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Autor(en): 
  • Earnest S. Robinson
  • Bare-Metal Machine Learning in Rust: Designing Real-Time AI and Edge Systems on Microcontrollers with Embassy and no_std 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 2 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 14-24 Tagen versandfertig
    Veröffentlichung:  August 2026  
    Genre:  EDV / Informatik 
     
    COMPUTERS / Embedded Computer Systems / COMPUTERS / Microprocessors / DESIGN / Product
    ISBN:  9798194612772 
    EAN-Code: 
    9798194612772 
    Verlag:  Independently Published 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 254 mm / B 178 mm / D 11 mm 
    Gewicht:  368 gr 
    Seiten:  206 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    What if you could execute ultra-low-latency, deterministic neural networks directly on milliwatt microcontrollers-without the bloat of operating systems or Python runtimes?
    Bare-Metal Machine Learning in Rust unlocks the true potential of edge intelligence by combining Rust's memory safety with the raw execution speed of bare-metal silicon. Centered on Rust's #![no_std] ecosystem and the Embassy async framework, this guide provides the blueprint for building, optimizing, and deploying real-time AI workloads straight to embedded hardware.
    What You Will Master:
    Bare-Metal #![no_std] Architecture: Construct crash-proof ML pipelines that operate without heap allocations, dynamic memory management, or OS overhead.
    Async Concurrency with Embassy: Modernize real-time control loops using Embassy's async executor to handle continuous sensor streams and inference tasks simultaneously.
    Model Optimization & Quantization: Convert complex neural network weights into fixed-point, static representations designed for tight RAM and flash memory constraints.
    Predictable Execution: Eliminate runtime panics, garbage collection pauses, and non-deterministic delays to guarantee sub-millisecond response times.
    Hands-On Edge Systems: Implement end-to-end edge AI applications-from real-time signal processing to predictive maintenance-tailored for ARM Cortex-M and RISC-V targets.
    Stop relying on resource-heavy runtimes and fragile cloud connections. Order your copy today and build the next generation of fast, secure, and deterministic edge AI on bare silicon.
    What if you could execute ultra-low-latency, deterministic neural networks directly on milliwatt microcontrollers-without the bloat of operating systems or Python runtimes?
    Bare-Metal Machine Learning in Rust unlocks the true potential of edge intelligence by combining Rust's memory safety with the raw execution speed of bare-metal silicon. Centered on Rust's #![no_std] ecosystem and the Embassy async framework, this guide provides the blueprint for building, optimizing, and deploying real-time AI workloads straight to embedded hardware.
    What You Will Master:
    Bare-Metal #![no_std] Architecture: Construct crash-proof ML pipelines that operate without heap allocations, dynamic memory management, or OS overhead.
    Async Concurrency with Embassy: Modernize real-time control loops using Embassy's async executor to handle continuous sensor streams and inference tasks simultaneously.
    Model Optimization & Quantization: Convert complex neural network weights into fixed-point, static representations designed for tight RAM and flash memory constraints.
    Predictable Execution: Eliminate runtime panics, garbage collection pauses, and non-deterministic delays to guarantee sub-millisecond response times.
    Hands-On Edge Systems: Implement end-to-end edge AI applications-from real-time signal processing to predictive maintenance-tailored for ARM Cortex-M and RISC-V targets.
    Stop relying on resource-heavy runtimes and fragile cloud connections. Order your copy today and build the next generation of fast, secure, and deterministic edge AI on bare silicon.

      



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