PITCHD 2024 EDITION: THE 1st PITCHD
Estimating the reliability of DNNs in the face of permanent GPU hardware failures
Mr. Juan Balaguera, PhD Candidate, DAUIN
Graphic Processing Units (GPUs) are crucial for modern Deep Neural
Network (DNN) acceleration. However, these devices can be affectedby faults that might jeopardize the DNNs' realiability. My researchproposes fault simulation strategies to effectively assess the impact of
permanent defects on GPUs regardless of the softwareimplementation of the neural networks.
Functional Stimuli Generation for Burn-In Test
Mr. Nick Deligiannis, PhD Candidate, DAUIN
In high-reliability applications, Burn-In testing (BI) is crucial to combat
early failures. Traditional static BI is inefficient for modern dense
circuits. In this work, we propose automated methods able to
generate effective, functional stress inducing stimuli, especially for
pipelined processors, destined for dynamic BI test.
Reliability and Performance Challenges of Next-Generation Smart Power Battery Management Systems for Electric Mobility
Mr. Amirhossein Ahmadi, PhD Candidate, DET
This project discusses the impact of electromagnetic interference
(EMI) on the battery management systems (BMS) and BMS vertical
interface (VIF). The susceptibility to EMI is tackeld by transistor-level
simulations and tests for the first time aiming to highlight the failure
mechanisms and consequently to propose methods to enhance the
performance.
Date and Time
Location
Hosts
Registration
- Date: 04 Mar 2024
- Time: 05:00 PM to 06:30 PM
- All times are (UTC+01:00) Rome
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- Politecnico di Torino, Corso Duca Degli Abruzzi 24
- Torino, Piemonte
- Italy 10129
- Building: DET
- Room Number: Maxwell Room
- Click here for Map