Massively parallel computation of atmospheric neutrino oscillations on CUDA-enabled accelerators

The computation of neutrino flavor transition amplitudes through inhomogeneous matter is a time-consuming step and thus could benefit from optimization and parallelization. Next to reliable parameter estimation of intrinsic physical quantities such as neutrino masses and mixing angles, these transition amplitudes are important in hypothesis testing of potential extensions of the standard model of elementary particle physics, such as additional neutrino flavors. Hence, fast yet precise implementations are of high importance to research. In the recent past, massively parallel accelerators such as CUDA-enabled GPUs featuring thousands of compute units have been widely adopted due to their superior memory bandwidth, vast compute capability, and highly competitive compute-to-energy ratio in comparison to traditional multi-core architectures with a few tens of monolithic cores. In this paper, we introduce two scalable multi-GPU extensions of common neutrino oscillation frameworks - namely Prob3++ and vSQuIDS - allowing for the acceleration of oscillation dynamics computation by one to three orders-of-magnitude while preserving numerical accuracy. (C) 2018 Elsevier B.V. All rights reserved.