Modeling and Simulation of Asynchrony in Neuromorphic Computing
Zareen Sheikh1, Vivek Khetade2

1Zareen Sheikh, Department of Electronics Engineering, Shri Ramdeobaba College of Engineering and Management, Nagpur, India.
2Vivek Khetade, Assistant Professor, Department of Electronics Design Technology, Shri Ramdeobaba College of Engineering and Management, Nagpur, India.
Manuscript received on 28 June 2019 | Revised Manuscript received on 05 July 2019 | Manuscript published on 30 July 2019 | PP: 676-685 | Volume-8 Issue-9, July 2019 | Retrieval Number: I7747078919/19©BEIESP | DOI: 10.35940/ijitee.I7747.078919

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Abstract: Neuromorphic computing is a non-von Neumann architecture which is also referred to as artificial neural network and that allows electronic system to function in the same manner as that of the human brain. In this paper we have developed neural core architecture analogous to that of the human brain. Each neural core has its own computational element neuron, memory to store information and local clock generator for synchronous functioning of neuron along with asynchronous input-output port and its port controller. The neuron model used here is a tailor-made of IBM TrueNorth’s neuron block. Our design methodology includes both synchronous and asynchronous circuit in order to build an event-driven neural network core. We have first simulated our design using Neuroph studio in order to calculate the weights and bias value and then used these weights for hardware implementation. With that we have successfully demonstrated the working of neural core using XOR application. It was designed in VHDL language and simulated in Xilinx ISE software.
Index Terms: IBM TrueNorth, Neuromorphic Computing, Port Controller, Synchronous-Asynchronous Design.

Scope of the Article: Simulation Optimization and Risk Management