MASTISK
Tinish Bhattacharya, Vivek Parmar, Manan Suri

TL;DR
MASTISK is an open-source MATLAB framework for designing and simulating neuromorphic hardware with nanodevices, supporting detailed device, circuit, and architecture modeling for spiking neural networks with advanced learning rules.
Contribution
It introduces a versatile, hierarchical simulation tool that enables detailed modeling of nanodevice-based neuromorphic systems with customizable synaptic and neuronal components.
Findings
Supports arbitrary synaptic circuit modeling with various stimuli
Enables flexible spike modeling and nanodevice neuron emulation
Provides validated simulation capabilities for neuromorphic hardware design
Abstract
In this paper, we present MASTISK (MAchine-learning and Synaptic-plasticity Technology Integrated Simulation frameworK). MASTISK is an open-source versatile and flexible tool developed in MATLAB for design exploration of dedicated neuromorphic hardware using nanodevices and hybrid CMOS-nanodevice circuits. MASTISK has a hierarchical organization capturing details at the level of devices, circuits (i.e. neurons or activation functions, synapses or weights) and architectures (i.e. topology, learning-rules, algorithms). In the current version, MASTISK provides user-friendly interface for design and simulation of spiking neural networks (SNN) powered by spatio-temporal learning rules such as Spike-Timing Dependent Plasticity (STDP). Users may provide network definition as a simple input parameter file and the framework is capable of performing automated learning/inference simulations.…
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Taxonomy
TopicsSex and Gender in Healthcare
