 Sequential, parallel , single-GPU and multi-GPU implementations are analyzed and compared with the state-of-the-art total viewshed computation algorithm. Experiments show that sDEM achieves an acceleration rate of up to 827.3 times for the best multi-GPU execution approach with respect to the best multi-core implementation .
<meaning-changed>  Sequential, parallel , single-GPU and multi-GPU implementations are analyzed and compared with the state-of-the-art total viewshed computation algorithm. Experiments show that sDEM achieves an acceleration rate of up to 827.3 times for the best multi-GPU execution approach with respect to the best multi-core implementation .
 Sequential, parallel , single-GPU and multi-GPU implementations are analyzed and compared with the state-of-the-art algorithm. In the first experiment, sDEM is on average 8.8x faster than current GIS software despite being able to consider only few points because of their limitations. In the second experiment, sDEM is 827.3 times for the best multi-GPU execution approach with respect to the best multi-core implementation .