Ramachandran Muralidhar

12 papers B 1C 1Journal 3Unranked 7

Year	Rank	Type	Title / Venue / Authors
2023	J	`jnl`	A Heterogeneous and Programmable Compute-In-Memory Accelerator Architecture for Analog-AI Using Dense 2-D Mesh. IEEE Trans. Very Large Scale Integr. Syst. Shubham Jain, Hsinyu Tsai, Ching-Tzu Chen, Ramachandran Muralidhar, Irem Boybat, Martin M. Frank, Stanislaw Wozniak, Milos Stanisavljevic, Praneet Adusumilli, Pritish Narayanan, Kohji Hosokawa, Masatoshi Ishii, Arvind Kumar, Vijay Narayanan, Geoffrey W. Burr
2023	—	`conf`	AnalogNAS: A Neural Network Design Framework for Accurate Inference with Analog In-Memory Computing. EDGE Hadjer Benmeziane, Corey Lammie, Irem Boybat, Malte J. Rasch, Manuel Le Gallo, Hsinyu Tsai, Ramachandran Muralidhar, Smaïl Niar, Hamza Ouarnoughi, Vijay Narayanan, Abu Sebastian, Kaoutar El Maghraoui
2023	J	`jnl`	AnalogNAS: A Neural Network Design Framework for Accurate Inference with Analog In-Memory Computing. CoRR Hadjer Benmeziane, Corey Lammie, Irem Boybat, Malte J. Rasch, Manuel Le Gallo, Hsinyu Tsai, Ramachandran Muralidhar, Smaïl Niar, Hamza Ouarnoughi, Vijay Narayanan, Abu Sebastian, Kaoutar El Maghraoui
2023	C	`conf`	Architectures and Circuits for Analog-memory-based Hardware Accelerators for Deep Neural Networks (Invited). ISCAS Hsinyu Tsai, Pritish Narayanan, Shubham Jain, Stefano Ambrogio, Kohji Hosokawa, Masatoshi Ishii, Charles Mackin, Ching-Tzu Chen, Atsuya Okazaki, Akiyo Nomura, Irem Boybat, Ramachandran Muralidhar, Martin M. Frank, Takeo Yasuda, Alexander M. Friz, Yasuteru Kohda, An Chen, Andrea Fasoli, Malte J. Rasch, Stanislaw Wozniak, Jose Luquin, Vijay Narayanan, Geoffrey W. Burr
2023	—	`conf`	Impact of Phase-Change Memory Drift on Energy Efficiency and Accuracy of Analog Compute-in-Memory Deep Learning Inference (Invited). IRPS Martin M. Frank, Ning Li, Malte J. Rasch, Shubham Jain, Ching-Tzu Chen, Ramachandran Muralidhar, Jin-Ping Han, Vijay Narayanan, Timothy Philip, Kevin Brew, Andrew Simon, Iqbal Saraf, Nicole Saulnier, Irem Boybat, Stanislaw Wozniak, Abu Sebastian, Pritish Narayanan, Charles Mackin, An Chen, Hsinyu Tsai, Geoffrey W. Burr
2022	B	`conf`	Source Localization and Bayesian leak magnitude inference of sparse wireless sensor data to detect fugitive methane leak. IEEE Big Data Siddesh Nageswaran, Ramachandran Muralidhar, Theodore G. van Kessel, Levente J. Klein
2020	—	`conf`	Satellite Guided Mobile Wireless Methane Detection for Oil and Gas Operations. WF-IoT Theodore G. van Kessel, Levente J. Klein, Ramachandran Muralidhar, Eric J. Zhang, Hendrik F. Hamann
2019	J	`jnl`	Field Deployment of a Portable Optical Spectrometer for Methane Fugitive Emissions Monitoring on Oil and Gas Well Pads. Sensors Eric J. Zhang, Chu C. Teng, Theodore G. van Kessel, Levente J. Klein, Ramachandran Muralidhar, Gerard Wysocki, William M. J. Green
2018	—	`conf`	Methane Leak Detection and Localization Using Wireless Sensor Networks for Remote Oil and Gas Operations. IEEE SENSORS Theodore G. van Kessel, Ramachandran Muralidhar, Levente J. Klein, Dhruv Nair, Nigel Hinds, Hendrik F. Hamann, Norma E. Sosa
2017	—	`conf`	A low maintenance particle pollution sensing system using the Minimum Airflow Particle Counter (MAPC). IEEE BigData Theodore G. van Kessel, Ramachandran Muralidhar, Josephine B. Chang, Jun-Song Wang, Michael A. Schappert, Hendrik F. Hamann
2017	—	`conf`	Distributed wireless sensing for fugitive methane leak detection. IEEE BigData Levente J. Klein, Theodore G. van Kessel, Dhruv Nair, Ramachandran Muralidhar, Nigel Hinds, Hendrik F. Hamann, Norma E. Sosa
2015	—	`conf`	A method for rapid screening of various low-k TDDB models. IRPS Fen Chen, Carole Graas, Michael A. Shinosky, Chad Burke, Kai D. Feng, Craig Bocash, Ramachandran Muralidhar