The continuous drive for performance enhancement, coupled with the need for energy efficiency in ICs, is challenging engineers to address power consumption at the most granular level. In high-performance computing, mobile processors, and even low-power IoT devices, power management must be an integral part of the design, directly influencing the thermal stability, reliability, and overall efficiency of semiconductor devices. In this blog, we’ll dig deeper into the newest techniques that could help reduce power consumption in modern IC designs.
Dynamic vs. Static Power Consumption in Advanced Nodes
In modern semiconductor design, power consumption is categorized into dynamic and static components, each demanding specialized mitigation techniques, especially as we approach sub-5nm technology nodes.
- Dynamic Power: Dominated by the charging and discharging of capacitive loads during transistor switching, dynamic power is defined by the formula:
Pdynamic = αCV²ƒ
The activity factor (𝛼) represents the proportion of gates switching per clock cycle, reflecting circuit activity. C is the load capacitance, V is the supply voltage, and ƒ is the clock frequency. Traditionally, reducing V and ƒ has been effective in minimizing dynamic power; however, in sub-10nm nodes, capacitance scaling becomes essential. Advanced FinFETs and GAAFET architectures now employ innovations such as high-k dielectrics to optimize gate capacitance, enabling sustained performance while controlling dynamic power dissipation.
- Static Power: Static or leakage power, primarily due to subthreshold leakage and gate oxide tunneling, has become a major concern at smaller technology nodes (e.g., 5nm, 3nm). As gate oxides thin to atomic-scale layers, quantum tunneling contributes significantly to leakage current. In ultra-low-power designs, such as wearables or IoT devices, leakage management is prioritized through multi-threshold CMOS (MTCMOS) and back-biasing techniques, allowing leakage to be traded off for performance in non-critical areas. Emerging technologies such as NCFETs show promise in further reducing leakage by utilizing ferroelectric materials for ultra-low-power designs.
Power Gating and Clock Gating for Energy Optimization
Power and clock gating are essential for reducing IC power consumption, especially in systems with varying workloads or idle phases.
- Power Gating: This approach involves cutting off power to blocks of logic when not in use, substantially reducing leakage. For example, in Qualcomm’s Snapdragon SoCs, power islands dynamically shut off cores based on workload, reducing leakage current during idle periods. These systems are further refined with voltage regulators that adjust power supply levels for active blocks, ensuring minimal energy waste without sacrificing performance. While power gating significantly reduces leakage, it may introduce wake-up latency and design challenges that must be balanced against energy savings.
- Clock Gating: This disables the clock signal to inactive circuit sections, minimizing unnecessary switching and dynamic power consumption. Modern ARM architectures, especially those used in mobile devices, leverage clock gating across various design levels—from individual gates to entire cores. This method achieves substantial energy savings, particularly in mobile SoCs where idle time is considerable.
Challenges of Node Shrinking and Power Consumption in Sub-7nm Technologies
With advancements to sub-7nm nodes, power management becomes increasingly complex, with leakage power and heat dissipation emerging as significant issues.
- Increased Leakage in Ultra-Small Nodes: The aggressive scaling of transistors increases leakage currents, with subthreshold leakage, gate-induced drain leakage (GIDL), and drain-induced barrier lowering (DIBL) as primary contributors. Engineers are turning to advanced materials and architectures like GAAFETs and vertical nanowires to counteract these effects. Additionally, introducing low-leakage transistors in non-critical paths and using back-biasing helps mitigate leakage current, enabling more sustainable designs.
- Thermal Runaway and Heat Dissipation: The smaller the transistors, the higher the power density, increasing susceptibility to thermal runaway. Advanced designs like Apple’s M1 chips employ robust thermal management systems, including heat spreaders and dynamic thermal throttling algorithms, to balance performance and thermal stability. These systems integrate real-time power monitoring circuits to adjust voltages and frequencies dynamically in response to thermal conditions.
Low-Power Design in IoT and Edge Devices
For IoT and edge devices with limited battery life, advanced low-power strategies are crucial.
- Dynamic Voltage and Frequency Scaling (DVFS): DVFS allows circuits to adjust voltage and frequency based on workload demands, reducing power when full performance is unnecessary. This technique is precious for IoT and edge devices, where peak performance demands are typically intermittent.
- Multi-Threshold CMOS (MTCMOS): MTCMOS is extensively used in ultra-low-power devices, such as wearables and sensor networks, where low-threshold transistors are employed in performance-critical sections and high-threshold transistors minimize leakage in non-critical areas. STMicroelectronics' STM32 microcontrollers are a prime example, employing MTCMOS to optimize both active and standby power consumption.
AI-Driven Power Optimization: A Forward-Looking Approach
AI and machine learning integration into power management systems is transforming IC power optimization.
- AI-Powered Dynamic Power Management: By analyzing real-time workloads and predicting computational demands, AI algorithms adjust power states within SoCs dynamically. Nvidia’s AI-based power management, utilized in GPUs, distributes workloads efficiently, enabling precise control over voltage and clock scaling to minimize power consumption during intensive computations. Use cases like data centers and autonomous vehicles benefit significantly, as AI-based workload prediction helps lower operational costs.
Quantum Tunneling Power Recovery: A Revolutionary Concept
In sub-5nm regimes, quantum mechanical effects such as tunneling dominate static power dissipation. Though still in research, capturing leakage currents using quantum capacitors is being explored as a future solution. By using advanced materials like graphene and 2D structures, engineers are exploring methods to capture and recycle tunneling leakage currents. These "quantum capacitors" store and reuse energy from otherwise wasted leakage currents, reducing net power consumption in energy-constrained applications, such as edge computing. Charge recovery mechanisms within leakage-prone areas of modern FinFET or GAAFET architectures can lead to substantial power savings, enhancing the longevity of low-power ICs.
Simulating Power Consumption: Tools for Design Optimization
Tools like SPICE and Cadence are invaluable in the design phase, allowing engineers to simulate power consumption accurately across various IC configurations. These tools help in identifying and optimizing potential leakage and dynamic power hotspots, enabling fine-tuning of power management techniques well before final production. With advanced node designs becoming increasingly complex, such simulations are indispensable for achieving precise power targets.
At McKinsey Electronics, we’re dedicated to providing industry-leading semiconductors and expert design guidance that enable engineers to push the boundaries of efficient, high-performance ICs. By equipping our partners with components from leading manufacturers and offering technical insights into effective power management techniques, we help engineers design circuits that address both dynamic and static power challenges at the sub-5nm level. You can then leverage the latest advances in power reduction—from AI-driven optimization to innovative gating techniques and beyond—to achieve greater efficiency and sustainability in your semiconductor applications. Contact us today.