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We present FlowPM, a Particle-Mesh (PM) cosmological N-body code implementedin Mesh-TensorFlow for GPU-accelerated, distributed, and differentiablesimulations. We implement and validate the accuracy of a novel multi-gridscheme based on multiresolution pyramids to compute large scale forcesefficiently on distributed platforms. We explore the scaling of the simulationon large-scale supercomputers and compare it with corresponding python based PMcode, finding on an average 10x speed-up in terms of wallclock time. We alsodemonstrate how this novel tool can be used for efficiently solving large scalecosmological inference problems, in particular reconstruction of cosmologicalfields in a forward model Bayesian framework with hybrid PM and neural networkforward model. We provide skeleton code for these examples and the entire codeis publicly available at https://github.com/modichirag/flowpm.

FlowPM: Distributed TensorFlow Implementation of the FastPM Cosmological N-body Solver