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This paper proposes a versatile mapping approach that has three objectives: i) it can map from one technologyindependent graph representation to another; ii) it can map to a cell library; iii) it supports logic rewriting. The method is cutbased, mitigates logic-sharing issues of previous graph mapping approaches, and exploits structural hashing. The mapper is the first one of its kind to support remapping among various graph representations, thus enabling specialized mapping to emerging technologies (such as AQFP) and for security applications (such as XAG-based design). We show that mapping to MIGs improves area by 10% as compared to the state of the art, and that technology mapping is 18% faster than ABC with slightly better results.

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Contemporary hardware implementations of artificial neural networks face the burden of excess area requirement due to resource-intensive elements such as multiplier and non-linear activation functions. The present work addresses this challenge by proposing a resource-efficient Coordinate Rotation Digital Computer (CORDIC)-based neuron architecture (RECON) which can be configured to compute both multiply-accumulate (MAC) and non-linear activation function (AF) operations. The CORDIC-based architecture uses linear and trigonometric relationships to realize MAC and AF operations respectively. The proposed design is synthesized and verified at 45nm technology using Cadence Virtuoso for all physical parameters. Implementation of the signed fixed-point 8-bit MAC using our design, shows 60% less area, latency, and power product (ALP) and shows improvement by 38% in area, 27% in power dissipation, and 15% in latency with respect to the state-of-the-art MAC design. Further, Monte-Carlo simulations for process-variations and device-mismatch are performed for both the proposed model and the state-of-the-art to evaluate expectations of functions of randomness in dynamic power variation. The dynamic power variation for our design shows that worst-case mean is 189.73μW which is 63% of the state-of-the-art. INDEX TERMS AF, CORDIC, configurable architecture, MAC, neural network.

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