FlowPM

FlowPM: Distributed TensorFlow Implementation of the FastPM Cosmological N-body Solver. We present FlowPM, a Particle-Mesh (PM) cosmological N-body code implemented in Mesh-TensorFlow for GPU-accelerated, distributed, and differentiable simulations. We implement and validate the accuracy of a novel multi-grid scheme based on multiresolution pyramids to compute large scale forces efficiently on distributed platforms. We explore the scaling of the simulation on large-scale supercomputers and compare it with corresponding python based PM code, finding on an average 10x speed-up in terms of wallclock time. We also demonstrate how this novel tool can be used for efficiently solving large scale cosmological inference problems, in particular reconstruction of cosmological fields in a forward model Bayesian framework with hybrid PM and neural network forward model. We provide skeleton code for these examples and the entire code is publicly available at this https URL.

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References in zbMATH (referenced in 1 article )

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  1. Vanessa Böhm, Yu Feng, Max E. Lee, Biwei Dai: MADLens, a python package for fast and differentiable non-Gaussian lensing simulations (2020) arXiv