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2020 – today
- 2023
[j17]Nitin Rathi
, Indranil Chakraborty, Adarsh Kosta, Abhronil Sengupta, Aayush Ankit, Priyadarshini Panda, Kaushik Roy:
Exploring Neuromorphic Computing Based on Spiking Neural Networks: Algorithms to Hardware. ACM Comput. Surv. 55(12): 243:1-243:49 (2023)- [j16]Dong Eun Kim, Aayush Ankit, Cheng Wang, Kaushik Roy:
SAMBA: Sparsity Aware In-Memory Computing Based Machine Learning Accelerator. IEEE Trans. Computers 72(9): 2615-2627 (2023) - 2022
- [c15]Shubham Negi, Indranil Chakraborty, Aayush Ankit, Kaushik Roy:
NAX: neural architecture and memristive xbar based accelerator co-design. DAC 2022: 451-456 - [c14]Adarsh Kosta, Efstathia Soufleri, Indranil Chakraborty, Amogh Agrawal, Aayush Ankit, Kaushik Roy:
HyperX: A Hybrid RRAM-SRAM partitioned system for error recovery in memristive Xbars. DATE 2022: 88-91 - [c13]Deepika Sharma, Aayush Ankit, Kaushik Roy:
Identifying Efficient Dataflows for Spiking Neural Networks. ISLPED 2022: 2:1-2:6 - 2021
- [j15]Gobinda Saha, Isha Garg, Aayush Ankit, Kaushik Roy:
SPACE: Structured Compression and Sharing of Representational Space for Continual Learning. IEEE Access 9: 150480-150494 (2021) - [c12]Indranil Chakraborty, Sourjya Roy, Shrihari Sridharan, Mustafa Fayez Ali, Aayush Ankit, Shubham Jain, Anand Raghunathan:
Design Tools for Resistive Crossbar based Machine Learning Accelerators. AICAS 2021: 1-4 - [c11]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, Paolo Faraboschi, John Paul Strachan, Deming Chen, Kaushik Roy, Wen-Mei W. Hwu, Dejan S. Milojicic:
Mixed Precision Quantization for ReRAM-based DNN Inference Accelerators. ASP-DAC 2021: 372-377 - [i14]Shubham Negi, Indranil Chakraborty, Aayush Ankit, Kaushik Roy:
NAX: Co-Designing Neural Network and Hardware Architecture for Memristive Xbar based Computing Systems. CoRR abs/2106.12125 (2021) - 2020
- [j14]Syed Shakib Sarwar, Aayush Ankit, Kaushik Roy:
Incremental Learning in Deep Convolutional Neural Networks Using Partial Network Sharing. IEEE Access 8: 4615-4628 (2020) - [j13]Aayush Ankit, Indranil Chakraborty, Amogh Agrawal, Mustafa Fayez Ali, Kaushik Roy:
Circuits and Architectures for In-Memory Computing-Based Machine Learning Accelerators. IEEE Micro 40(6): 8-22 (2020) - [j12]Indranil Chakraborty, Deboleena Roy, Isha Garg, Aayush Ankit, Kaushik Roy:
Constructing energy-efficient mixed-precision neural networks through principal component analysis for edge intelligence. Nat. Mach. Intell. 2(1): 43-55 (2020) - [j11]Indranil Chakraborty, Mustafa Fayez Ali, Aayush Ankit, Shubham Jain, Sourjya Roy, Shrihari Sridharan, Amogh Agrawal, Anand Raghunathan, Kaushik Roy:
Resistive Crossbars as Approximate Hardware Building Blocks for Machine Learning: Opportunities and Challenges. Proc. IEEE 108(12): 2276-2310 (2020) - [j10]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:
PANTHER: A Programmable Architecture for Neural Network Training Harnessing Energy-Efficient ReRAM. IEEE Trans. Computers 69(8): 1128-1142 (2020) - [j9]Aayush Ankit, Timur Ibrayev, Abhronil Sengupta, Kaushik Roy:
TraNNsformer: Clustered Pruning on Crossbar-Based Architectures for Energy-Efficient Neural Networks. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 39(10): 2361-2374 (2020) - [c10]Kaushik Roy, Indranil Chakraborty, Mustafa Fayez Ali, Aayush Ankit, Amogh Agrawal:
In-Memory Computing in Emerging Memory Technologies for Machine Learning: An Overview. DAC 2020: 1-6 - [c9]Indranil Chakraborty, Mustafa Fayez Ali, Dong Eun Kim, Aayush Ankit, Kaushik Roy:
GENIEx: A Generalized Approach to Emulating Non-Ideality in Memristive Xbars using Neural Networks. DAC 2020: 1-6 - [c8]Sourav Sanyal, Aayush Ankit, Craig M. Vineyard, Kaushik Roy:
Energy-Efficient Target Recognition using ReRAM Crossbars for Enabling On-Device Intelligence. SiPS 2020: 1-6 - [i13]Gobinda Saha, Isha Garg, Aayush Ankit, Kaushik Roy:
Structured Compression and Sharing of Representational Space for Continual Learning. CoRR abs/2001.08650 (2020) - [i12]Indranil Chakraborty, Mustafa Fayez Ali, Dong Eun Kim, Aayush Ankit, Kaushik Roy:
GENIEx: A Generalized Approach to Emulating Non-Ideality in Memristive Xbars using Neural Networks. CoRR abs/2003.06902 (2020)
2010 – 2019
- 2019
- [j8]Shubham Jain, Aayush Ankit, Indranil Chakraborty, Tayfun Gokmen, Malte J. Rasch, Wilfried Haensch, Kaushik Roy, Anand Raghunathan:
Neural network accelerator design with resistive crossbars: Opportunities and challenges. IBM J. Res. Dev. 63(6): 10:1-10:13 (2019) - [j7]Amogh Agrawal, Aayush Ankit, Kaushik Roy:
SPARE: Spiking Neural Network Acceleration Using ROM-Embedded RAMs as In-Memory-Computation Primitives. IEEE Trans. Computers 68(8): 1190-1200 (2019) - [j6]Amogh Agrawal, Akhilesh Jaiswal, Deboleena Roy, Bing Han, Gopalakrishnan Srinivasan, Aayush Ankit, Kaushik Roy:
Xcel-RAM: Accelerating Binary Neural Networks in High-Throughput SRAM Compute Arrays. IEEE Trans. Circuits Syst. I Regul. Pap. 66-I(8): 3064-3076 (2019) - [j5]Aayush Ankit, Minsuk Koo, Shreyas Sen, Kaushik Roy:
Powerline Communication for Enhanced Connectivity in Neuromorphic Systems. IEEE Trans. Very Large Scale Integr. Syst. 27(8): 1897-1906 (2019) - [c7]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, Dejan S. Milojicic:
PUMA: A Programmable Ultra-efficient Memristor-based Accelerator for Machine Learning Inference. ASPLOS 2019: 715-731 - [c6]Maryam Parsa, Aayush Ankit, Amirkoushyar Ziabari, Kaushik Roy:
PABO: Pseudo Agent-Based Multi-Objective Bayesian Hyperparameter Optimization for Efficient Neural Accelerator Design. ICCAD 2019: 1-8 - [i11]Aayush Ankit, Izzat El Hajj, Sai Rahul Chalamalasetti, Geoffrey Ndu, Martin Foltin, R. Stanley Williams, Paolo Faraboschi, Wen-Mei Hwu, John Paul Strachan, Kaushik Roy, Dejan S. Milojicic:
PUMA: A Programmable Ultra-efficient Memristor-based Accelerator for Machine Learning Inference. CoRR abs/1901.10351 (2019) - [i10]Indranil Chakraborty, Deboleena Roy, Aayush Ankit, Kaushik Roy:
Efficient Hybrid Network Architectures for Extremely Quantized Neural Networks Enabling Intelligence at the Edge. CoRR abs/1902.00460 (2019) - [i9]Indranil Chakraborty, Deboleena Roy, Isha Garg, Aayush Ankit, Kaushik Roy:
PCA-driven Hybrid network design for enabling Intelligence at the Edge. CoRR abs/1906.01493 (2019) - [i8]Maryam Parsa, Aayush Ankit, Amirkoushyar Ziabari, Kaushik Roy:
PABO: Pseudo Agent-Based Multi-Objective Bayesian Hyperparameter Optimization for Efficient Neural Accelerator Design. CoRR abs/1906.08167 (2019) - [i7]Aayush Ankit, Izzat El Hajj, Sai Rahul Chalamalasetti, Sapan Agarwal, Matthew J. Marinella, Martin Foltin, John Paul Strachan, Dejan S. Milojicic, Wen-Mei W. Hwu, Kaushik Roy:
PANTHER: A Programmable Architecture for Neural Network Training Harnessing Energy-efficient ReRAM. CoRR abs/1912.11516 (2019) - 2018
- [j4]Syed Shakib Sarwar, Swagath Venkataramani, Aayush Ankit, Anand Raghunathan, Kaushik Roy:
Energy-Efficient Neural Computing with Approximate Multipliers. ACM J. Emerg. Technol. Comput. Syst. 14(2): 16:1-16:23 (2018) - [j3]Parami Wijesinghe, Aayush Ankit, Abhronil Sengupta, Kaushik Roy:
An All-Memristor Deep Spiking Neural Computing System: A Step Toward Realizing the Low-Power Stochastic Brain. IEEE Trans. Emerg. Top. Comput. Intell. 2(5): 345-358 (2018) - [j2]Bing Han, Aayush Ankit, Abhronil Sengupta, Kaushik Roy:
Cross-Layer Design Exploration for Energy-Quality Tradeoffs in Spiking and Non-Spiking Deep Artificial Neural Networks. IEEE Trans. Multi Scale Comput. Syst. 4(4): 613-623 (2018) - [c5]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, Sunil Vishwanathpur Lakshminarasimha, Dejan S. Milojicic, Mohan Parthasarathy, Filipe Ribeiro, Lucas Rosa, Kaushik Roy, Plínio Silveira, John Paul Strachan:
Hardware-Software Co-Design for an Analog-Digital Accelerator for Machine Learning. ICRC 2018: 1-13 - [c4]Aayush Ankit, Abhronil Sengupta, Kaushik Roy:
Neuromorphic Computing Across the Stack: Devices, Circuits and Architectures. SiPS 2018: 1-6 - 2017
- [j1]Priyadarshini Panda, Aayush Ankit, Parami Wijesinghe, Kaushik Roy:
FALCON: Feature Driven Selective Classification for Energy-Efficient Image Recognition. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 36(12): 2017-2029 (2017) - [c3]Aayush Ankit, Abhronil Sengupta, Priyadarshini Panda, Kaushik Roy:
RESPARC: A Reconfigurable and Energy-Efficient Architecture with Memristive Crossbars for Deep Spiking Neural Networks. DAC 2017: 27:1-27:6 - [c2]Aayush Ankit, Abhronil Sengupta, Kaushik Roy:
TraNNsformer: Neural network transformation for memristive crossbar based neuromorphic system design. ICCAD 2017: 533-540 - [c1]Abhronil Sengupta, Aayush Ankit, Kaushik Roy:
Performance analysis and benchmarking of all-spin spiking neural networks (Special session paper). IJCNN 2017: 4557-4563 - [i6]Aayush Ankit, Abhronil Sengupta, Priyadarshini Panda, Kaushik Roy:
RESPARC: A Reconfigurable and Energy-Efficient Architecture with Memristive Crossbars for Deep Spiking Neural Networks. CoRR abs/1702.06064 (2017) - [i5]Aayush Ankit, Abhronil Sengupta, Kaushik Roy:
TraNNsformer: Neural Network Transformation for Memristive Crossbar based Neuromorphic System Design. CoRR abs/1708.07949 (2017) - [i4]Amogh Agrawal, Aayush Ankit, Kaushik Roy:
SPARE: Spiking Networks Acceleration Using CMOS ROM-Embedded RAM as an In-Memory-Computation Primitive. CoRR abs/1711.07546 (2017) - [i3]Parami Wijesinghe, Aayush Ankit, Abhronil Sengupta, Kaushik Roy:
An All-Memristor Deep Spiking Neural Network: A Step Towards Realizing the Low Power, Stochastic Brain. CoRR abs/1712.01472 (2017) - [i2]Syed Shakib Sarwar, Aayush Ankit, Kaushik Roy:
Incremental Learning in Deep Convolutional Neural Networks Using Partial Network Sharing. CoRR abs/1712.02719 (2017) - 2016
- [i1]Priyadarshini Panda, Aayush Ankit, Parami Wijesinghe, Kaushik Roy:
FALCON: Feature Driven Selective Classification for Energy-Efficient Image Recognition. CoRR abs/1609.03396 (2016)
Coauthor Index
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