Low Power Circuit Designs | 9. Advanced Topics and Emerging Trends in Low Power Design by Pavan | Learn Smarter
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9. Advanced Topics and Emerging Trends in Low Power Design

9. Advanced Topics and Emerging Trends in Low Power Design

The chapter discusses the innovations and methodologies in low power design, focusing on technologies such as Near-Threshold Computing and Energy Harvesting. It highlights the importance of machine learning, new materials, ultra-low power memory innovations, chiplet integration, and security measures in modern electronics. The future of semiconductor design is portrayed as a convergence of advanced devices and intelligent systems aimed at extreme energy efficiency.

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  1. 9
    Advanced Topics And Emerging Trends In Low Power Design

    The section discusses the latest advancements in low power design, including...

  2. 9.1
    Introduction

    This section introduces the evolving landscape of low-power design...

  3. 9.2
    Step 1: Near-Threshold And Subthreshold Computing

    This section discusses Near-Threshold Computing (NTC) and Subthreshold...

  4. 9.3
    Step 2: Energy Harvesting And Power-Scavenging Designs

    This section discusses the design of energy harvesting circuits and...

  5. 9.4
    Step 3: Ultra-Low Power Memory Innovations

    The section discusses advancements in ultra-low power memory innovations...

  6. 9.5
    Step 4: Chiplet And Heterogeneous Integration

    This section discusses the significance of chiplet architecture and...

  7. 9.6
    Step 5: Security And Reliability In Low Power Design

    This section discusses the importance of designing secure and robust low...

  8. 9.7

    The conclusion emphasizes the synergy between device innovation, intelligent...

What we have learnt

  • Near-threshold and subthreshold logic enable ultra-low energy devices.
  • AI-based power control and in-memory computing are redefining efficiency.
  • GAAFETs, chiplets, and heterogeneous packaging are reshaping SoC design.
  • Reliability, security, and robustness must scale alongside power optimizations.

Key Concepts

-- NearThreshold Computing (NTC)
A design methodology that operates circuits at voltages near the transistor threshold to achieve energy efficiency while maintaining acceptable performance.
-- Subthreshold Computing
A technique that operates devices below their threshold voltage, using leakage currents for function, enabling ultra-low power consumption suitable for applications like biomedical sensors.
-- Energy Harvesting
Technology that captures ambient energy from environmental sources like light and vibration to power electronic systems.
-- Machine Learning for Power Optimization
The use of AI models to predict workloads and optimize power usage dynamically in semiconductor devices.
-- GateAllAround FETs (GAAFETs)
An advanced transistor design providing improved control and efficiency over FinFETs, especially in ultra-low power applications.
-- InMemory Computing (IMC)
A computational method that integrates memory and logic within the same chip architecture to reduce energy consumption associated with data movement.
-- Chiplet Integration
A design approach that allows different chips (logic, memory, I/O) to be combined in various configurations for improved performance and power efficiency.

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