25 June 2010 9:51:56.581 AM ZIGGURAT_OPEN_MP: FORTRAN77 version The number of processors = 8 The number of threads = 1 TEST01 SHR3 computes random integers. Since the output is completely determined by the input value of SEED, we can run in parallel as long as we make an array of seeds. The number of threads is 1 Correctness check: Computing values sequentially should reach the same result as doing it in parallel: THREAD Sequential Parallel Difference 0 -1863796367 -1863796367 0 Efficiency check: Computing values in parallel should be faster. Sequential Parallel TIME: 0.639031E-01 0.496941E-01 RATE: 156.487 201.231 TEST02 R4_UNI computes uniformly random single precision real values. Since the output is completely determined by the input value of SEED, we can run in parallel as long as we make an array of seeds. The number of threads is 1 Correctness check: Computing values sequentially should reach the same result as doing it in parallel: THREAD Sequential Parallel Difference 0 0.660512E-01 0.660512E-01 0.00000 Efficiency check: Computing values in parallel should be faster. Sequential Parallel TIME: 0.464201E-01 0.463130E-01 RATE: 215.424 215.922 TEST03 R4_NOR computes normal random single precision real values. Since the output is completely determined by the input value of SEED and the tables, we can run in parallel as long as we make an array of seeds and share the tables. The number of threads is 1 Correctness check: Computing values sequentially should reach the same result as doing it in parallel: THREAD Sequential Parallel Difference 0 -0.326194 -0.326194 0.00000 Efficiency check: Computing values in parallel should be faster. Sequential Parallel TIME: 0.840828E-01 0.840631E-01 RATE: 118.930 118.958 TEST04 R4_EXP computes exponential random single precision real values. Since the output is completely determined by the input value of SEED and the tables, we can run in parallel as long as we make an array of seeds and share the tables. The number of threads is 1 Correctness check: Computing values sequentially should reach the same result as doing it in parallel: THREAD Sequential Parallel Difference 0 0.351739 0.351739 0.00000 Efficiency check: Computing values in parallel should be faster. Sequential Parallel TIME: 0.606821E-01 0.627470E-01 RATE: 164.793 159.370 ZIGGURAT_OPEN_MP: Normal end of execution. 25 June 2010 9:51:57.105 AM 25 June 2010 9:51:57.216 AM ZIGGURAT_OPEN_MP: FORTRAN77 version The number of processors = 8 The number of threads = 2 TEST01 SHR3 computes random integers. Since the output is completely determined by the input value of SEED, we can run in parallel as long as we make an array of seeds. The number of threads is 2 Correctness check: Computing values sequentially should reach the same result as doing it in parallel: THREAD Sequential Parallel Difference 0 1249912034 1249912034 0 1 503020437 503020437 0 Efficiency check: Computing values in parallel should be faster. Sequential Parallel TIME: 0.638258E-01 0.323522E-01 RATE: 156.676 309.098 TEST02 R4_UNI computes uniformly random single precision real values. Since the output is completely determined by the input value of SEED, we can run in parallel as long as we make an array of seeds. The number of threads is 2 Correctness check: Computing values sequentially should reach the same result as doing it in parallel: THREAD Sequential Parallel Difference 0 0.791018 0.791018 0.00000 1 0.617119 0.617119 0.00000 Efficiency check: Computing values in parallel should be faster. Sequential Parallel TIME: 0.508659E-01 0.231681E-01 RATE: 196.595 431.628 TEST03 R4_NOR computes normal random single precision real values. Since the output is completely determined by the input value of SEED and the tables, we can run in parallel as long as we make an array of seeds and share the tables. The number of threads is 2 Correctness check: Computing values sequentially should reach the same result as doing it in parallel: THREAD Sequential Parallel Difference 0 0.977730 0.977730 0.00000 1 -1.07051 -1.07051 0.00000 Efficiency check: Computing values in parallel should be faster. Sequential Parallel TIME: 0.840871E-01 0.430529E-01 RATE: 118.924 232.272 TEST04 R4_EXP computes exponential random single precision real values. Since the output is completely determined by the input value of SEED and the tables, we can run in parallel as long as we make an array of seeds and share the tables. The number of threads is 2 Correctness check: Computing values sequentially should reach the same result as doing it in parallel: THREAD Sequential Parallel Difference 0 1.73583 1.73583 0.00000 1 0.502068 0.502068 0.00000 Efficiency check: Computing values in parallel should be faster. Sequential Parallel TIME: 0.643721E-01 0.314019E-01 RATE: 155.347 318.452 ZIGGURAT_OPEN_MP: Normal end of execution. 25 June 2010 9:51:57.621 AM 25 June 2010 9:51:57.640 AM ZIGGURAT_OPEN_MP: FORTRAN77 version The number of processors = 8 The number of threads = 4 TEST01 SHR3 computes random integers. Since the output is completely determined by the input value of SEED, we can run in parallel as long as we make an array of seeds. The number of threads is 4 Correctness check: Computing values sequentially should reach the same result as doing it in parallel: THREAD Sequential Parallel Difference 0 -1669655539 -1669655539 0 1 108105747 108105747 0 2 -1587791136 -1587791136 0 3 1909075432 1909075432 0 Efficiency check: Computing values in parallel should be faster. Sequential Parallel TIME: 0.404952E-01 0.104940E-01 RATE: 246.943 952.926 TEST02 R4_UNI computes uniformly random single precision real values. Since the output is completely determined by the input value of SEED, we can run in parallel as long as we make an array of seeds. The number of threads is 4 Correctness check: Computing values sequentially should reach the same result as doing it in parallel: THREAD Sequential Parallel Difference 0 0.111253 0.111253 0.00000 1 0.525170 0.525170 0.00000 2 0.130314 0.130314 0.00000 3 0.944491 0.944491 0.00000 Efficiency check: Computing values in parallel should be faster. Sequential Parallel TIME: 0.466080E-01 0.119281E-01 RATE: 214.556 838.358 TEST03 R4_NOR computes normal random single precision real values. Since the output is completely determined by the input value of SEED and the tables, we can run in parallel as long as we make an array of seeds and share the tables. The number of threads is 4 Correctness check: Computing values sequentially should reach the same result as doing it in parallel: THREAD Sequential Parallel Difference 0 -0.828252 -0.828252 0.00000 1 0.314686 0.314686 0.00000 2 -0.989801 -0.989801 0.00000 3 -1.48772 -1.48772 0.00000 Efficiency check: Computing values in parallel should be faster. Sequential Parallel TIME: 0.844212E-01 0.768089E-01 RATE: 118.454 130.193 TEST04 R4_EXP computes exponential random single precision real values. Since the output is completely determined by the input value of SEED and the tables, we can run in parallel as long as we make an array of seeds and share the tables. The number of threads is 4 Correctness check: Computing values sequentially should reach the same result as doing it in parallel: THREAD Sequential Parallel Difference 0 0.129717 0.129717 0.00000 1 0.439901 0.439901 0.00000 2 0.834098 0.834098 0.00000 3 0.973891 0.973891 0.00000 Efficiency check: Computing values in parallel should be faster. Sequential Parallel TIME: 0.609131E-01 0.301111E-01 RATE: 164.168 332.104 ZIGGURAT_OPEN_MP: Normal end of execution. 25 June 2010 9:51:58.013 AM 25 June 2010 9:51:58.069 AM ZIGGURAT_OPEN_MP: FORTRAN77 version The number of processors = 8 The number of threads = 8 TEST01 SHR3 computes random integers. Since the output is completely determined by the input value of SEED, we can run in parallel as long as we make an array of seeds. The number of threads is 8 Correctness check: Computing values sequentially should reach the same result as doing it in parallel: THREAD Sequential Parallel Difference 0 2066176573 2066176573 0 1 -1303848666 -1303848666 0 2 167050157 167050157 0 3 412856606 412856606 0 4 -541773661 -541773661 0 5 -189888513 -189888513 0 6 -435391081 -435391081 0 7 1328385438 1328385438 0 Efficiency check: Computing values in parallel should be faster. Sequential Parallel TIME: 0.425410E-01 0.541115E-02 RATE: 235.067 1848.04 TEST02 R4_UNI computes uniformly random single precision real values. Since the output is completely determined by the input value of SEED, we can run in parallel as long as we make an array of seeds. The number of threads is 8 Correctness check: Computing values sequentially should reach the same result as doing it in parallel: THREAD Sequential Parallel Difference 0 0.981069 0.981069 0.00000 1 0.196424 0.196424 0.00000 2 0.538894 0.538894 0.00000 3 0.596126 0.596126 0.00000 4 0.373859 0.373859 0.00000 5 0.455788 0.455788 0.00000 6 0.398628 0.398628 0.00000 7 0.809289 0.809289 0.00000 Efficiency check: Computing values in parallel should be faster. Sequential Parallel TIME: 0.490301E-01 0.611210E-02 RATE: 203.956 1636.10 TEST03 R4_NOR computes normal random single precision real values. Since the output is completely determined by the input value of SEED and the tables, we can run in parallel as long as we make an array of seeds and share the tables. The number of threads is 8 Correctness check: Computing values sequentially should reach the same result as doing it in parallel: THREAD Sequential Parallel Difference 0 -1.33701 -1.33701 0.00000 1 1.76707 1.76707 0.00000 2 0.673030 0.673030 0.00000 3 -0.489069E-01 -0.489069E-01 0.00000 4 -0.393083 -0.393083 0.00000 5 -0.447175 -0.447175 0.00000 6 -0.819305E-01 -0.819305E-01 0.00000 7 -0.861219 -0.861219 0.00000 Efficiency check: Computing values in parallel should be faster. Sequential Parallel TIME: 0.861020E-01 0.671561E-01 RATE: 116.141 148.907 TEST04 R4_EXP computes exponential random single precision real values. Since the output is completely determined by the input value of SEED and the tables, we can run in parallel as long as we make an array of seeds and share the tables. The number of threads is 8 Correctness check: Computing values sequentially should reach the same result as doing it in parallel: THREAD Sequential Parallel Difference 0 0.445202 0.445202 0.00000 1 0.451912 0.451912 0.00000 2 0.355638 0.355638 0.00000 3 0.743365 0.743365 0.00000 4 1.85271 1.85271 0.00000 5 0.674086 0.674086 0.00000 6 0.810988 0.810988 0.00000 7 0.686205 0.686205 0.00000 Efficiency check: Computing values in parallel should be faster. Sequential Parallel TIME: 0.642180E-01 0.303359E-01 RATE: 155.719 329.642 ZIGGURAT_OPEN_MP: Normal end of execution. 25 June 2010 9:51:58.490 AM