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ORCIDArnab Raha
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- affiliation: Intel Corporation, Santa Clara, CA, USA
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2020 – today
- 2024
[j30]Arghadip Das
, Soumendu Kumar Ghosh, Arnab Raha, Vijay Raghunathan:
Toward Energy-Efficient Collaborative Inference Using Multisystem Approximations. IEEE Internet Things J. 11(10): 17989-18004 (2024)- [j29]Shamik Kundu, Suvadeep Banerjee, Arnab Raha, Suriyaprakash Natarajan, Kanad Basu:
DiagNNose: Toward Error Localization in Deep Learning Hardware-Based on VTA-TVM Stack. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 43(1): 217-229 (2024) - [j28]Soumendu Kumar Ghosh, Arnab Raha, Vijay Raghunathan, Anand Raghunathan:
PArtNNer: Platform-Agnostic Adaptive Edge-Cloud DNN Partitioning for Minimizing End-to-End Latency. ACM Trans. Embed. Comput. Syst. 23(1): 6:1-6:38 (2024) - [j27]Shamik Kundu, Sanjay Das, Sayar Karmakar, Arnab Raha, Souvik Kundu, Yiorgos Makris, Kanad Basu:
Bit-by-Bit: Investigating the Vulnerabilities of Binary Neural Networks to Adversarial Bit Flipping. Trans. Mach. Learn. Res. 2024 (2024) - [c43]Sanjay Das, Shamik Kundu, Pooja Madhusoodhanan, Viswanathan Pillai Prasanth, Rubin A. Parekhji, Arnab Raha, Suvadeep Banerjee, Suriya Natarajan, Kanad Basu:
Graph Learning-based Fault Criticality Analysis for Enhancing Functional Safety of E/E Systems. DAC 2024: 206:1-206:6 - [c42]Shamik Kundu, Navnil Choudhury, Sanjay Das, Arnab Raha, Kanad Basu:
QNAD: Quantum Noise Injection for Adversarial Defense in Deep Neural Networks. HOST 2024: 1-11 - [c41]Shamik Kundu, Soumendu Kumar Ghosh, Arnab Raha, Deepak A. Mathaikutty:
SwiSS: Switchable Single-Sided Sparsity-based DNN Accelerators. ISLPED 2024: 1-6 - [c40]Shamik Kundu, Arnab Raha, Deepak A. Mathaikutty, Kanad Basu:
RASH: Reliable Deep Learning Acceleration using Sparsity-based Hardware. ISQED 2024: 1 - [c39]Soumendu Kumar Ghosh, Shamik Kundu, Arnab Raha, Deepak A. Mathaikutty, Vijay Raghunathan:
HARVEST: Towards Efficient Sparse DNN Accelerators using Programmable Thresholds. VLSID 2024: 228-234 - [i6]Arnab Raha, Deepak A. Mathaikutty, Soumendu Kumar Ghosh, Shamik Kundu:
FlexNN: A Dataflow-aware Flexible Deep Learning Accelerator for Energy-Efficient Edge Devices. CoRR abs/2403.09026 (2024) - [i5]Ayush Arunachalam, Ian Kintz, Suvadeep Banerjee, Arnab Raha, Xiankun Jin, Fei Su, Viswanathan Pillai Prasanth, Rubin A. Parekhji, Suriyaprakash Natarajan, Kanad Basu:
Enhancing Functional Safety in Automotive AMS Circuits through Unsupervised Machine Learning. CoRR abs/2404.01632 (2024) - 2023
- [j26]Shamik Kundu, Arnab Raha, Suvadeep Banerjee, Suriyaprakash Natarajan, Kanad Basu:
Analysis and Mitigation of DRAM Faults in Sparse-DNN Accelerators. IEEE Des. Test 40(2): 90-99 (2023) - [j25]Shamik Kundu, Suvadeep Banerjee, Arnab Raha, Fei Su, Suriyaprakash Natarajan, Kanad Basu:
Trouble-Shooting at GAN Point: Improving Functional Safety in Deep Learning Accelerators. IEEE Trans. Computers 72(8): 2194-2208 (2023) - [j24]Arghadip Das, Chandrachur Majumder, Debaprasad De, Arnab Raha, Mrinal Kanti Naskar:
HIPEDAP: Energy-Efficient Hardware Accelerators for Hidden Periodicity Detection. IEEE Trans. Computers 72(10): 2781-2794 (2023) - [j23]Ayush Arunachalam, Shamik Kundu, Arnab Raha, Suvadeep Banerjee, Suriyaprakash Natarajan, Kanad Basu:
A Novel Low-Power Compression Scheme for Systolic Array-Based Deep Learning Accelerators. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 42(4): 1085-1098 (2023) - [j22]Soumendu Kumar Ghosh, Arnab Raha, Vijay Raghunathan:
Energy-Efficient Approximate Edge Inference Systems. ACM Trans. Embed. Comput. Syst. 22(4): 77:1-77:50 (2023) - [c38]Ayush Arunachalam, Sanjay Das, Monikka Rajan, Fei Su, Xiankun Jin, Suvadeep Banerjee, Arnab Raha, Suriyaprakash Natarajan, Kanad Basu:
Enhanced ML-Based Approach for Functional Safety Improvement in Automotive AMS Circuits. ITC 2023: 266-275 - [i4]Charles Qi, Yi Wang, Hui Wang, Yang Lu, Shiva Shankar Subramanian, Finola Cahill, Conall Tuohy, Victor Li, Xu Qian, Darren Crews, Ling Wang, Shivaji Roy, Andrea Deidda, Martin Power, Niall Hanrahan, Rick Richmond, Umer Cheema, Arnab Raha, Alessandro Palla, Gary Baugh, Deepak Mathaikutty:
VPU-EM: An Event-based Modeling Framework to Evaluate NPU Performance and Power Efficiency at Scale. CoRR abs/2303.10271 (2023) - 2022
- [j21]Sandeep Krishna Thirumala, Arnab Raha, Sumeet Gupta, Vijay Raghunathan:
Exploring the Design of Energy-Efficient Intermittently Powered Systems Using Reconfigurable Ferroelectric Transistors. IEEE Trans. Very Large Scale Integr. Syst. 30(4): 365-378 (2022) - [j20]Bitan Banerjee, Sibendu Paul, Omar Alfandi, Arnab Raha, Amitava Mukherjee:
ENROUTE: An Entropy Aware Routing Scheme for Information-Centric Networks (ICN). Wirel. Pers. Commun. 122(2): 1171-1195 (2022) - [c37]Ayush Arunachalam, Shamik Kundu, Arnab Raha, Suvadeep Banerjee, Kanad Basu:
Fault Resilience of DNN Accelerators for Compressed Sensor Inputs. ISVLSI 2022: 329-332 - [c36]Ayush Arunachalam, Athulya Kizhakkayil, Shamik Kundu, Arnab Raha, Suvadeep Banerjee, Robert Jin, Fei Su, Kanad Basu:
Unsupervised Learning-based Early Anomaly Detection in AMS Circuits of Automotive SoCs. ITC 2022: 229-238 - [c35]Shamik Kundu, Akul Malhotra, Arnab Raha, Sumeet Kumar Gupta, Kanad Basu:
RIBoNN: Designing Robust In-Memory Binary Neural Network Accelerators. ITC 2022: 504-508 - [c34]Bodepu Sai Tirumala Naidu, Shreya Biswas, Rounak Chatterjee, Sayak Mandal, Srijan Pratihar, Ayan Chatterjee, Arnab Raha, Amitava Mukherjee, Janet Paluh:
SCENIC: An Area and Energy-Efficient CNN-based Hardware Accelerator for Discernable Classification of Brain Pathologies using MRI. VLSID 2022: 168-173 - [c33]Steven Hsu, Amit Agarwal, Mark A. Anders, Arnab Raha, Raymond Sung, Deepak Mathaikutty, Ram Krishnamurthy, James W. Tschanz, Vivek De:
2.4GHz, Double-Buffered, 4kb Standard-Cell-Based Register File with Low-Power Mixed-Frequency Clocking for Machine Learning Accelerators. VLSI Technology and Circuits 2022: 22-23 - [c32]Shamik Kundu, Suvadeep Banerjee, Arnab Raha, Kanad Basu:
Special Session: Effective In-field Testing of Deep Neural Network Hardware Accelerators. VTS 2022: 1-4 - 2021
- [j19]Shamik Kundu, Suvadeep Banerjee, Arnab Raha, Suriyaprakash Natarajan, Kanad Basu:
Toward Functional Safety of Systolic Array-Based Deep Learning Hardware Accelerators. IEEE Trans. Very Large Scale Integr. Syst. 29(3): 485-498 (2021) - [j18]Archisman Ghosh, Biswadeep Chakraborty, Arnab Raha, Amitava Mukherjee:
Improving Network Throughput by Hardware Realization of a Dynamic Content Caching Scheme for Information-Centric Networking (ICN). Wirel. Pers. Commun. 116(4): 2873-2898 (2021) - [c31]Arnab Raha, Soumendu Kumar Ghosh, Debabrata Mohapatra, Deepak A. Mathaikutty, Raymond Sung, Cormac Brick, Vijay Raghunathan:
Special Session: Approximate TinyML Systems: Full System Approximations for Extreme Energy-Efficiency in Intelligent Edge Devices. ICCD 2021: 13-16 - [c30]Ayush Arunachalam, Shamik Kundu, Arnab Raha, Suvadeep Banerjee, Suriyaprakash Natarajan, Kanad Basu:
HardCompress: A Novel Hardware-based Low-power Compression Scheme for DNN Accelerators. ISQED 2021: 457-462 - [c29]Arghadip Das, Chandrachur Majumder, Debaprasad De, Arnab Raha, Mrinal Kanti Naskar:
HIPER: Low Power, High Performance and Area-Efficient Hardware Accelerators for Hidden Periodicity Detection using Ramanujan Filter Banks. VLSID 2021: 111-116 - [c28]Rounak Chatterjee, Souradeep Chowdhury, Soham Mondal, Arnab Raha, Janet Paluh, Amitava Mukherjee:
PreSyNC: Hardware realization of the Presynaptic Region of a Biologically Extensive Neuronal Circuitry. VLSID 2021: 228-233 - [c27]Arnab Raha, Sang Kyun Kim, Deepak Mathaikutty, Guruguhanathan Venkataramanan, Debabrata Mohapatra, Raymond Sung, Cormac Brick, Gautham N. Chinya:
Design Considerations for Edge Neural Network Accelerators: An Industry Perspective. VLSID 2021: 328-333 - 2020
- [j17]Avrajit Ghosh, Arnab Raha, Amitava Mukherjee:
Energy-Efficient IoT-Health Monitoring System using Approximate Computing. Internet Things 9: 100166 (2020) - [j16]Arnab Raha, Ankush Chakrabarty, Vijay Raghunathan, Gregery T. Buzzard:
Embedding Approximate Nonlinear Model Predictive Control at Ultrahigh Speed and Extremely Low Power. IEEE Trans. Control. Syst. Technol. 28(3): 1092-1099 (2020) - [j15]Ashish Ranjan, Arnab Raha, Vijay Raghunathan, Anand Raghunathan:
Approximate Memory Compression. IEEE Trans. Very Large Scale Integr. Syst. 28(4): 980-991 (2020) - [c26]Sandeep Krishna Thirumala, Arnab Raha, Vijay Raghunathan, Sumeet Kumar Gupta:
IPS-CiM: Enhancing Energy Efficiency of Intermittently-Powered Systems with Compute-in-Memory. ICCD 2020: 368-376 - [c25]Soumendu Kumar Ghosh, Arnab Raha, Vijay Raghunathan:
Approximate inference systems (AxIS): end-to-end approximations for energy-efficient inference at the edge. ISLPED 2020: 7-12 - [c24]Archisman Ghosh, K. Gaurav Kumar, Debaprasad De, Arnab Raha, Mrinal Kanti Naskar:
Energy-Efficient Edge Detection using Approximate Ramanujan Sums. ISQED 2020: 414-420
2010 – 2019
- 2019
- [c23]Sandeep Krishna Thirumala, T. Hung, Arnab Raha, Niharika Thakuria, K. Cho, Vijay Raghunathan, Zhihong Chen, S. Gupta:
WSe2 based Valley-Coupled-Spintronic Devices for Low Power Non-Volatile Memories. DRC 2019: 211-212 - [c22]Sandeep Krishna Thirumala, Arnab Raha, Vijaykrishnan Narayanan, Vijay Raghunathan, Sumeet Kumar Gupta:
Non-volatile Logic and Memory based on Reconfigurable Ferroelectric Transistors. NANOARCH 2019: 1-6 - [p2]Ashish Ranjan, Swagath Venkataramani, Shubham Jain, Younghoon Kim, Shankar Ganesh Ramasubramanian, Arnab Raha, Kaushik Roy, Anand Raghunathan:
Automatic Synthesis Techniques for Approximate Circuits. Approximate Circuits 2019: 123-140 - [p1]Arnab Raha, Vijay Raghunathan:
Approximate Systems: Synergistically Approximating Sensing, Computing, Memory, and Communication Subsystems for Energy Efficiency. Approximate Circuits 2019: 349-368 - [i3]Sandeep Krishna Thirumala, Yi-Tse Hung, Shubham Jain, Arnab Raha, Niharika Thakuria, Vijay Raghunathan, Anand Raghunathan, Zhihong Chen, Sumeet Kumar Gupta:
Valley-Coupled-Spintronic Non-Volatile Memories with Compute-In-Memory Support. CoRR abs/1912.07821 (2019) - 2018
- [j14]Soubhagya Sutar, Arnab Raha, Devadatta M. Kulkarni, Rajeev Shorey, Jeffrey D. Tew, Vijay Raghunathan:
D-PUF: An Intrinsically Reconfigurable DRAM PUF for Device Authentication and Random Number Generation. ACM Trans. Embed. Comput. Syst. 17(1): 17:1-17:31 (2018) - [j13]Soubhagya Sutar, Arnab Raha, Vijay Raghunathan:
Memory-Based Combination PUFs for Device Authentication in Embedded Systems. IEEE Trans. Multi Scale Comput. Syst. 4(4): 793-810 (2018) - [j12]Arnab Raha, Akhilesh Jaiswal, Syed Shakib Sarwar, Hrishikesh Jayakumar, Vijay Raghunathan, Kaushik Roy:
Designing Energy-Efficient Intermittently Powered Systems Using Spin-Hall-Effect-Based Nonvolatile SRAM. IEEE Trans. Very Large Scale Integr. Syst. 26(2): 294-307 (2018) - [j11]Arnab Raha, Vijay Raghunathan:
Approximating Beyond the Processor: Exploring Full-System Energy-Accuracy Tradeoffs in a Smart Camera System. IEEE Trans. Very Large Scale Integr. Syst. 26(12): 2884-2897 (2018) - [c21]Sandeep Krishna Thirumala, Arnab Raha, Hrishikesh Jayakumar, Kaisheng Ma, Narayanan Vijaykrishnan, Vijay Raghunathan, Sumeet Kumar Gupta:
Dual Mode Ferroelectric Transistor based Non-Volatile Flip-Flops for Intermittently-Powered Systems. ISLPED 2018: 31:1-31:6 - 2017
- [j10]Arnab Raha, Vijay Raghunathan:
Synergistic Approximation of Computation and Memory Subsystems for Error-Resilient Applications. IEEE Embed. Syst. Lett. 9(1): 21-24 (2017) - [j9]Arnab Raha, Soubhagya Sutar, Hrishikesh Jayakumar, Vijay Raghunathan:
Quality Configurable Approximate DRAM. IEEE Trans. Computers 66(7): 1172-1187 (2017) - [j8]Hrishikesh Jayakumar, Arnab Raha, Jacob R. Stevens, Vijay Raghunathan:
Energy-Aware Memory Mapping for Hybrid FRAM-SRAM MCUs in Intermittently-Powered IoT Devices. ACM Trans. Embed. Comput. Syst. 16(3): 65:1-65:23 (2017) - [j7]Arnab Raha, Vijay Raghunathan:
qLUT: Input-Aware Quantized Table Lookup for Energy-Efficient Approximate Accelerators. ACM Trans. Embed. Comput. Syst. 16(5s): 130:1-130:23 (2017) - [j6]Arnab Raha, Swagath Venkataramani, Vijay Raghunathan, Anand Raghunathan:
Energy-Efficient Reduce-and-Rank Using Input-Adaptive Approximations. IEEE Trans. Very Large Scale Integr. Syst. 25(2): 462-475 (2017) - [c20]Arnab Raha, Ankush Chakrabarty, Vijay Raghunathan, Gregery T. Buzzard:
Ultrafast embedded explicit model predictive control for nonlinear systems. ACC 2017: 4398-4403 - [c19]Arnab Raha, Vijay Raghunathan:
Towards Full-System Energy-Accuracy Tradeoffs: A Case Study of An Approximate Smart Camera System. DAC 2017: 74:1-74:6 - [c18]Ashish Ranjan, Arnab Raha, Vijay Raghunathan, Anand Raghunathan:
Approximate memory compression for energy-efficiency. ISLPED 2017: 1-6 - [i2]Soubhagya Sutar, Arnab Raha, Vijay Raghunathan:
Memory-based Combination PUFs for Device Authentication in Embedded Systems. CoRR abs/1712.01611 (2017) - 2016
- [j5]Hrishikesh Jayakumar, Arnab Raha, Vijay Raghunathan:
Sleep-Mode Voltage Scaling: Enabling SRAM Data Retention at Ultra-Low Power in Embedded Microcontrollers. ACM Trans. Embed. Comput. Syst. 16(1): 10:1-10:25 (2016) - [j4]Arnab Raha, Hrishikesh Jayakumar, Vijay Raghunathan:
Input-Based Dynamic Reconfiguration of Approximate Arithmetic Units for Video Encoding. IEEE Trans. Very Large Scale Integr. Syst. 24(3): 846-857 (2016) - [c17]Hrishikesh Jayakumar, Arnab Raha, Younghyun Kim, Soubhagya Sutar, Woo Suk Lee, Vijay Raghunathan:
Energy-efficient system design for IoT devices. ASP-DAC 2016: 298-301 - [c16]Soubhagya Sutar, Arnab Raha, Vijay Raghunathan:
D-PUF: an intrinsically reconfigurable DRAM PUF for device authentication in embedded systems. CASES 2016: 12:1-12:10 - [c15]Hrishikesh Jayakumar, Arnab Raha, Vijay Raghunathan:
Energy-Aware Memory Mapping for Hybrid FRAM-SRAM MCUs in IoT Edge Devices. VLSID 2016: 264-269 - 2015
- [j3]Hrishikesh Jayakumar, Arnab Raha, Woo Suk Lee, Vijay Raghunathan:
QuickRecall: A HW/SW Approach for Computing across Power Cycles in Transiently Powered Computers. ACM J. Emerg. Technol. Comput. Syst. 12(1): 8:1-8:19 (2015) - [c14]Arnab Raha, Hrishikesh Jayakumar, Soubhagya Sutar, Vijay Raghunathan:
Quality-aware data allocation in approximate DRAM? CASES 2015: 89-98 - [c13]Arnab Raha, Swagath Venkataramani, Vijay Raghunathan, Anand Raghunathan:
Quality configurable reduce-and-rank for energy efficient approximate computing. DATE 2015: 665-670 - [c12]Arnab Raha, Subrata Mitra, Vijay Raghunathan, Sanjay G. Rao:
VIDalizer: An energy efficient video streamer. WCNC 2015: 2233-2238 - 2014
- [j2]Shaik Sahil Babu, Arnab Raha, Omar Alfandi, Dieter Hogrefe, Mrinal Kanti Naskar:
Trust integrated node potential aware routing for WSNs. Int. J. Trust. Manag. Comput. Commun. 2(2): 103-124 (2014) - [c11]Hrishikesh Jayakumar, Arnab Raha, Vijay Raghunathan:
Hypnos: An ultra-low power sleep mode with SRAM data retention for embedded microcontrollers! CODES+ISSS 2014: 11:1-11:10 - [c10]Ashish Ranjan, Arnab Raha, Swagath Venkataramani, Kaushik Roy, Anand Raghunathan:
ASLAN: Synthesis of approximate sequential circuits. DATE 2014: 1-6 - [c9]Hrishikesh Jayakumar, Kangwoo Lee, Woo Suk Lee, Arnab Raha, Younghyun Kim, Vijay Raghunathan:
Powering the internet of things. ISLPED 2014: 375-380 - [c8]Arnab Raha, Hrishikesh Jayakumar, Vijay Raghunathan:
A Power Efficient Video Encoder Using Reconfigurable Approximate Arithmetic Units. VLSID 2014: 324-329 - [c7]Hrishikesh Jayakumar, Arnab Raha, Vijay Raghunathan:
QUICKRECALL: A Low Overhead HW/SW Approach for Enabling Computations across Power Cycles in Transiently Powered Computers. VLSID 2014: 330-335 - 2012
- [c6]Arpita Chakraborty, Arnab Raha, Shovan Maity, Mrinal Kanti Naskar, Anupam Karmakar:
A fuzzy based trustworthy route selection method using LSRP in wireless sensor networks (FTRSP). CCSEIT 2012: 413-419 - [c5]Shovan Maity, Arnab Raha, Souvik Kumar Mitra, Victor Seal, Mrinal Kanti Naskar, Amitava Mukherjee:
An efficient sleep protocol for lifetime enhancement in multi covered and multi connected WSNs. ICACCI 2012: 343-347 - [c4]Arnab Raha, Shovan Maity, Mrinal Kanti Naskar, Omar Alfandi, Dieter Hogrefe:
An optimal sensor deployment scheme to ensure multi level coverage and connectivity in wireless sensor networks. IWCMC 2012: 299-304 - [c3]Arnab Raha, Mrinal Kanti Naskar, Arpita Chakraborty, Omar Alfandi, Dieter Hogrefe:
A Novel Indirect Trust Based Link State Routing Scheme Using a Robust Route Trust Method for Wireless Sensor Networks. NTMS 2012: 1-5 - [c2]Shaik Sahil Babu, Arnab Raha, Mrinal Kanti Naskar, Omar Alfandi, Dieter Hogrefe:
Fuzzy Logic Election of Node for Routing in WSNs. TrustCom 2012: 1279-1284 - [i1]Victor Seal, Arnab Raha, Shovan Maity, Souvik Kumar Mitra, Amitava Mukherjee, Mrinal Kanti Naskar:
A Simple Flood Forecasting Scheme Using Wireless Sensor Networks. CoRR abs/1203.2511 (2012) - 2011
- [j1]Shaik Sahil Babu, Arnab Raha, Mrinal K. Naskar:
A Direct Trust dependent Link State Routing Protocol Using Route Trusts for WSNs (DTLSRP). Wirel. Sens. Netw. 3(4): 125-134 (2011) - [c1]Arnab Raha, Shaik Sahil Babu, Mrinal Kanti Naskar, Omar Alfandi, Dieter Hogrefe:
Trust integrated link state routing protocol for Wireless Sensor Networks (TILSRP). IEEE ANTS 2011: 1-6
Coauthor Index
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