11 May 2025 08:31:31 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: 0.0689566 0.0626938 RATE: 145.019 159.505 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: 0.292775 0.295753 RATE: 34.156 33.812 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: 0.149367 0.146525 RATE: 66.9492 68.2476 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: 0.744175 0.74813 RATE: 13.4377 13.3667 ZIGGURAT_OPENMP: Normal end of execution. 11 May 2025 08:31:34 PM 11 May 2025 08:31:34 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: 0.0634091 0.0320242 RATE: 157.706 312.264 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: 0.305587 0.155533 RATE: 32.7239 64.2949 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: 0.148669 0.0845229 RATE: 67.2634 118.311 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: 0.752101 0.389972 RATE: 13.2961 25.6429 ZIGGURAT_OPENMP: Normal end of execution. 11 May 2025 08:31:36 PM 11 May 2025 08:31:36 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: 0.0663685 0.0165088 RATE: 150.674 605.739 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: 0.295557 0.0762168 RATE: 33.8344 131.205 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: 0.154815 0.0373019 RATE: 64.5934 268.083 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: 0.772414 0.189644 RATE: 12.9464 52.7303 ZIGGURAT_OPENMP: Normal end of execution. 11 May 2025 08:31:37 PM 11 May 2025 08:31:37 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: 0.0651726 0.0266717 RATE: 153.439 374.929 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: 0.289354 0.0487052 RATE: 34.5597 205.317 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: 0.149214 0.033447 RATE: 67.0178 298.98 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: 0.764578 0.132604 RATE: 13.0791 75.4124 ZIGGURAT_OPENMP: Normal end of execution. 11 May 2025 08:31:39 PM