An adaptive prefix-assignment technique for symmetry reduction

This paper presents a technique for symmetry reduction that adaptively assigns a prefix of variables in a system of constraints so that the generated prefix-assignments are pairwise nonisomorphic under the action of the symmetry group of the system. The technique is based on McKay's canonical extension framework [J.~Algorithms 26 (1998), no.~2, 306--324]. Among key features of the technique are (i) adaptability---the prefix sequence can be user-prescribed and truncated for compatibility with the group of symmetries; (ii) parallelizability---prefix-assignments can be processed in parallel independently of each other; (iii) versatility---the method is applicable whenever the group of symmetries can be concisely represented as the automorphism group of a vertex-colored graph; and (iv) implementability---the method can be implemented relying on a canonical labeling map for vertex-colored graphs as the only nontrivial subroutine. To demonstrate the practical applicability of our technique, we have prepared an experimental open-source implementation of the technique and carry out a set of experiments that demonstrate ability to reduce symmetry on hard instances. Furthermore, we demonstrate that the implementation effectively parallelizes to compute clusters with multiple nodes via a message-passing interface.Comment: Updated manuscript submitted for revie

Data Detection and Code Channel Allocation for Frequency-Domain Spread ACO-OFDM Systems Over Indoor Diffuse Wireless Channels

Future optical wireless communication systems promise to provide high-speed data transmission in indoor diffuse environments. This paper considers frequency-domain spread asymmetrically clipped optical orthogonal frequency-division multiplexing (ACOOFDM) systems in indoor diffuse channels and aims to develop efficient data detection and code channel allocation schemes. By exploiting the frequency-domain spread concept, a linear multi-code detection scheme is proposed to maximize the signal to interference plus noise ratio (SINR) at the receiver. The achieved SINR and bit error ratio (BER) performance are analyzed. A computationally efficient code channel allocation algorithm is proposed to improve the BER performance of the frequency-domain spread ACO-OFDM system. Numerical results show that the frequency-domain spread ACO-OFDM system outperforms conventional ACO-OFDM systems in indoor diffuse channels. Moreover, the proposed linear multi-code detection and code channel allocation algorithm can improve the performance of optical peak-to-average power ratio (PAPR

Distributed Verification of Rare Properties using Importance Splitting Observers

Rare properties remain a challenge for statistical model checking (SMC) due to the quadratic scaling of variance with rarity. We address this with a variance reduction framework based on lightweight importance splitting observers. These expose the model-property automaton to allow the construction of score functions for high performance algorithms. The confidence intervals defined for importance splitting make it appealing for SMC, but optimising its performance in the standard way makes distribution inefficient. We show how it is possible to achieve equivalently good results in less time by distributing simpler algorithms. We first explore the challenges posed by importance splitting and present an algorithm optimised for distribution. We then define a specific bounded time logic that is compiled into memory-efficient observers to monitor executions. Finally, we demonstrate our framework on a number of challenging case studies

Submicron Systems Architecture Project: Semiannual Technical Report

No abstract available