Banca de DEFESA: MATEUS ARNAUD SANTOS DE SOUSA GOLDBARG

Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
STUDENT : MATEUS ARNAUD SANTOS DE SOUSA GOLDBARG
DATE: 20/02/2024
TIME: 09:00
LOCAL: meet.google.com/qzz-okrm-iyw
TITLE:

Aware Compression of Deep Neural Network Models Based on Pruning Followed by Quantization.

KEY WORDS:

Deep learning, Aware Quantization, Aware Pruning, Microservices, Automatic Modulation Classification

PAGES: 100
BIG AREA: Engenharias
AREA: Engenharia Elétrica
SUBÁREA: Eletrônica Industrial, Sistemas e Controles Eletrônicos
SUMMARY:

Deep learning techniques, particularly deep neural networks (DNNs), have been successfully employed in numerous problems. However, these types of algorithms demand substantial computational effort due to the large number of parameters and mathematical operations involved, which can pose challenges for applications with limited computational resources, low latency requirements, or low energy consumption. Thus, this work proposes the application of a novel training strategy for the conscious compression of DNN models based on pruning, quantization, and pruning followed by quantization, capable of reducing processing time and memory footprint. The compression strategy was applied in two domains: the first for automatic modulation classification, where the model size was reduced by 13 times, maintaining an accuracy only 1.8% lower than the uncompressed model. In the second domain, focused on image classification in microservices environments, the same compression strategy was applied. In this context, a 7.6-fold reduction in model size was observed, with accuracy close to the uncompressed model. Furthermore, the implementation of these techniques reduced prediction latency by 1.7 times and significantly decreased the time required for the deployment of microservices containing these models. These results underscore the effectiveness of the proposed approach, indicating its potential positive impact in scenarios that require computational efficiency and resource conservation.

COMMITTEE MEMBERS:
Presidente - 1837240 - MARCELO AUGUSTO COSTA FERNANDES
Interno - 2579664 - ALLAN DE MEDEIROS MARTINS
Interno - ***.521.094-** - SERGIO NATAN SILVA - UFRN
Externa à Instituição - FLAVIA MARISTELA SANTOS NASCIMENTO - IFBA
Externa à Instituição - MARIA GRACIELLY FERNANDES COUTINHO