SPRNG

Algorithm 806: SPRNG: A Scalable Library for Pseudorandom Number Generation. SPRNG 1.0 provides the user the various SPRNG random number generators each in its own library. For most users this is acceptable, as one rarely uses more than one type of generator in a single program. However, if the user desires this added flexibility, SPRNG 2.0 provides it. In all other respects, SPRNG 1.0 and SPRNG 2.0 are identical. Both versions only uses the GNU Multi Precision (GMP) package for one of their generators. SPRNG 3.0 uses GMP for all generators. SPRNG 4.0 is a C++ version with the GMP package removed. It is not backwards compatible with any of the previous SPRNG versions, except for its default FORTRAN interface. SPRNG is Y2K compliant software.


References in zbMATH (referenced in 45 articles , 1 standard article )

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  1. Kneusel, Ronald T.: Random numbers and computers (2018)
  2. Aljahdali, Asia; Mascagni, Michael: Feistel-inspired scrambling improves the quality of linear congruential generators (2017)
  3. Barash, L. Yu.; Guskova, M. S.; Shchur, L. N.: Employing AVX vectorization to improve the performance of random number generators (2017)
  4. Beebe, Nelson H. F.: The mathematical-function computation handbook. Programming using the MathCW portable software library (2017)
  5. Jones, Aquil D.; Simpson, Gideon; Wilson, William: Conservative integrators for a toy model of weak turbulence (2017)
  6. L’Ecuyer, Pierre; Munger, David; Oreshkin, Boris; Simard, Richard: Random numbers for parallel computers: requirements and methods, with emphasis on gpus (2017)
  7. Ni, Eric C.; Ciocan, Dragos F.; Henderson, Shane G.; Hunter, Susan R.: Efficient ranking and selection in parallel computing environments (2017)
  8. Lenôtre, Lionel: A strategy for parallel implementations of stochastic Lagrangian simulation (2016)
  9. Binder, Andrew; Lelièvre, Tony; Simpson, Gideon: A generalized parallel replica dynamics (2015)
  10. de Doncker, Elise; Kapenga, John; Assaf, Rida: Monte Carlo automatic integration with dynamic parallelism in CUDA (2014)
  11. Ginting, V.; Pereira, F.; Rahunanthan, A.: A prefetching technique for prediction of porous media flows (2014)
  12. Karl, Andrew T.; Eubank, Randy; Milovanovic, Jelena; Reiser, Mark; Young, Dennis: Using rngstreams for parallel random number generation in C++ and R (2014)
  13. Mascagni, Michael; Qiu, Yue; Hin, Lin-Yee: High performance computing in quantitative finance: a review from the pseudo-random number generator perspective (2014)
  14. Ireland, Peter J.; Vaithianathan, T.; Sukheswalla, Parvez S.; Ray, Baidurja; Collins, Lance R.: Highly parallel particle-laden flow solver for turbulence research (2013)
  15. Mascagni, Michael; Hin, Lin-Yee: Parallel pseudo-random number generators: a derivative pricing perspective with the Heston stochastic volatility model (2013)
  16. A. Talha Yalta, Sven Schreiber: Random Number Generation in gretl (2012) not zbMATH
  17. Balaž, Antun; Vidanović, Ivana; Stojiljković, Danica; Vudragović, Dušan; Belić, Aleksandar; Bogojević, Aleksandar: SPEEDUP code for calculation of transition amplitudes via the effective action approach (2012)
  18. Corsaro, S.; De Angelis, P. L.; Marino, Z.; Perla, F.: Participating life insurance policies: an accurate and efficient parallel software for COTS clusters (2011)
  19. Andreas Alfons; Matthias Templ; Peter Filzmoser: An Object-Oriented Framework for Statistical Simulation: The R Package simFrame (2010) not zbMATH
  20. Corsaro, S.; De Angelis, P. L.; Marino, Z.; Perla, F.; Zanetti, P.: On parallel asset-liability management in life insurance: a forward risk-neutral approach (2010)

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