RESPARC: A Reconfigurable and Energy-Efficient Architecture with Memristive Crossbars for Deep Spiking Neural Networks. - Aayush Ankit; Abhronil Sengupta; Priyadarshini Panda; Kaushik Roy 001 (DAC, 2017)

TraNNsformer: Neural network transformation for memristive crossbar based neuromorphic system design. - Aayush Ankit; Abhronil Sengupta; Kaushik Roy 001 (ICCAD, 2017)

Performance analysis and benchmarking of all-spin spiking neural networks (Special session paper). - Abhronil Sengupta; Aayush Ankit; Kaushik Roy 001 (IJCNN, 2017)

SPARE: Spiking Networks Acceleration Using CMOS ROM-Embedded RAM as an In-Memory-Computation Primitive. - Amogh Agrawal; Aayush Ankit; Kaushik Roy 001 (CoRR, 2017)

An All-Memristor Deep Spiking Neural Network: A Step Towards Realizing the Low Power, Stochastic Brain. - Parami Wijesinghe; Aayush Ankit; Abhronil Sengupta; Kaushik Roy 001 (CoRR, 2017)

FALCON: Feature Driven Selective Classification for Energy-Efficient Image Recognition. - Priyadarshini Panda; Aayush Ankit; Parami Wijesinghe; Kaushik Roy 001 (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2017)

Hardware-Software Co-Design for an Analog-Digital Accelerator for Machine Learning. - Joao Ambrosi; Aayush Ankit; Rodrigo Antunes; Sai Rahul Chalamalasetti; Soumitra Chatterjee; Izzat El Hajj; Guilherme Fachini; Paolo Faraboschi; Martin Foltin; Sitao Huang; Wen-Mei Hwu; Gustavo Knuppe; et al. (ICRC, 2018)

Neuromorphic Computing Across the Stack: Devices, Circuits and Architectures. - Aayush Ankit; Abhronil Sengupta; Kaushik Roy 001 (SiPS, 2018)

Energy-Efficient Neural Computing with Approximate Multipliers. - Syed Shakib Sarwar; Swagath Venkataramani; Aayush Ankit; Anand Raghunathan; Kaushik Roy 001 (ACM J. Emerg. Technol. Comput. Syst., 2018)

An All-Memristor Deep Spiking Neural Computing System: A Step Toward Realizing the Low-Power Stochastic Brain. - Parami Wijesinghe; Aayush Ankit; Abhronil Sengupta; Kaushik Roy 001 (IEEE Trans. Emerg. Top. Comput. Intell., 2018)

Cross-Layer Design Exploration for Energy-Quality Tradeoffs in Spiking and Non-Spiking Deep Artificial Neural Networks. - Bing Han 006; Aayush Ankit; Abhronil Sengupta; Kaushik Roy 001 (IEEE Trans. Multi Scale Comput. Syst., 2018)

PUMA: A Programmable Ultra-efficient Memristor-based Accelerator for Machine Learning Inference. - Aayush Ankit; Izzat El Hajj; Sai Rahul Chalamalasetti; Geoffrey Ndu; Martin Foltin; R. Stanley Williams; Paolo Faraboschi; Wen-mei W. Hwu; John Paul Strachan; Kaushik Roy 001; Dejan S. Milojicic (ASPLOS, 2019)

PABO: Pseudo Agent-Based Multi-Objective Bayesian Hyperparameter Optimization for Efficient Neural Accelerator Design. - Maryam Parsa; Aayush Ankit; Amirkoushyar Ziabari; Kaushik Roy 001 (ICCAD, 2019)

Efficient Hybrid Network Architectures for Extremely Quantized Neural Networks Enabling Intelligence at the Edge. - Indranil Chakraborty; Deboleena Roy; Aayush Ankit; Kaushik Roy 001 (CoRR, 2019)

PCA-driven Hybrid network design for enabling Intelligence at the Edge. - Indranil Chakraborty; Deboleena Roy; Isha Garg; Aayush Ankit; Kaushik Roy 001 (CoRR, 2019)

Neural network accelerator design with resistive crossbars: Opportunities and challenges. - Shubham Jain; Aayush Ankit; Indranil Chakraborty; Tayfun Gokmen; Malte J. Rasch; Wilfried Haensch; Kaushik Roy 001; Anand Raghunathan (IBM J. Res. Dev., 2019)

SPARE: Spiking Neural Network Acceleration Using ROM-Embedded RAMs as In-Memory-Computation Primitives. - Amogh Agrawal; Aayush Ankit; Kaushik Roy 001 (IEEE Trans. Computers, 2019)

Xcel-RAM: Accelerating Binary Neural Networks in High-Throughput SRAM Compute Arrays. - Amogh Agrawal; Akhilesh Jaiswal 001; Deboleena Roy; Bing Han 006; Gopalakrishnan Srinivasan; Aayush Ankit; Kaushik Roy 001 (IEEE Trans. Circuits Syst. I Regul. Pap., 2019)

Powerline Communication for Enhanced Connectivity in Neuromorphic Systems. - Aayush Ankit; Minsuk Koo; Shreyas Sen; Kaushik Roy 001 (IEEE Trans. Very Large Scale Integr. Syst., 2019)

In-Memory Computing in Emerging Memory Technologies for Machine Learning: An Overview. - Kaushik Roy 001; Indranil Chakraborty; Mustafa Fayez Ali; Aayush Ankit; Amogh Agrawal (DAC, 2020)

GENIEx: A Generalized Approach to Emulating Non-Ideality in Memristive Xbars using Neural Networks. - Indranil Chakraborty; Mustafa Fayez Ali; Dong Eun Kim; Aayush Ankit; Kaushik Roy 001 (DAC, 2020)

Energy-Efficient Target Recognition using ReRAM Crossbars for Enabling On-Device Intelligence. - Sourav Sanyal; Aayush Ankit; Craig M. Vineyard; Kaushik Roy 001 (SiPS, 2020)

Incremental Learning in Deep Convolutional Neural Networks Using Partial Network Sharing. - Syed Shakib Sarwar; Aayush Ankit; Kaushik Roy 001 (IEEE Access, 2020)

Structured Compression and Sharing of Representational Space for Continual Learning. - Gobinda Saha; Isha Garg; Aayush Ankit; Kaushik Roy 001 (CoRR, 2020)

Circuits and Architectures for In-Memory Computing-Based Machine Learning Accelerators. - Aayush Ankit; Indranil Chakraborty; Amogh Agrawal; Mustafa Fayez Ali; Kaushik Roy 001 (IEEE Micro, 2020)

Constructing energy-efficient mixed-precision neural networks through principal component analysis for edge intelligence. - Indranil Chakraborty; Deboleena Roy; Isha Garg; Aayush Ankit; Kaushik Roy 001 (Nat. Mach. Intell., 2020)

Resistive Crossbars as Approximate Hardware Building Blocks for Machine Learning: Opportunities and Challenges. - Indranil Chakraborty; Mustafa Fayez Ali; Aayush Ankit; Shubham Jain; Sourjya Roy; Shrihari Sridharan; Amogh Agrawal; Anand Raghunathan; Kaushik Roy 001 (Proc. IEEE, 2020)

PANTHER: A Programmable Architecture for Neural Network Training Harnessing Energy-Efficient ReRAM. - Aayush Ankit; Izzat El Hajj; Sai Rahul Chalamalasetti; Sapan Agarwal; Matthew J. Marinella; Martin Foltin; John Paul Strachan; Dejan S. Milojicic; Wen-Mei Hwu; Kaushik Roy 001 (IEEE Trans. Computers, 2020)

TraNNsformer: Clustered Pruning on Crossbar-Based Architectures for Energy-Efficient Neural Networks. - Aayush Ankit; Timur Ibrayev; Abhronil Sengupta; Kaushik Roy 001 (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2020)

Design Tools for Resistive Crossbar based Machine Learning Accelerators. - Indranil Chakraborty; Sourjya Roy; Shrihari Sridharan; Mustafa Fayez Ali; Aayush Ankit; Shubham Jain; Anand Raghunathan (AICAS, 2021)

Mixed Precision Quantization for ReRAM-based DNN Inference Accelerators. - Sitao Huang; Aayush Ankit; Plínio Silveira; Rodrigo Antunes; Sai Rahul Chalamalasetti; Izzat El Hajj; Dong Eun Kim; Glaucimar Aguiar; Pedro Bruel; Sergey Serebryakov; Cong Xu; Can Li; et al. (ASP-DAC, 2021)

SPACE: Structured Compression and Sharing of Representational Space for Continual Learning. - Gobinda Saha; Isha Garg; Aayush Ankit; Kaushik Roy 001 (IEEE Access, 2021)

NAX: Co-Designing Neural Network and Hardware Architecture for Memristive Xbar based Computing Systems. - Shubham Negi; Indranil Chakraborty; Aayush Ankit; Kaushik Roy 001 (CoRR, 2021)

NAX: neural architecture and memristive xbar based accelerator co-design. - Shubham Negi; Indranil Chakraborty; Aayush Ankit; Kaushik Roy 001 (DAC, 2022)

HyperX: A Hybrid RRAM-SRAM partitioned system for error recovery in memristive Xbars. - Adarsh Kosta; Efstathia Soufleri; Indranil Chakraborty; Amogh Agrawal; Aayush Ankit; Kaushik Roy 001 (DATE, 2022)

Identifying Efficient Dataflows for Spiking Neural Networks. - Deepika Sharma; Aayush Ankit; Kaushik Roy 001 (ISLPED, 2022)

SAMBA: Sparsity Aware In-Memory Computing Based Machine Learning Accelerator. - Dong Eun Kim; Aayush Ankit; Cheng Wang 036; Kaushik Roy 001 (IEEE Trans. Computers, 2023)

Exploring Neuromorphic Computing Based on Spiking Neural Networks: Algorithms to Hardware. - Nitin Rathi; Indranil Chakraborty; Adarsh Kosta; Abhronil Sengupta; Aayush Ankit; Priyadarshini Panda; Kaushik Roy 001 (ACM Comput. Surv., 2023)