14 October 2011 9:55:55.647 AM ZIGGURAT_OPENMP: 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: 0.990050E-01 0.997112E-01 RATE: 101.005 100.290 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: 0.121570 0.119837 RATE: 82.2571 83.4466 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: 0.260356 0.260443 RATE: 38.4089 38.3961 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: 0.298151 0.268195 RATE: 33.5401 37.2863 ZIGGURAT_OPENMP: Normal end of execution. 14 October 2011 9:55:57.182 AM 14 October 2011 9:55:57.185 AM ZIGGURAT_OPENMP: 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: 0.999742E-01 0.522890E-01 RATE: 100.026 191.245 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: 0.121623 0.650671E-01 RATE: 82.2213 153.688 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: 0.260644 0.135814 RATE: 38.3665 73.6301 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: 0.299676 0.139120 RATE: 33.3694 71.8803 ZIGGURAT_OPENMP: Normal end of execution. 14 October 2011 9:55:58.360 AM 14 October 2011 9:55:58.362 AM ZIGGURAT_OPENMP: 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: 0.992401E-01 0.313089E-01 RATE: 100.766 319.398 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: 0.121259 0.373921E-01 RATE: 82.4681 267.436 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: 0.260343 0.854361E-01 RATE: 38.4109 117.047 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: 0.296940 0.934069E-01 RATE: 33.6768 107.058 ZIGGURAT_OPENMP: Normal end of execution. 14 October 2011 9:55:59.390 AM