We describe Renesis, an automated synthesis tool that accepts an ordinary irreversible netlist and produces a verified, technology-mapped energy-recovery (adiabatic) circuit, using energy rather than area or delay as the optimization criterion. Renesis models the netlist with a vector-space formulation that expresses simulation and justification sweeps as forward and reverse traversals whose cost is linear in the number of circuit components. The traversals populate ledgers with data tags that characterize switching, erasure, and observability information at their natural R\'enyi orders. The output is a logically reversible circuit mapped to one of eight energy-recovery families, with the associated parameters reported. Reversibility is treated here as a circuit-level requirement rather than a thermodynamic one. When an adiabatic gate erases information the penalty is not $k_B T \ln 2$ but a full non-adiabatic $CV^2$ discharge, which is comparable to the switching energy the circuit style exists to recover. Every synthesis transformation is equivalence-checked, and it must improve one of two reported cost tables, one uncapped and one after a series-realizability bound, while worsening neither before it is accepted. Across a twenty-circuit development set, optional re-synthesis passes improve fourteen circuits. On a held-out set of twenty circuits, fifteen of nineteen are improved, with a best-arm median of $0.91$ of the default energy. A certified optimality-gap program computes the distance between the synthesized circuits and the provable floor of the tool's own search space. A device-level SPICE deck reproduces the tool's per-cycle energy figures on the reference family. The tool, the benchmark netlists, the validation procedure, and the run records behind every reported number are released as open source.
It is proved that the local ZX simplification layer (spider fusion and identity removal) computes exactly the free-product normal form of Z_2 * Z_8, giving exact per-instance compression and, under a calibrated ergodicity hypothesis, a depth-independent limit law confirmed on two independently constructed nets.
Chon-Fai Kam, A. Mahasinghe, Kaushika De Silva et al.· 0 citations
LevelSyn is a novel physical-aware logic synthesis framework that integrates hierarchical representation learning with a wirelength-driven optimization engine that significantly outperforms state-of-the-art methods on the EPFL benchmark suite.
Jing-Yi Zhou, Zhengyuan Shi, Zi-Yang Zheng et al.· 0 citations
Following Moore's Law, the ever-increasing complexity, i.e., the number of logic gates, of digital systems poses significant challenges for verification at the netlist (i.e., logic gate) level. On the one hand, the inherent bit-level parallelism exposed by netlists cannot be efficiently exploited to accelerate simulati...
M. Weißbrich, Mohamed Wassim Chebili, G. Payá-Vayá· IEEE International Conferenc...· 0 citations
A novel variation of high-effort logic synthesis called transduction is presented, which performs transformation and reduction using don’t-cares to restructure the circuit.
Yukio Miyasaka, Alan Mishchenko, John Wawrzynek et al.· 0 citations
A unified, highly scalable methodology for the optimal design of reversible circuits across both libraries is presented, establishing best-known upper bounds that significantly outperform heuristic literature benchmarks.
Programmable quantum annealers are used for optimization, probabilistic sampling, and simulation, but their performance is commonly reported without the energy exchanged during computation. Here we characterize the D-Wave quantum annealer as a closed thermodynamic cycle. From initial and final Ising energies and an eff...
Jakub Pawłowski, Tomasz Śmierzchalski, Fengping Jin et al.· 0 citations
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