Processor architecture not a factor for low-power mobile systems
DSP DesignLine (April 20, 2009)
Much is made in marketing literature of the energy efficiency of different processor architectures. The power consumption of the processor is relevant but a small component of the overall power budget of the device. The instruction set architecture (x86, ARM, or otherwise) has a minimal effect on the power consumption of a processor and is of negligible consequence to the mobile system power budget.
Mobile consumer electronics devices are generally built from some combination of the components shown in Table 1.
Ultimately these machines must serve their human users by tickling the senses. The human eye requires a certain amount of incident light energy to clearly see an image. That sets a minimum amount of light power per unit area that a display must emit. The 1.7 inch display of a clam shell flip phone requires about 150 mW, a 3.5 inch smart phone display requires about 600 mW, an 8.4-inch mobile internet device display requires about 3 watts, and a 15-inch notebook computer display might require 10 watts. Those numbers do vary significantly depending on how the user sets the brightness control.
E-mail This Article | Printer-Friendly Page |
Related Articles
New Articles
- Quantum Readiness Considerations for Suppliers and Manufacturers
- A Rad Hard ASIC Design Approach: Triple Modular Redundancy (TMR)
- Early Interactive Short Isolation for Faster SoC Verification
- The Ideal Crypto Coprocessor with Root of Trust to Support Customer Complete Full Chip Evaluation: PUFcc gained SESIP and PSA Certified™ Level 3 RoT Component Certification
- Advanced Packaging and Chiplets Can Be for Everyone
Most Popular
- System Verilog Assertions Simplified
- System Verilog Macro: A Powerful Feature for Design Verification Projects
- UPF Constraint coding for SoC - A Case Study
- Dynamic Memory Allocation and Fragmentation in C and C++
- Enhancing VLSI Design Efficiency: Tackling Congestion and Shorts with Practical Approaches and PnR Tool (ICC2)