9783725878550 - hardware acceleration for machine learning (8 risultati)
- Rilegato
Da: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 72,88
Spedizione gratuitaSpedito in U.S.A.Quantità: Più di 20 disponibili
HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
- Rilegato
Da: California Books, Miami, FL, U.S.A.California Books
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 73,08
Spedizione gratuitaSpedito in U.S.A.Quantità: Più di 20 disponibili
Condizione: New.
- Rilegato
Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 68,48
EUR 5,85 spedizioneSpedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
- Rilegato
- Print on Demand
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 79,12
Spedizione gratuitaSpedito in U.S.A.Quantità: 1 disponibili
Hardcover. Condizione: new. Hardcover. 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 c…ollection 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. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
- Rilegato
- Print on Demand
Da: CitiRetail, Stevenage, Regno UnitoCitiRetail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 77,41
EUR 43,12 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Hardcover. Condizione: new. Hardcover. 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 c…ollection 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
- Rilegato
- Print on Demand
Da: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 92,12
EUR 32,01 spedizioneSpedito da Australia a U.S.A.Quantità: 1 disponibili
Hardcover. Condizione: new. Hardcover. 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 c…ollection 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. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
- Rilegato
- Print on Demand
Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 94,69
EUR 63,53 spedizioneSpedito da Germania a U.S.A.Quantità: 2 disponibili
Buch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering.
- Rilegato
- Print on Demand
Da: preigu, Osnabrück, Germaniapreigu
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 106,60
EUR 70,00 spedizioneSpedito da Germania a U.S.A.Quantità: 5 disponibili
Buch. Condizione: Neu. Hardware Acceleration for Machine Learning | Buch | Englisch | 2026 | MDPI AG | EAN 9783725878550 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
