Publication

Impact of Memory Voltage Scaling on Accuracy and Resilience of Deep Learning Based Edge Devices

About
Privacy
Disclaimer

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Impact of Memory Voltage Scaling on Accuracy and Resilience of Deep Learning Based Edge Devices

Graph Chatbot

Chat with Graph Search

EdgeAI-Aware Design of In-Memory Computing Architectures

Low Power LDPC Decoding by Reliable Voltage Down-Scaling

In-Memory Hardware and Architectural Extensions for Workloads Acceleration

Error Resilient In-Memory Computing Architecture for CNN Inference on the Edge

Exploration Methodology for BTI-Induced Failures on RRAM-Based Edge AI Systems

Low-Power Design of Digital VLSI Circuits around the Point of First Failure

Fusing TensorFlow with building energy simulation for intelligent energy management in smart cities

Hardware/Software Co-Design and Reliability Analysis of Ultra-Low Power Biomedical Devices

A Product Engine for Energy-Efficient Execution of Binary Neural Networks Using Resistive Memories

A 24 kb Single-Well Mixed 3T Gain-Cell eDRAM with Body-Bias in 28 nm FD-SOI for Refresh-Free DSP Applications