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Reversible circuits are vulnerable to intellectual property and integrated circuit piracy. To show these vulnerabilities, a detailed understanding on how to identify the function embedded in a reversible circuit is crucial. To obtain the embedded function, one needs to know the synthesis approach used to generate the reversible circuit in the first place. We present a machine learning based scheme...
Synthesis of reversible circuits finds application in many promising domains but has to deal with the fact that the underlying circuits require a unique mapping from the inputs to the outputs. Existing solutions addressed this problem by additionally performing a so-called embedding process prior to synthesis or by naively mapping building blocks of conventional logic to their corresponding reversible...
Encoders play an important role in many areas such as memory addressing, data demultiplexing, or for interconnect solutions. However, design solutions for the automatic synthesis of corresponding circuits suffer from various drawbacks, e.g. they are often not scalable, do not exploit the full degree of freedom, or are applicable to realize certain codes only. All these problems are caused by the fact...
Reversible computation became established as a promising concept due to its application in various areas like quantum computation, energy-aware circuits, and further areas. Unfortunately, most functions of interest are non-reversible. Therefore, a process called embedding has to be conducted to transform a non-reversible function into a reversible one — a coNP-hard problem. Existing solutions suffer...
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