Optimized massively parallel solving of N-Queens on GPGPUs

Continuous evolution and improvement of GPGPUs has significantly broadened areas of application. The massively parallel platform they offer, paired with the high efficiency of performing certain operations, opens many questions on the development of suitable techniques and algorithms. In this work, we present a novel algorithm and create a massively parallel, GPGPU-based solver for enumerating solutions of the N-Queens problem. We discuss two implementations of our algorithm for GPGPUs and provide insights on the optimizations we applied. We also evaluate the performance of our approach and compare our work to existing literature, showing a clear reduction in computational time.