On Scalability of Hybrid Monte Carlo Methods on advanced architectures and their sensitivity to random numbers

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Persistent URL	http://purl.org/net/epubs/work/63574884
Record Status	Checked
Record Id	63574884
Title	On Scalability of Hybrid Monte Carlo Methods on advanced architectures and their sensitivity to random numbers
Contributors	A Lebedev (STFC Daresbury Lab.) (Pr.Au.), O Ivanyshyn Yaman (STFC Daresbury Lab.), E Sahin (STFC Daresbury Lab.), M Abalenkovs (STFC Daresbury Lab.), V Alexandrov (STFC Daresbury Lab.)
Abstract	This presentation was given at the Large Scale Scientific Computations conference. We present the recent observations on the use of Markov Chain Monte Carlo method for the computation of preconditioners for large sparse linear systems. We further present eraly-stage observations of the effect of using a quantum random number generator instead of a parallel pseudo-random number generator.
Organisation	STFC , HC
Keywords	numerical linear algebra , iterative methods , Markov Chain Monte Carlo , stochastic methods , quantum random number generator
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Licence Information:	Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
Language	English (EN)

Type	Details	URI(s)	Local file(s)	Year
Presentation	Presented at 14th International Conference on Large Scale Scientific Computations (LSSC 2023), Sozopol, Bulgaria, 5-9 Jun 2023.		AL_MCMCMI_LSSC23_final.pdf	2023