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Random talk on chips -- how to simulate and calculate power consumption

Date: 2024-1-11 (Source: Internet)

Chip power simulation is an important part of electronic design automation (EDA), which is used to predict and evaluate chip power consumption. In the process of chip design, accurate estimation of power consumption is critical to meet power requirements, optimize chip performance and extend battery life. The following will introduce FDP070AN06A0 The general flow and related technologies of chip power simulation calculation.

1. Power consumption modeling

Chip power modeling is the basis of power simulation calculation, which describes the power characteristics of each component of the chip. There are two common power modeling methods: physical model based modeling and statistical model based modeling.

Physical model based modeling is to build a power consumption model by analyzing the physical structure and circuit characteristics of the chip. This modeling method requires accurate circuit simulation and power supply simulation, and can provide accurate power consumption prediction results. However, the modeling based on physical model needs to consider many details and has high computational complexity.

Statistical model based modeling is to establish a power consumption model by counting the historical power consumption data of the chip. This modeling method can quickly estimate chip power consumption, but its accuracy is relatively low. It is suitable for fast power evaluation in large-scale chip design.

2. Power consumption simulation process

The power simulation calculation generally includes the following steps:

(1) Design input: First, the circuit design of the chip needs to be input into the simulation tool. These design inputs include circuit structure, logic function, process parameters, etc.

(2) Circuit simulation: the simulation tool will conduct accurate circuit simulation to obtain the circuit voltage, current and other parameters.

(3) Power supply simulation: according to the results of circuit simulation, power supply simulation is carried out to calculate the power consumption of the circuit under different working conditions.

(4) Analysis and optimization: According to the power simulation results, the power consumption of the chip is analyzed and optimized. The power consumption can be reduced by changing the circuit structure, logic function and power supply strategy.

(5) Result evaluation: Finally, the optimized power consumption is evaluated to determine whether it meets the power consumption requirements.

3. Power simulation technology

In order to improve the accuracy and efficiency of power simulation, researchers have proposed many related technologies. The following are some common power simulation technologies:

(1) Clock tree simulation: The clock tree is one of the most power consuming parts of the chip, so the clock tree simulation can accurately estimate the clock power consumption. Clock tree simulation needs to consider factors such as clock frequency, clock division ratio and clock buffer.

(2) Power noise simulation: The power noise of the chip can affect the power consumption. By simulating the power supply noise, we can predict the power fluctuation range of the chip.

(3) Temperature simulation: the temperature of the chip will also affect the power consumption. By simulating the temperature change of the chip, the power consumption of the chip at different temperatures can be evaluated.

(4) Power optimization technology: In addition to simulating and calculating power consumption, some optimization technologies can also be used to reduce the power consumption of the chip. For example, using low-power logic design, optimizing clock frequency division ratio, reducing power supply voltage, etc.

Summary:

Chip power simulation is a key step in chip design, which is used to predict and evaluate chip power consumption. It includes power modeling, simulation process and related technologies. Accurate power simulation can help designers optimize chip power consumption, improve chip performance and work efficiency.


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