04 August 2020 02:19:25 PM ZIGGURAT_OPENMP: C++ version Number of processors = 8 Number of threads = 1 TEST01 SHR3_SEEDED 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: 0.0752051 0.0696993 RATE: 132.97 143.473 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 0.0660511 0.0660511 0 Efficiency check: Computing values in parallel should be faster:' Sequential Parallel TIME: 0.321393 0.317587 RATE: 31.1146 31.4875 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 Efficiency check: Computing values in parallel should be faster: Sequential Parallel TIME: 0.183488 0.194632 RATE: 54.4995 51.379 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 0.113969 0.113969 0 Efficiency check: Computing values in parallel should be faster: Sequential Parallel TIME: 0.844057 0.849704 RATE: 11.8475 11.7688 ZIGGURAT_OPENMP: Normal end of execution. 04 August 2020 02:19:28 PM 04 August 2020 02:19:28 PM ZIGGURAT_OPENMP: C++ version Number of processors = 8 Number of threads = 2 TEST01 SHR3_SEEDED 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: 0.075685 0.0406594 RATE: 132.127 245.945 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 1 0.617119 0.617119 0 Efficiency check: Computing values in parallel should be faster:' Sequential Parallel TIME: 0.346219 0.169137 RATE: 28.8834 59.1238 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 0.97773 0.97773 0 1 -1.07051 -1.07051 0 Efficiency check: Computing values in parallel should be faster: Sequential Parallel TIME: 0.190641 0.10783 RATE: 52.4546 92.7389 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 0.332266 0.332266 0 1 0.605476 0.605476 0 Efficiency check: Computing values in parallel should be faster: Sequential Parallel TIME: 0.836007 0.429099 RATE: 11.9616 23.3047 ZIGGURAT_OPENMP: Normal end of execution. 04 August 2020 02:19:30 PM 04 August 2020 02:19:30 PM ZIGGURAT_OPENMP: C++ version Number of processors = 8 Number of threads = 4 TEST01 SHR3_SEEDED 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: 0.0716377 0.0195979 RATE: 139.591 510.259 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 1 0.52517 0.52517 0 2 0.130314 0.130314 0 3 0.944491 0.944491 0 Efficiency check: Computing values in parallel should be faster:' Sequential Parallel TIME: 0.324737 0.0885026 RATE: 30.7942 112.991 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 1 0.314686 0.314686 0 2 -0.989801 -0.989801 0 3 -1.48772 -1.48772 0 Efficiency check: Computing values in parallel should be faster: Sequential Parallel TIME: 0.177302 0.0514274 RATE: 56.4009 194.449 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 0.427391 0.427391 0 1 0.162032 0.162032 0 2 0.125027 0.125027 0 3 0.264089 0.264089 0 Efficiency check: Computing values in parallel should be faster: Sequential Parallel TIME: 0.819097 0.225701 RATE: 12.2086 44.3065 ZIGGURAT_OPENMP: Normal end of execution. 04 August 2020 02:19:32 PM 04 August 2020 02:19:32 PM ZIGGURAT_OPENMP: C++ version Number of processors = 8 Number of threads = 8 TEST01 SHR3_SEEDED 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: 0.0766704 0.0194639 RATE: 130.428 513.773 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 1 0.196424 0.196424 0 2 0.538894 0.538894 0 3 0.596126 0.596126 0 4 0.373859 0.373859 0 5 0.455788 0.455788 0 6 0.398628 0.398628 0 7 0.809289 0.809289 0 Efficiency check: Computing values in parallel should be faster:' Sequential Parallel TIME: 0.330928 0.0553384 RATE: 30.2181 180.706 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 1 1.76707 1.76707 0 2 0.67303 0.67303 0 3 -0.0489069 -0.0489069 0 4 -0.393083 -0.393083 0 5 -0.447175 -0.447175 0 6 -0.0819305 -0.0819305 0 7 -0.861219 -0.861219 0 Efficiency check: Computing values in parallel should be faster: Sequential Parallel TIME: 0.182593 0.0421319 RATE: 54.7667 237.35 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 1.33056 1.33056 0 1 0.276245 0.276245 0 2 0.123901 0.123901 0 3 0.34829 0.34829 0 4 0.348777 0.348777 0 5 0.145308 0.145308 0 6 0.669387 0.669387 0 7 0.877301 0.877301 0 Efficiency check: Computing values in parallel should be faster: Sequential Parallel TIME: 0.836544 0.155821 RATE: 11.9539 64.1763 ZIGGURAT_OPENMP: Normal end of execution. 04 August 2020 02:19:34 PM