A. Augusto Alves Junior

Thank you very much G. Jones, I will look into it right now and update the testing code. I will post back here the results. About the impact of the PRNG quality in the results, it is hard to say for sure, agree. Also, it would be harder to find out than just update the PRNG for a reliable one. It is plenty of choice around, with very good performances. Let's see...

Thank you very much Lorenzo. Your results just confirmed my suspicions. Ï will update my testing wrapper to perform the byte extraction in the way you did, and document well the whole thing, to recomend the core developers the adoption of a more reliable PRNG. Thank you very much.

Hi Lorenzo, thank you very much. Can you access the repository below? https://gitlab.ikp.kit.edu/AAAlvesJr/C7PRNG It is a cmake project. Building: >> cd C7PRNG >> mkdir build >> cd build >> cmake ../ >> make You can use prng_streamer to run PractRand. Usage: /prng_streamer -s{0,1,2} -m{0,1,2}| /opt/practrand/RNG_test stdin Options: -s: sequence number: the generator is generating 3 sequences in chunks of 1024 numbers. -m: test mode. 0 [ naive conversion of double to uint64_t ] ; 1 [ test the higher...

Hi Lorenzo, thank you very much. Can you access the repository below? https://gitlab.ikp.kit.edu/AAAlvesJr/C7PRNG It is a cmake project. Building: >> cd C7PRNG >> mkdir build >> cd build >> cmake ../ >> make You can use prng_streamer to run PractRand. Usage: /prng_streamer -s{0,1,2} -m{0,1,2}| /opt/practrand/RNG_test stdin Options: -s: sequence number: the generator is generating 3 sequences in chunks of 1024 numbers. -m: test mode. 0 [ naive conversion of double to uint64_t ] ; 1 [ test the higher...

The version I am tested is part of a major, and quite legacy, simulation tool and was originaly coded in FORTRAN at CERNLIB. It produces doubles as output. The generator passes TestU01, but the amount of tested data there is relatively small, as you know. Basically, for each generated double x I do : uint64_t y; uint32_t z; memcpy( &y, &x, sizeof(double) ); z = (y>>20); //for the 32 higher random bits of the mantissa // or z=y; // for the 32 lower random bits of the mantissa then I stream out to...

The version I am tested is part of a major, and quite legacy, simulation tool and was originaly coded in FORTRAN at CERNLIB. It produces doubles as output. The generator passes TestU01, but the amount of tested data there is relatively small, as you know. Basically, for each generated double x I do : uint64_t y; uint32_t z; memcpy( &y, &x, sizeof(double) ); z = (x>>20); //for the 32 higher random bits of the mantissa // or z=x; // for the 32 lower random bits of the mantissa then I stream out to...

Hi Guys, First of all let me presents my contratulations for the very nice and usefull project. Here is my question: I am dealing with a legacy PRNG, the one described in the paper "George Marsaglia, Arif Zaman, Wai Wan Tsang - Toward a universal random number generator, Statistics & Probability Letters, Volume 9, Issue 1, 1990, Pages 35-39, https://doi.org/10.1016/0167-7152(90)90092-L" , which generates uniform doubles in the range [0. , 1. ]. Is it possible to test it using practrand ? If yes,...