25 June 2010 9:47:50.640 AM ZIGGURAT_OPEN_MP: FORTRAN77 version The number of processors = 16 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: 0.638008E-01 0.648320E-01 RATE: 156.738 154.245 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 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: 0.519209E-01 0.462918E-01 RATE: 192.601 216.021 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: 0.839689E-01 0.839500E-01 RATE: 119.092 119.118 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: 0.606489E-01 0.626888E-01 RATE: 164.883 159.518 ZIGGURAT_OPEN_MP: Normal end of execution. 25 June 2010 9:47:51.173 AM 25 June 2010 9:47:51.267 AM ZIGGURAT_OPEN_MP: FORTRAN77 version The number of processors = 16 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: 0.638220E-01 0.268888E-01 RATE: 156.686 371.901 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: 0.463810E-01 0.233309E-01 RATE: 215.606 428.616 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: 0.840349E-01 0.668910E-01 RATE: 118.998 149.497 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: 0.606170E-01 0.375712E-01 RATE: 164.970 266.161 ZIGGURAT_OPEN_MP: Normal end of execution. 25 June 2010 9:47:51.686 AM 25 June 2010 9:47:51.886 AM ZIGGURAT_OPEN_MP: FORTRAN77 version The number of processors = 16 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: 0.504098E-01 0.162518E-01 RATE: 198.374 615.316 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: 0.463870E-01 0.155680E-01 RATE: 215.578 642.343 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: 0.842519E-01 0.523651E-01 RATE: 118.692 190.967 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: 0.606899E-01 0.293770E-01 RATE: 164.772 340.403 ZIGGURAT_OPEN_MP: Normal end of execution. 25 June 2010 9:47:52.249 AM