Arghadip Das

According to our database, Arghadip Das authored at least 11 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

RamForm: A Ramanujan Wavelet Transform-Based Accelerator for Energy-Efficient Signal Processing.

Arya Pandit, Soham Das, Arghadip Das, Debaprasad De, Arnab Raha, Mrinal Kanti Naskar

Proceedings of the 39th International Conference on VLSI Design & 25th International Conference on Embedded Systems, 2026

2025

Towards Energy-Accuracy Scalable Multimodal Cognitive Systems.

Soumendu Kumar Ghosh, Arghadip Das, Arnab Raha, Vijay Raghunathan

IEEE Embed. Syst. Lett., June, 2025

XAMBA: Enabling Efficient State Space Models on Resource-Constrained Neural Processing Units.

Arghadip Das, Arnab Raha, Shamik Kundu, Soumendu Kumar Ghosh, Deepak Mathaikutty, Vijay Raghunathan

CoRR, February, 2025

Demo Abstract: A Low-Power Real-Time Hardware Accelerator for Edge Detection Using Stochastic Computing.

Priyajit Ghosh, Rajarshi Mukherjee, Auro Anand Saha, Sutirtha Naha, Arghadip Das, Arnab Raha, Mrinal Kanti Naskar

Proceedings of the IEEE/ACM International Symposium on Low Power Electronics and Design, 2025

Demo Abstract: ECO: Low Power Context-Aware Multimodal AI on NPUs.

Arghadip Das, Yatharth Agarwal, Soumendu Kumar Ghosh, Arnab Raha, Vijay Raghunathan

Proceedings of the IEEE/ACM International Symposium on Low Power Electronics and Design, 2025

GraNNite: Enabling High-Performance Execution of Graph Neural Networks on Resource-Constrained Neural Processing Units.

Arghadip Das, Shamik Kundu, Arnab Raha, Soumendu Kumar Ghosh, Deepak Mathaikutty, Vijay Raghunathan

Proceedings of the International Joint Conference on Neural Networks, 2025

LLM-NPU: Towards Efficient Foundation Model Inference on Low-Power Neural Processing Units.

Arnab Raha, Souvik Kundu, Sharath Nittur Sridhar, Shamik Kundu, Soumendu Kumar Ghosh, Alessandro Palla, Arghadip Das, Darren Crews, Deepak A. Mathaikutty

Proceedings of the IEEE International Conference on Omni-layer Intelligent Systems, 2025

PRISM: Toward Energy-Efficient AIoT with Processing-In-Sensor+Memory in Battery-Free Devices.

Arghadip Das, Yatharth Agarwal, Chunguang Wang, Arnab Raha, Sandeep Krishna Thirumala, Sumeet Kumar Gupta, Vijay Raghunathan

Proceedings of the IEEE International Conference on Omni-layer Intelligent Systems, 2025

2024

Toward Energy-Efficient Collaborative Inference Using Multisystem Approximations.

Arghadip Das, Soumendu Kumar Ghosh, Arnab Raha, Vijay Raghunathan

IEEE Internet Things J., May, 2024

2023

HIPED_AP: Energy-Efficient Hardware Accelerators for Hidden Periodicity Detection.

Arghadip Das, Chandrachur Majumder, Debaprasad De, Arnab Raha, Mrinal Kanti Naskar

IEEE Trans. Computers, October, 2023

2021

HIPER: Low Power, High Performance and Area-Efficient Hardware Accelerators for Hidden Periodicity Detection using Ramanujan Filter Banks.

Arghadip Das, Chandrachur Majumder, Debaprasad De, Arnab Raha, Mrinal Kanti Naskar

Proceedings of the 34th International Conference on VLSI Design and 20th International Conference on Embedded Systems, 2021