Srinivasu Bodapati

Orcid: 0000-0003-0974-8245

Affiliations:
  • Indian Institute of Technology Mandi (IIT Mandi), India
  • Nanyang Technological University, Singapore (2017-2019)
  • IIT Madras, Department of Electrical Engineering, India (PhD 2017)


According to our database1, Srinivasu Bodapati authored at least 19 papers between 2016 and 2026.

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Bibliography

2026
A Reconfigurable Multiplier Architecture for Error-Resilient Applications in RISC-V Core.
CoRR, May, 2026

Energy Efficient Exact and Approximate Systolic Array Architecture for Matrix Multiplication.
Proceedings of the 39th International Conference on VLSI Design & 25th International Conference on Embedded Systems, 2026

2025
High-Performance Gemmini-Based Matrix Multiplication Accelerator for Deep Learning Workloads.
IEEE Trans. Very Large Scale Integr. Syst., December, 2025

Low Complexity Three's Complement Parallel Multiplier Using Special Operators of Ternary Logic.
IEEE Trans. Circuits Syst. II Express Briefs, November, 2025

Approximate Signed Multiplier with Sign-Focused Compressor for Edge Detection Applications.
CoRR, October, 2025

Low Power Approximate Multiplier Architecture for Deep Neural Networks.
CoRR, September, 2025

Advancing Neural Network Performance with Probabilistic Computing for ReLU Function.
Proceedings of the 38th International Conference on VLSI Design and 2024 23rd International Conference on Embedded Systems, 2025

MAGIC-Based High-Speed Adders for in-Memory Computing Using Memristors.
Proceedings of the 38th International Conference on VLSI Design and 2024 23rd International Conference on Embedded Systems, 2025

Optimizing Multipliers: An Energy-Efficient Design Using a Novel 3: 2 Compressor.
Proceedings of the 38th International Conference on VLSI Design and 2024 23rd International Conference on Embedded Systems, 2025

2024
Energy Efficient Memristor-Based Subtractors and Comparator for In-Memory Computing in MAGIC.
IEEE Trans. Circuits Syst. II Express Briefs, June, 2024

Approximate Ternary Matrix Multiplication for Image Processing and Neural Networks.
Proceedings of the IEEE Computer Society Annual Symposium on VLSI, 2024

Energy Efficient Accurate and Approximate Modified Adders for Ternary Multipliers.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2024

High-Speed Serial and Semi-Parallel IMPLY-based Approximate Adders through Memristors for In-Memory Computing.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2024

2023
Memristor-based High Speed and Area Efficient Comparators in IMPLY Logic.
Proceedings of the 36th International Conference on VLSI Design and 2023 22nd International Conference on Embedded Systems, 2023

2022
High Performance Ternary Full Adder in CNFET-Memristor Logic Technology.
Proceedings of the VLSI Design and Test - 26th International Symposium, 2022

2018
CoLPUF : A Novel Configurable LFSR-based PUF.
Proceedings of the 2018 IEEE Asia Pacific Conference on Circuits and Systems, 2018

2017
A Synthesis Methodology for Ternary Logic Circuits in Emerging Device Technologies.
IEEE Trans. Circuits Syst. I Regul. Pap., 2017

Carbon nanotube FET-based low-delay and low-power multi-digit adder designs.
IET Circuits Devices Syst., 2017

2016
Low-Complexity Multiternary Digit Multiplier Design in CNTFET Technology.
IEEE Trans. Circuits Syst. II Express Briefs, 2016


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