Wei-Chen Wei

According to our database1, Wei-Chen Wei authored at least 11 papers between 2018 and 2020.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2020
Embedded 1-Mb ReRAM-Based Computing-in- Memory Macro With Multibit Input and Weight for CNN-Based AI Edge Processors.
IEEE J. Solid State Circuits, 2020

A Twin-8T SRAM Computation-in-Memory Unit-Macro for Multibit CNN-Based AI Edge Processors.
IEEE J. Solid State Circuits, 2020

A 4-Kb 1-to-8-bit Configurable 6T SRAM-Based Computation-in-Memory Unit-Macro for CNN-Based AI Edge Processors.
IEEE J. Solid State Circuits, 2020

15.4 A 22nm 2Mb ReRAM Compute-in-Memory Macro with 121-28TOPS/W for Multibit MAC Computing for Tiny AI Edge Devices.
Proceedings of the 2020 IEEE International Solid- State Circuits Conference, 2020

15.5 A 28nm 64Kb 6T SRAM Computing-in-Memory Macro with 8b MAC Operation for AI Edge Chips.
Proceedings of the 2020 IEEE International Solid- State Circuits Conference, 2020

2019
Considerations Of Integrating Computing-In-Memory And Processing-In-Sensor Into Convolutional Neural Network Accelerators For Low-Power Edge Devices.
Proceedings of the 2019 Symposium on VLSI Circuits, Kyoto, Japan, June 9-14, 2019, 2019

A 1Mb Multibit ReRAM Computing-In-Memory Macro with 14.6ns Parallel MAC Computing Time for CNN Based AI Edge Processors.
Proceedings of the IEEE International Solid- State Circuits Conference, 2019

A Twin-8T SRAM Computation-In-Memory Macro for Multiple-Bit CNN-Based Machine Learning.
Proceedings of the IEEE International Solid- State Circuits Conference, 2019

A 55nm 1-to-8 bit Configurable 6T SRAM based Computing-in-Memory Unit-Macro for CNN-based AI Edge Processors.
Proceedings of the IEEE Asian Solid-State Circuits Conference, 2019

A 0.5V Real-Time Computational CMOS Image Sensor with Programmable Kernel for Always-On Feature Extraction.
Proceedings of the IEEE Asian Solid-State Circuits Conference, 2019

2018
A Neuromorphic Computing System for Bitwise Neural Networks Based on ReRAM Synaptic Array.
Proceedings of the 2018 IEEE Biomedical Circuits and Systems Conference, 2018


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