Tina’s Random Number Generator Library (TRNG) is a state of the art C++ pseudo-random number generator library for sequential and parallel Monte Carlo simulations. Its design principles are based on a proposal for an extensible random number generator facility, that will be part of the random number generator facility of the forthcoming revision of the C++ standard. The TRNG library features an object oriented design, is easy to use and has been speed optimized. Its implementation does not depend on any communication library or hardware architecture. TRNG is suited for shared memory as well as for distributed memory computers and may be used in any parallel programming environment, e.g. Message Passing Standard, OpenMP or CUDA. All generators, that are implemented by TRNG, have been subjected to thorough statistical tests in sequential and parallel setups.
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References in zbMATH (referenced in 9 articles )
Showing results 1 to 9 of 9.
- Kiefer, Nicholas; Oremek, Maximilian J.; Hoeft, Andreas; Zenker, Sven: Model-based quantification of left ventricular diastolic function in critically ill patients with atrial fibrillation from routine data: a feasibility study (2019)
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- Osborn, Sarah; Vassilevski, Panayot S.; Villa, Umberto: A multilevel, hierarchical sampling technique for spatially correlated random fields (2017)
- Xu, Yi-Zhi; Zhou, Hai-Jun: Optimal segmentation of directed graph and the minimum number of feedback arcs (2017)
- Li, Yao: On the stochastic behaviors of locally confined particle systems (2015)
- Demchik, Vadim: Pseudorandom numbers generation for Monte Carlo simulations on GPUs: OpenCL approach (2014)
- Mascagni, Michael; Hin, Lin-Yee: Parallel pseudo-random number generators: a derivative pricing perspective with the Heston stochastic volatility model (2013)
- Mascagni, Michael; Hin, Lin-Yee: Parallel random number generators in Monte Carlo derivative pricing: an application-based test (2012)
- Behnia, S.; Akhavan, A.; Akhshani, A.; Samsudin, A.: A novel dynamic model of pseudo random number generator (2011)