GPU accelerated manifold correction method for spinning compact binaries
Chong-xi Ran, Song Liu, Shuang-ying Zhong

TL;DR
This paper introduces a GPU-accelerated manifold correction method for simulating spinning compact binaries, significantly improving computational speed while maintaining accuracy, and enabling detailed studies of binary dynamics.
Contribution
The paper presents a novel GPU-based implementation of the manifold correction method, achieving nearly 13x speedup and enabling efficient long-term simulations of spinning compact binaries.
Findings
GPU implementation maintains accuracy comparable to CPU methods.
Speedup of nearly 13 times achieved with GPU acceleration.
Enabled detailed numerical study of spin effects on binary dynamics.
Abstract
The conservative Post-Newtonian (PN) Hamiltonian formulation of spinning compact binaries has six integrals of motion including the total energy, the total angular momentum and the constant unit lengths of spins. The manifold correction method can effectively eliminate the integration errors accumulation in a long time. In this paper, the accelerated manifold correction method based on graphics processing unit (GPU) is designed to simulate the dynamic evolution of spinning compact binaries. The feasibility and the efficiency of parallel computation on GPU for spinning compact binaries have been confirmed by various numerical experiments. The numerical comparisons show that the accuracy on GPU execution of manifold corrections method has a good agreement with the execution of codes on merely central processing unit (CPU-based) method. The acceleration ability when the codes are…
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