Maximilian Liehr

According to our database, Maximilian Liehr authored at least 14 papers between 2019 and 2024.

Collaborative distances:

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

2024

A 65-nm RRAM Compute-in-Memory Macro for Genome Processing.

Fan Zhang, Amitesh Sridharan, Wangxin He, Injune Yeo, Maximilian Liehr, Wei Zhang, Nathaniel C. Cady, Yu Cao, Jae-Sun Seo, Deliang Fan

IEEE J. Solid State Circuits, July, 2024

In-Memory Computation Using CMOS-Integrated Resistive RAM for Robotic Navigation.

Jeelka Solanki, Jacob Pelton, Rocco Febbo, Maximilian Liehr, Andrew DeCandia, Karsten Beckmann, Garrett S. Rose, Nathaniel C. Cady

Proceedings of the International Conference on Neuromorphic Systems, 2024

2023

An Efficient and Accurate Memristive Memory for Array-Based Spiking Neural Networks.

Hritom Das, Rocco D. Febbo, Sree Nirmillo Biswash Tushar, Nishith N. Chakraborty, Maximilian Liehr, Nathaniel C. Cady, Garrett S. Rose

IEEE Trans. Circuits Syst. I Regul. Pap., December, 2023

Deep Mapper: A Multi-Channel Single-Cycle Near-Sensor DNN Accelerator.

Mehrdad Morsali, Sepehr Tabrizchi, Maximilian Liehr, Nathaniel C. Cady, Mohsen Imani, Arman Roohi, Shaahin Angizi

Proceedings of the IEEE International Conference on Rebooting Computing, 2023

RFAM: RESET-Failure-Aware-Model for HfO2-based Memristor to Enhance the Reliability of Neuromorphic Design.

Hritom Das, Manu Rathore, Rocco Febbo, Maximilian Liehr, Nathaniel C. Cady, Garrett S. Rose

Proceedings of the Great Lakes Symposium on VLSI 2023, 2023

A 65nm RRAM Compute-in-Memory Macro for Genome Sequencing Alignment.

Fan Zhang, Wangxin He, Injune Yeo, Maximilian Liehr, Nathaniel C. Cady, Yu Cao, Jae-Sun Seo, Deliang Fan

Proceedings of the 49th IEEE European Solid State Circuits Conference, 2023

2022

Hybrid RRAM/SRAM in-Memory Computing for Robust DNN Acceleration.

Gokul Krishnan, Zhenyu Wang, Injune Yeo, Li Yang, Jian Meng, Maximilian Liehr, Rajiv V. Joshi, Nathaniel C. Cady, Deliang Fan, Jae-Sun Seo, Yu Cao

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2022

Exploring Model Stability of Deep Neural Networks for Reliable RRAM-Based In-Memory Acceleration.

Gokul Krishnan, Li Yang, Jingbo Sun, Jubin Hazra, Xiaocong Du, Maximilian Liehr, Zheng Li, Karsten Beckmann, Rajiv V. Joshi, Nathaniel C. Cady, Deliang Fan, Yu Cao

IEEE Trans. Computers, 2022

A Compact Model for the Variable Switching Dynamics of HfO2 Memristors.

Manu Rathore, Ryan Weiss, Mst Shamim Ara Shawkat, Garrett S. Rose, Maximilian Liehr, Minhaz Abedin, Sarah Rafiq, Nathaniel C. Cady

Proceedings of the 65th IEEE International Midwest Symposium on Circuits and Systems, 2022

2021

Investigation of ReRAM Variability on Flow-Based Edge Detection Computing Using HfO₂-Based ReRAM Arrays.

Sarah Rafiq, Jubin Hazra, Maximilian Liehr, Karsten Beckmann, Minhaz Abedin, Jodh S. Pannu, Sumit Kumar Jha, Nathaniel C. Cady

IEEE Trans. Circuits Syst. I Regul. Pap., 2021

In-memory Computation of Error-Correcting Codes Using a Reconfigurable HfOx ReRAM 1T1R Array.

Minhaz Abedin, Maximilian Liehr, Karsten Beckmann, Jubin Hazra, Sarah Rafiq, Nathaniel C. Cady

Proceedings of the 64th IEEE International Midwest Symposium on Circuits and Systems, 2021

Robust RRAM-based In-Memory Computing in Light of Model Stability.

Gokul Krishnan, Jingbo Sun, Jubin Hazra, Xiaocong Du, Maximilian Liehr, Zheng Li, Karsten Beckmann, Rajiv V. Joshi, Nathaniel C. Cady, Yu Cao

Proceedings of the IEEE International Reliability Physics Symposium, 2021

Optimization of Switching Metrics for CMOS Integrated HfO2 based RRAM Devices on 300 mm Wafer Platform.

Jubin Hazra, Maximilian Liehr, Karsten Beckmann, Minhaz Abedin, Sarah Rafiq, Nathaniel C. Cady

Proceedings of the IEEE International Memory Workshop, 2021

2019

Fabrication and Performance of Hybrid ReRAM-CMOS Circuit Elements for Dynamic Neural Networks.

Maximilian Liehr, Jubin Hazra, Karsten Beckmann, Wilkie Olin-Ammentorp, Nathaniel C. Cady, Ryan Weiss, Sagarvarma Sayyaparaju, Garrett S. Rose, Joseph Van Nostrand

Proceedings of the International Conference on Neuromorphic Systems, 2019