TL;DR
This paper introduces a GPU-accelerated parallel method for quantum system time evolution integration using batched BLAS routines, significantly improving performance for small to medium systems.
Contribution
It presents a novel parallel time integration algorithm leveraging batched BLAS routines on GPUs, enabling efficient quantum system simulations.
Findings
Significant performance improvements for small to medium quantum systems.
Implementation using CUDA-enabled GPUs with batched BLAS routines.
Easy portability across platforms due to reliance on standard routines.
Abstract
We present an approach for integrating the time evolution of quantum systems. We leverage the computation power of graphics processing units (GPUs) to perform the integration of all time steps in parallel. The performance boost is especially prominent for small to medium-sized quantum systems. The devised algorithm can largely be implemented using the recently-specified batched versions of the BLAS routines, and can therefore be easily ported to a variety of platforms. Our PARAllelized Matrix Exponentiation for Numerical Time evolution (PARAMENT) implementation runs on CUDA-enabled graphics processing units.
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