2.2.12-20
os.arch i686
java.version 1.1.8
java.vendor IBM Corporation
java.vendor.url http://www.ibm.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 | 202.717 153.534 173.376 184.647
i 33 | 98.813 92.027 94.22 83.302
z 66 | 41.771 41.762 41.837 41.962
e 100 | 42.172 42.22 42.356 41.648
300 | 19.299 19.433 18.965 19.279
1000 | 19.756 19.185 19.013 19
Performance of DoubleMatrix2D assign [Mops/sec]
type=sparse
| density
| 0.0010 0.01 0.1 0.999
---------------------------------------------
s 30 | 90.17 62.385 21.478 3.495
i 33 | 108.349 75.37 27.035 2.289
z 66 | 384.744 169.401 31.19 2.746
e 100 | 726.676 242.37 NaN NaN
300 | 2.219E+003 349.705 NaN NaN
1000 | 2.101E+003 313.301 NaN NaN
Speedup of dense over sparse
| density
| 0.0010 0.01 0.1 0.999
-------------------------------------
s 30 | 2.248 2.461 8.072 52.829
i 33 | 0.912 1.221 3.485 36.386
z 66 | 0.109 0.247 1.341 15.282
e 100 | 0.058 0.174 NaN NaN
300 | 0.009 0.056 NaN NaN
1000 | 0.009 0.061 NaN NaN
Run took a total of Time=456.004 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 | 10.568 10.641 10.593 10.595
i 33 | 10.346 10.328 10.411 10.314
z 66 | 10.353 10.46 10.431 10.441
e 100 | 10.324 10.304 10.336 10.292
300 | 7.264 7.388 7.556 7.488
1000 | 7.469 7.382 7.322 7.357
Performance of DoubleMatrix2D assignGetSetQuick [Mops/sec]
type=sparse
| density
| 0.0010 0.01 0.1 0.999
-------------------------------------
s 30 | 1.553 1.445 1.229 0.67
i 33 | 1.547 1.454 1.263 0.525
z 66 | 1.446 1.453 1.263 0.585
e 100 | 1.489 1.455 NaN NaN
300 | 1.483 1.434 NaN NaN
1000 | 1.472 1.425 NaN NaN
Speedup of dense over sparse
| density
| 0.0010 0.01 0.1 0.999
-------------------------------------
s 30 | 6.804 7.365 8.618 15.817
i 33 | 6.687 7.1 8.242 19.629
z 66 | 7.162 7.199 8.259 17.85
e 100 | 6.931 7.084 NaN NaN
300 | 4.898 5.151 NaN NaN
1000 | 5.072 5.182 NaN NaN
Run took a total of Time=414.626 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 | 6.746 6.64 6.699 6.847
i 33 | 6.531 6.577 6.603 6.585
z 66 | 6.196 6.522 6.531 6.561
e 100 | 6.504 6.507 6.485 5.879
300 | 5.242 5.015 4.998 4.978
1000 | 5.074 4.836 4.821 4.838
Performance of DoubleMatrix2D assignGetSet [Mops/sec]
type=sparse
| density
| 0.0010 0.01 0.1 0.999
-------------------------------------
s 30 | 1.392 1.313 1.126 0.631
i 33 | 1.382 1.305 1.138 0.503
z 66 | 1.323 1.294 1.153 0.554
e 100 | 1.333 1.304 NaN NaN
300 | 1.309 1.295 NaN NaN
1000 | 1.326 1.284 NaN NaN
Speedup of dense over sparse
| density
| 0.0010 0.01 0.1 0.999
-------------------------------------
s 30 | 4.847 5.057 5.951 10.847
i 33 | 4.725 5.041 5.801 13.102
z 66 | 4.683 5.039 5.665 11.846
e 100 | 4.879 4.99 NaN NaN
300 | 4.006 3.871 NaN NaN
1000 | 3.828 3.766 NaN NaN
Run took a total of Time=408.428 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 | 98.881 98.287 98.709 97.516
i 33 | 160.007 115.289 66.786 66.492
z 66 | 354.733 194.525 70.956 70.511
e 100 | 572.834 256.28 80.372 80.499
300 | 1.163E+003 391.62 39.72 40.832
1000 | 2.334E+003 409.794 38.098 38.136
Performance of DoubleMatrix.zMult(B,C) [Mflops/sec]
type=sparse
| density
| 0.0010 0.01 0.1 0.999
----------------------------------------
s 30 | 2.886 2.74 2.664 2.918
i 33 | 26.198 7.754 2.69 2.9
z 66 | 66.685 13.284 2.629 2.989
e 100 | 96.516 21.726 NaN NaN
300 | 254.417 60.629 NaN NaN
1000 | 590.058 110.73 NaN NaN
Speedup of dense over sparse
| density
| 0.0010 0.01 0.1 0.999
--------------------------------------
s 30 | 34.263 35.865 37.059 33.415
i 33 | 6.108 14.869 24.825 22.928
z 66 | 5.319 14.644 26.988 23.587
e 100 | 5.935 11.796 NaN NaN
300 | 4.57 6.459 NaN NaN
1000 | 3.955 3.701 NaN NaN
Run took a total of Time=480.366 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 | 32.872 33.542 30.249 31.479
i 33 | 28.883 28.955 30.614 32.409
z 66 | 33.719 33.596 28.864 28.647
e 100 | 34.309 15.042 31.192 23.819
300 | 11.471 12.285 12.778 12.17
1000 | 11.316 12.548 12.556 12.564
Performance of DoubleMatrix Elementwise mult [Mflops/sec]
type=sparse
| density
| 0.0010 0.01 0.1 0.999
-------------------------------------
s 30 | 0.97 0.969 0.959 0.923
i 33 | 0.97 0.957 0.939 0.94
z 66 | 0.953 0.96 0.93 0.905
e 100 | 0.955 0.954 NaN NaN
300 | 0.963 0.93 NaN NaN
1000 | 0.97 0.934 NaN NaN
Speedup of dense over sparse
| density
| 0.0010 0.01 0.1 0.999
--------------------------------------
s 30 | 33.888 34.607 31.543 34.108
i 33 | 29.784 30.248 32.595 34.486
z 66 | 35.379 34.988 31.027 31.655
e 100 | 35.909 15.763 NaN NaN
300 | 11.915 13.203 NaN NaN
1000 | 11.662 13.434 NaN NaN
Run took a total of Time=435.369 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 | 47.347 44.246 27.743 29.804
i 33 | 52.492 47.662 29.728 32.303
z 66 | 115.045 103.169 46.469 46.186
e 100 | 173.61 148.554 59.58 53.518
300 | 436.16 284.92 79.678 64.8
1000 | 1.088E+003 444.296 49.603 36.64
Performance of LUQuick.decompose [Mflops/sec]
type=sparse
| density
| 0.0010 0.01 0.1 0.999
---------------------------------------
s 30 | 8.192 6.852 2.163 0.631
i 33 | 8.874 7.488 1.964 1.021
z 66 | 18.245 13.991 2.491 0.485
e 100 | 26.055 19.432 NaN NaN
300 | 72.595 40.609 NaN NaN
1000 | 193.489 55.849 NaN NaN
Speedup of dense over sparse
| density
| 0.0010 0.01 0.1 0.999
-------------------------------------
s 30 | 5.78 6.457 12.824 47.266
i 33 | 5.915 6.365 15.134 31.632
z 66 | 6.306 7.374 18.654 95.149
e 100 | 6.663 7.645 NaN NaN
300 | 6.008 7.016 NaN NaN
1000 | 5.625 7.955 NaN NaN
Run took a total of Time=405.341 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 | 163.602 160.545 118.415 60.703
i 33 | 183.644 171.665 133.95 63.351
z 66 | 390.497 385.474 104.919 59.314
e 100 | 602.888 572.391 91.152 58.984
300 | 1.414E+003 1.021E+003 43.214 37.514
1000 | 4.173E+003 95.584 27.1 26.42
Performance of LUQuick.solve [Mflops/sec]
type=sparse
| density
| 0.0010 0.01 0.1 0.999
---------------------------------------
s 30 | 29.442 28.247 6.491 2.454
i 33 | 32.493 31.325 6.419 2.44
z 66 | 65.155 59.621 4.121 2.485
e 100 | 98.301 88.317 NaN NaN
300 | 290.192 56.379 NaN NaN
1000 | 953.788 8.095 NaN NaN
Speedup of dense over sparse
| density
| 0.0010 0.01 0.1 0.999
--------------------------------------
s 30 | 5.557 5.684 18.243 24.731
i 33 | 5.652 5.48 20.868 25.959
z 66 | 5.993 6.465 25.459 23.865
e 100 | 6.133 6.481 NaN NaN
300 | 4.872 18.103 NaN NaN
1000 | 4.375 11.808 NaN NaN
Run took a total of Time=820.9 secs. End of run.
@x....x....x....x....x....x....
@x....x....x....x....x....x....*
Performance of SOR [Mflops/sec]
type=dense
| density
| 0.0010 0.01 0.1 0.999
------------------------------------
s 30 | 48.783 48.821 49.564 50.123
i 33 | 49.667 49.708 47.578 47.156
z 66 | 47.419 47.552 47.489 47.515
e 100 | 46.315 46.509 43.907 46.581
300 | 32.033 31.594 31.748 33.434
1000 | 29.318 29.433 28.839 30.675
Performance of SOR [Mflops/sec]
type=sparse
| density
| 0.0010 0.01 0.1 0.999
-------------------------------------
s 30 | 2.799 2.577 0.392 0.479
i 33 | 3.17 3.169 0.238 -0.404
z 66 | 2.561 2.469 2.504 -0.39
e 100 | 2.965 2.599 NaN NaN
300 | 2.551 1.887 NaN NaN
1000 | 2.34 1.765 NaN NaN
Speedup of dense over sparse
| density
| 0.0010 0.01 0.1 0.999
---------------------------------------
s 30 | 17.428 18.944 126.521 104.558
i 33 | 15.67 15.687 199.875 -116.737
z 66 | 18.518 19.262 18.966 -121.748
e 100 | 15.621 17.893 NaN NaN
300 | 12.559 16.746 NaN NaN
1000 | 12.529 16.672 NaN NaN
Run took a total of Time=526.636 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 | 7.616 5.48 7.146 9.215
i 33 | 5.066 1.638 12.988 12.338
z 66 | 3.169 20.329 19.492 47.602
e 100 | 8.249 16.061 16.662 17.166
300 | 27.918 44.257 44.345 43.717
1000 | 35.083 37.06 34.811 36.058
Performance of Correlation [Mflops/sec]
type=sparse
| density
| 0.0010 0.01 0.1 0.999
-------------------------------------
s 30 | 2.846 2.716 2.202 2.005
i 33 | 1.723 1.869 2.747 2.637
z 66 | 2.721 2.935 2.825 3.032
e 100 | 2.976 2.945 NaN NaN
300 | 3.019 2.905 NaN NaN
1000 | 3.104 2.891 NaN NaN
Speedup of dense over sparse
| density
| 0.0010 0.01 0.1 0.999
--------------------------------------
s 30 | 2.677 2.017 3.245 4.595
i 33 | 2.94 0.877 4.729 4.679
z 66 | 1.165 6.927 6.901 15.698
e 100 | 2.771 5.453 NaN NaN
300 | 9.247 15.233 NaN NaN
1000 | 11.303 12.818 NaN NaN
Run took a total of Time=1153.666 secs. End of run.
Program execution took a total of 85.08745 minutes.
Good bye.
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