Hardware Acceleration for Machine Learning - Couverture rigide

Couverture rigide

ISBN 10 : 3725878552 ISBN 13 : 9783725878550

Editeur : Mdpi AG, 2026

Synopsis

This Reprint, titled "Hardware Acceleration for Machine Learning", provides a coherent and updated snapshot of the rapidly evolving ecosystem for machine learning acceleration. As hardware platforms transition from general-purpose solutions to specialized heterogeneous architectures, this collection synthesizes cutting-edge developments essential for researchers and designers. The eight contributions within this Reprint cover a full spectrum of advancements, from low-power IoT applications and embedded FPGA and SoC implementations to ASIC edge solutions and efficient data-processing algorithms. Key research presented includes multi-dimensional benchmarking of deep learning inference frameworks, novel power-optimized RTL designs for CNN accelerators, unified FPGA/CGRA pipelines for time-critical edge AI, and new adaptive optimizers designed for training efficiency. Further studies address the performance impacts of data preprocessing techniques, general-purpose hyperdimensional computing accelerators, and innovative approaches to overcoming resource constraints in edge AI through DSP-free architectures and integer-state dynamics in quantized spiking neural networks. By combining these diverse strategies, this collection offers a comprehensive reference for those interested in building implementable, scalable, and energy-sustainable hardware platforms for next-generation intelligent systems.

Détails de l'édition

• Éditeur: Mdpi AG
• Date d'édition: 2026
• Langue: anglais
• ISBN 10: 3725878552
• ISBN 13: 9783725878550
• Reliure: Relié
• Nombre de pages: 202
• Éditeur: Spanò Sergio, Cardarilli Gian Carlo, Di Nunzio Luca
• Coordonnées du fabricant: non disponible
• Personne responsable: GPSR Kontakt; gpsr@libri.de; ; Europaallee 1; Bad Hersfeld; 36244; Allemagne