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Optimal Metastability-Containing Sorting Networks


Bund,  Johannes
Algorithms and Complexity, MPI for Informatics, Max Planck Society;


Lenzen,  Christoph
Algorithms and Complexity, MPI for Informatics, Max Planck Society;

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Bund, J., Lenzen, C., & Medina, M. (2018). Optimal Metastability-Containing Sorting Networks. Retrieved from http://arxiv.org/abs/1801.07549.

Cite as: http://hdl.handle.net/21.11116/0000-0002-1801-2
When setup/hold times of bistable elements are violated, they may become metastable, i.e., enter a transient state that is neither digital 0 nor 1. In general, metastability cannot be avoided, a problem that manifests whenever taking discrete measurements of analog values. Metastability of the output then reflects uncertainty as to whether a measurement should be rounded up or down to the next possible measurement outcome. Surprisingly, Lenzen and Medina (ASYNC 2016) showed that metastability can be contained, i.e., measurement values can be correctly sorted without resolving metastability first. However, both their work and the state of the art by Bund et al. (DATE 2017) leave open whether such a solution can be as small and fast as standard sorting networks. We show that this is indeed possible, by providing a circuit that sorts Gray code inputs (possibly containing a metastable bit) and has asymptotically optimal depth and size. Concretely, for 10-channel sorting networks and 16-bit wide inputs, we improve by 48.46% in delay and by 71.58% in area over Bund et al. Our simulations indicate that straightforward transistor-level optimization is likely to result in performance on par with standard (non-containing) solutions.