18 citations · 74 across the 23 of their papers we have counts for
24 papers
Mixing and Merging Metric Spaces using Directed Graphs
Mahir Bilen Can, Shantanu Chakrabartty
Let be metric spaces with and let . Let be a directed graph with vertex set and…
KALAM: toolKit for Automating high-Level synthesis of Analog computing systeMs
Ankita Nandi, Krishil Gandhi, Mahendra Pratap Singh +2
Diverse computing paradigms have emerged to meet the growing needs for intelligent energy-efficient systems. The Margin Propagation (MP) framework, being one such initiative in the…
Margin Propagation based XOR-SAT Solvers for Decoding of LDPC Codes
Ankita Nandi, Shantanu Chakrabartty, Chetan Singh Thakur
Decoding of Low-Density Parity Check (LDPC) codes can be viewed as a special case of XOR-SAT problems, for which low-computational complexity bit-flipping algorithms have been prop…
Estimation of Energy-dissipation Lower-bounds for Neuromorphic Learning-in-memory
Zihao Chen, Faiek Ahsan, Johannes Leugering +2
Neuromorphic or neurally-inspired optimizers rely on local but parallel parameter updates to solve problems that range from quadratic programming to Ising machines. An ideal realiz…
Neuromorphic Computing with AER using Time-to-Event-Margin Propagation
Madhuvanthi Srivatsav R, Shantanu Chakrabartty, Chetan Singh Thakur
Address-Event-Representation (AER) is a spike-routing protocol that allows the scaling of neuromorphic and spiking neural network (SNN) architectures to a size that is comparable t…
Multiplierless In-filter Computing for tinyML Platforms
Abhishek Ramdas Nair, Pallab Kumar Nath, Shantanu Chakrabartty +1
Wildlife conservation using continuous monitoring of environmental factors and biomedical classification, which generate a vast amount of sensor data, is a challenge due to limited…
A Framework for Analyzing Cross-correlators using Price's Theorem and Piecewise-Linear Decomposition
Zhili Xiao, Shantanu Chakrabartty
Precise estimation of cross-correlation or similarity between two random variables lies at the heart of signal detection, hyperdimensional computing, associative memories, and neur…
On-device Synaptic Memory Consolidation using Fowler-Nordheim Quantum-tunneling
Mustafizur Rahman, Subhankar Bose, Shantanu Chakrabartty
Synaptic memory consolidation has been heralded as one of the key mechanisms for supporting continual learning in neuromorphic Artificial Intelligence (AI) systems. Here we report…
Process, Bias and Temperature Scalable CMOS Analog Computing Circuits for Machine Learning
Pratik Kumar, Ankita Nandi, Shantanu Chakrabartty +1
Analog computing is attractive compared to digital computing due to its potential for achieving higher computational density and higher energy efficiency. However, unlike digital c…
Bias-Scalable Near-Memory CMOS Analog Processor for Machine Learning
Pratik Kumar, Ankita Nandi, Shantanu Chakrabartty +1
Bias-scalable analog computing is attractive for implementing machine learning (ML) processors with distinct power-performance specifications. For instance, ML implementations for…
A Dynamical Systems Framework for Generating the Riemann Zeta Function and Dirichlet L-functions
Shantanu Chakrabartty
We first construct a dynamical systems model which in its steady-state serves as an analytic continuation of the completed Riemann zeta function over the entire critical strip. The…
In-filter Computing For Designing Ultra-light Acoustic Pattern Recognizers
Abhishek Ramdas Nair, Shantanu Chakrabartty, Chetan Singh Thakur
We present a novel in-filter computing framework that can be used for designing ultra-light acoustic classifiers for use in smart internet-of-things (IoTs). Unlike a conventional a…
Using growth transform dynamical systems for spatio-temporal data sonification
Oindrila Chatterjee, Shantanu Chakrabartty
Sonification, or encoding information in meaningful audio signatures, has several advantages in augmenting or replacing traditional visualization methods for human-in-the-loop deci…
Multiplierless MP-Kernel Machine For Energy-efficient Edge Devices
Abhishek Ramdas Nair, Pallab Kumar Nath, Shantanu Chakrabartty +1
We present a novel framework for designing multiplierless kernel machines that can be used on resource-constrained platforms like intelligent edge devices. The framework uses a pie…
An Adaptive Synaptic Array using Fowler-Nordheim Dynamic Analog Memory
Darshit Mehta, Kenji Aono, Shantanu Chakrabartty
In this paper we present a synaptic array that uses dynamical states to implement an analog memory for energy-efficient training of machine learning (ML) systems. Each of the analo…
SPoTKD: A Protocol for Symmetric Key Distribution over Public Channels Using Self-Powered Timekeeping Devices
Mustafizur Rahman, Liang Zhou, Shantanu Chakrabartty
In this paper, we propose a novel class of symmetric key distribution protocols that leverages basic security primitives offered by low-cost, hardware chipsets containing millions…
A Self-powered Analog Sensor-data-logging Device based on Fowler-Nordheim Dynamical Systems
Darshit Mehta, Kenji Aono, Shantanu Chakrabartty
Continuous, battery-free operation of sensor nodes requires ultra-low-power sensing and data-logging techniques. Here we report that by directly coupling a sensor/transducer signal…
Multiplierless and Sparse Machine Learning based on Margin Propagation Networks
Nazreen P. M., Shantanu Chakrabartty, Chetan Singh Thakur
The new generation of machine learning processors have evolved from multi-core and parallel architectures that were designed to efficiently implement matrix-vector-multiplications…
Resonant Machine Learning Based on Complex Growth Transform Dynamical Systems
Oindrila Chatterjee, Shantanu Chakrabartty
Traditional energy-based learning models associate a single energy metric to each configuration of variables involved in the underlying optimization process. Such models associate…
Neuromorphic In-Memory Computing Framework using Memtransistor Cross-bar based Support Vector Machines
P. Kumar, A. R. Nair, O. Chatterjee +4
This paper presents a novel framework for designing support vector machines (SVMs), which does not impose restriction on the SVM kernel to be positive-definite and allows the user…
A Unified Perspective of Evolutionary Game Dynamics Using Generalized Growth Transforms
Oindrila Chatterjee, Shantanu Chakrabartty
In this paper, we show that different types of evolutionary game dynamics are, in principle, special cases of a dynamical system model based on our previously reported framework of…
A Fowler-Nordheim Integrator can Track the Density of Prime Numbers
Liang Zhou, SriHarsha Kondapalli, Shantanu Chakrabartty
"Does there exist a naturally occurring counting device that might elucidate the hidden structure of prime numbers ?" is a question that has fascinated computer scientists and math…
Global Optimization based on Growth Transform Dynamical Model
Oindrila Chatterjee, Shantanu Chakrabartty
Conservation principles like conservation of charge or energy provide a natural way to couple and constrain different physical variables. In this letter, we propose a dynamical sys…
Energy-dissipation Limits in Variance-based Computing
Sri Harsha Kondapalli, Xuan Zhang, Shantanu Chakrabartty
Variance-based logic (VBL) uses the fluctuations or the variance in the state of a particle or a physical quantity to represent different logic levels. In this letter we show that…