Power management ICs: meeting new design paradigm challenges
Jae-Inh Song, Dongbu HiTek Co., Ltd.
10/30/2010 11:15 PM EDT
Power management semiconductor market forecast
Power management ICs (PMIC) represents one of the fastest-growing semiconductor market segments. According to iSuppli, the total available power management market is expected to reach $31.4 billion worldwide in 2010 and then more than double by 2014, reaching $45 billion, posting a 15% compound annual growth rate (CAGR), Figure 1. Revenue generated by PMICs is expected to grow from $12.4 billion in 2009 to $19.7 billion in 2014, posting a 14.5% CAGR.
Figure 1: Revenue forecast for PMICs, 2009 â 2014 (in billions of U.S. dollars)
The design paradigm for power management ICs (PMICs) continues to shift from analog-heavy implementations to system-on-chip solutions using digital techniques. Key factors driving this transition are increasing multi-functionality, particularly in consumer electronics and mobile applications, as well as severe pricing pressures to make products affordable and the need for faster turnaround from silicon prototype to shipment of finished ICs. As a result of these factors, chip design and development at smaller geometries has escalated dramatically.
To read the full article, click here
Related Semiconductor IP
- USB 20Gbps Device Controller
- AGILEX 7 R-Tile Gen5 NVMe Host IP
- 100G PAM4 Serdes PHY - 14nm
- Bluetooth Low Energy Subsystem IP
- Multi-core capable 64-bit RISC-V CPU with vector extensions
Related White Papers
- Calibrate and Configure your Power Management IC with NVM IP
- Survey shows SoC design data management is mission critical
- Beat power management challenges in advanced LTE smartphones
- Who's managing your power management?
Latest White Papers
- CRADLE: Conversational RTL Design Space Exploration with LLM-based Multi-Agent Systems
- On the Thermal Vulnerability of 3D-Stacked High-Bandwidth Memory Architectures
- OmniSim: Simulating Hardware with C Speed and RTL Accuracy for High-Level Synthesis Designs
- Balancing Power and Performance With Task Dependencies in Multi-Core Systems
- LLM Inference with Codebook-based Q4X Quantization using the Llama.cpp Framework on RISC-V Vector CPUs