Use este identificador para citar ou linkar para este item: http://repositorio.utfpr.edu.br/jspui/handle/1/29755
Título: Special session: how much quality is enough quality? A case for acceptability in approximate designs
Autor(es): Felzmann, Isaías Bittencourt
Fabrício Filho, João
Oliveira, Juliane Regina de
Wanner, Lucas Francisco
Palavras-chave: Teoria da aproximação
Imagens digitais
Processamento de sinais
Energia - Consumo
Approximation theory
Digital images
Signal processing
Energy consumption
Data do documento: 24-Out-2021
Câmpus: Campo Mourao
Citação: FELZMANN, Isaías; FABRÍCIO FILHO, João; OLIVEIRA, Juliane Regina de; WANNER, Lucas. Special session: how much quality is enough quality? A case for acceptability in approximate designs. In: INTERNATIONAL CONFERENCE ON COMPUTER DESIGN, 39., 2021, Storrs. Anais eletrônicos […]. Los Alamitos: IEEE Computer Society, Conference Publishing Services, 2021. p. 5-8. DOI: 10.1109/ICCD53106.2021.00013. Disponível em: https://ieeexplore.ieee.org/document/9643638. Acesso em: 09 jun. 2022.
Abstract: Approximate systems are designed to offer improved efficiency with potentially reduced quality of results. Quality of output in these systems is typically quantified in comparison to a precise result using metrics such as RMSE, MAE, PSNR, or application-specific metrics such as structural similarity of images (SSIM). Furthermore, systems are typically designed to maximize efficiency for a given minimum quality requirement. It is often difficult to determine what this quality requirement should be for an application, let alone a system. Thus, a fixed quality requirement may be overly conservative, and leave optimization opportunities on the table. In this work, we present a different approach to evaluate approximate systems based on the usefulness of results instead of quality. Our method qualitatively determines the acceptability of approximate results within different processing pipelines. To demonstrate the method, we implement three image and signal processing applications featuring scenarios of image classification, image recognition, and frequency estimation. Our results show that designing approximate systems to guarantee acceptability can produce up to 20% more valid results than the conservative quality thresholds commonly adopted in the literature, allowing for higher error rates and, consequently, lower energy cost.
URI: http://repositorio.utfpr.edu.br/jspui/handle/1/29755
ISBN: 9781665432191
ISSN: 2576-6996
Aparece nas coleções:PCS - Trabalhos publicados em Eventos

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