Faster Sorting Networks for $17$, $19$ and $20$ Inputs
Thorsten Ehlers, Müller, Mike · arXiv (Cornell University) · 2014
We present new parallel sorting networks for $17$ to $20$ inputs. For $17, 19,$ and $20$ inputs these new networks are faster (i.e., they require less computation steps) than the previously known best networks. Therefore, we improve upon the known upper bounds for minimal depth sorting networks on $17, 19,$ and $20$ channels. The networks were obtained using a combination of hand-crafted first layers and a SAT encoding of sorting networks.