Abstract
The processing unit is the most essential part in an artificial neural network. The processing unit performs the complex parallel computations that are important for the efficient working of the neuron which along with the activation unit makes up an artificial neural network. In our work, we have proposed an efficient MAC (Multiplication and Accumulation) unit which can be implemented as the processing unit in an ANN. It makes use of Vedic Multiplier, Carry Select Adder (CSLA) and Ripple Carry Adder (RCA) using reversible logic gates. Our design attempts to be superior than the current implementations as far as area and delay are concerned. An efficient MAC processing unit can improve the speed of ANN to a larger extent. The Verilog HDL design language was used to create and implement our proposed MAC unit, and the results were analyzed.
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Apoorva, B.S., Amjad, M.A., Bharatha, O., Surya, P.S., Nagendra Prasad, S. (2022). Design of MAC Unit for an Artificial Neural Network Using Reversible Logic Gates. In: Tripathi, A., Soni, A., Shrivastava, A., Swarnkar, A., Sahariya, J. (eds) Intelligent Computing Techniques for Smart Energy Systems. Lecture Notes in Electrical Engineering, vol 862. Springer, Singapore. https://doi.org/10.1007/978-981-19-0252-9_27
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