Communication Dans Un Congrès Année : 2025

Automatic generation of input-aware approximate arithmetic circuits

Résumé

Approximate Computing (AxC) is systematically applied across various abstraction levels to reduce overheads and enhance the performance of applications such as image processing and machine learning. However, AxC does not typically consider the specific workload (i.e., data input) of a given application. For instance, in signal processing applications like filters, some inputs are constants (filter coefficients), which allows for an additional level of approximation by considering the specific input distribution. This method is known as "Input-Aware Approximation" (IAA) and has shown potential advantages in previous studies. Unfortunately, existing input-aware design methodologies lack scalability as they mostly depend on ad-hoc, non-automatic design approaches, limiting their applicability. In this paper, we investigate how the input-aware approximate design approach can be integrated into a systematic, generic, and automatic design flow. We employ state-of-the-art approximation and multi-objective optimization techniques to achieve input awareness. Our experimental results, focusing on classical signal processing applications like FIR filters, demonstrate that the input-aware approach can provide significant savings in both area and power consumption.

Fichier principal
Vignette du fichier
DDECS_2025_IAA.pdf (396.52 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)
Licence

Dates et versions

hal-05333876 , version 1 (27-10-2025)

Licence

Identifiants

Citer

Mario Barbareschi, Salvatore Barone, Alberto Bosio, Bastien Deveautour, Ali Piri, et al.. Automatic generation of input-aware approximate arithmetic circuits. DDECS 2025 - IEEE 28th International Symposium on Design and Diagnostics of Electronic Circuits and Systems, May 2025, Lyon, France. pp.139-144, ⟨10.1109/DDECS63720.2025.11006680⟩. ⟨hal-05333876⟩
152 Consultations
132 Téléchargements

Altmetric

Partager

  • More