Causal convolutional neural networks reconstruct neutron star observables for static, Keplerian, and rotating configurations in about 50 milliseconds per equation of state, compared to 30 minutes with traditional RNS calculations.
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A Kokkos-based C++ port of the SACRA numerical relativity code achieves ~10x speedup on GPU/APU over the Fortran CPU version while preserving waveform accuracy, pi-symmetry, and second-order convergence.
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Reconstruction of fast-rotating neutron star observables with the neural network
Causal convolutional neural networks reconstruct neutron star observables for static, Keplerian, and rotating configurations in about 50 milliseconds per equation of state, compared to 30 minutes with traditional RNS calculations.
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SACRA-K: A Performance-Portable Numerical Relativity Code with Kokkos
A Kokkos-based C++ port of the SACRA numerical relativity code achieves ~10x speedup on GPU/APU over the Fortran CPU version while preserving waveform accuracy, pi-symmetry, and second-order convergence.