GPU Accelerated Manifold Correction Method For Spinning Compact Binaries

All of us hope there be fine accuracy and velocity for numerical value scientific computing.The computing pattern of GPU combined with CPU has been widely used in numeric calculating field in recent years.The graphics processing unit(GPU)acceleration of the manifold correction algorithm based on the compute unified device architecture(CUDA)technology is designed to simulate the dynamic evolution of the Post-Newtonian(PN)Hamiltonian formulation of spinning compact binaries.The feasibility and the efficiency of parallel computation on GPU have been confirmed by various numerical experiments.To inspected the accuracy and velocity results,this paper will draw charts of the data set.The results show that the accelerated data compared with original data have no error in numerical precision and the times of computational process have been more short.acceleration ability when the codes are implemented on GPU can increase enormously through the use of shared memory and register optimization techniques without additional hardware costs,implying that the speedup is nearly 13 times as compared with the codes executed on CPU for phase space scan(including 314 × 314 orbits).In addition,GPU accelerated manifold correction method is used to numerically study how dynamics are affected by the spininduced quadrupole–monopole interaction for black hole binary system.In this paper GPU accelerated theory also be applied to finite difference time domain(FDTD)to simulate electromagnetic wave propagation in plasma and than simulate the refractive coefficient and reflective coefficient.The actual numerical experiment results show that the maximum speed-up ratio can be tens of times.