New Bounds on Optimal Sorting Networks
Abstract
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. Furthermore, we show that our sorting network for 17 inputs is optimal in the sense that no sorting network using less layers exists. This solves the main open problem of [D. Bundala & J. Za\'vodn\'y. Optimal sorting networks, Proc. LATA 2014].
Turn this paper into a lesson
ArcXiv compiles a structured reading guide from this paper's metadata: plain-English importance, contributions, prerequisite concepts, which sections to read first, flashcards, and a quiz. Grounded in the abstract, never invented.