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A hybrid parareal Monte-Carlo algorithm for parabolic problems *

Abstract : In this work, we examine a hybrid Monte-Carlo/deterministic approach for a toy model based on the parabolic time-dependent diffusion equation. We consider two different solvers: a low-cost "coarse" solver based on a deterministic Galerkin scheme and a "fine" solver based on a Monte-Carlo resolution. We use a hybrid "parareal-in-time" algorithm based on these two solvers to reduce the computational cost with respect to a full Monte-Carlo simulation. In a set of benchmark numerical experiments, we compare our hybrid parareal strategy with a standard full Monte-Carlo solution of the time-dependent diffusion equation. In particular, we show that for a large number of processors, our hybrid strategy significantly reduces the computational time of the simulation while preserving its accuracy. The convergence properties of the proposed Monte-Carlo/deterministic parareal strategy are also discussed.
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Preprints, Working Papers, ...
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Contributor : Jad Dabaghi <>
Submitted on : Tuesday, February 16, 2021 - 8:52:49 PM
Last modification on : Sunday, March 14, 2021 - 3:22:02 AM


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  • HAL Id : hal-03143554, version 1


Jad Dabaghi, Yvon Maday, Andrea Zoia. A hybrid parareal Monte-Carlo algorithm for parabolic problems *. 2021. ⟨hal-03143554v1⟩



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