Introduction
As mobile games continue to increase in visual complexity and gameplay intensity, power consumption has become a critical performance constraint. Based on collected profiling data, we analyzed several core factors that influence energy usage in real game scenarios.
Using Perfetto-based metrics and supporting profiling tools, we categorize power consumption into five main areas: CPU, GPU, bandwidth (memory traffic), screen, and network activity.
This article summarizes observed relationships between these factors and real-world power behavior in mobile games.
1. GPU: The Most Direct Driver of Power Consumption
GPU behavior shows a strong and direct correlation with power usage.
In tests conducted on a live game under different graphical quality settings, GPU Clocks and GPU power consumption exhibited a clear positive relationship.
When switching from a low-quality (smooth) preset to a higher-quality preset:
- GPU Clocks increase significantly
- GPU Power Rails increase accordingly
- Overall device power consumption rises noticeably
This confirms that GPU load is one of the most sensitive and direct contributors to power consumption in rendering-heavy scenarios.
In practical terms, higher visual quality almost always translates into higher GPU frequency and higher energy usage.
2. Bandwidth: A Major but Often Underestimated Factor
Bandwidth plays a significant role in both memory and GPU-related power consumption.
In a test scenario involving an empty scene with up to 30 layers of transparent objects, we evaluated the impact of texture compression and mipmap usage.
The results show:
- Enabling mipmaps reduces bandwidth significantly
- The impact of mipmaps on power consumption is even more noticeable than texture compression alone
After enabling mipmaps (up to 50 layers test condition):
- Bandwidth dropped from ~6 GB/s to ~1.5 GB/s
- Overall power consumption decreased significantly
- GPU-related metrics such as GPU Clocks also decreased
This indicates that bandwidth is not only a memory-side cost but also indirectly influences GPU workload.
Empirical Observation
Based on data fitting:
Each additional 1 GB/s bandwidth increase corresponds to approximately 60–70 mW additional power consumption.
This aligns in magnitude with industry observations (~100 mW per 1 GB/s).
Practical Recommendation
In 3D rendering pipelines, enabling mipmaps for all textures is strongly recommended to reduce bandwidth pressure and energy consumption.
3. Screen Power Consumption: Brightness, Refresh Rate, and Content Matter
Screen power usage depends on multiple factors:
- Brightness level
- Refresh rate
- Display content
Test results show:
- Higher brightness increases power consumption
- Higher refresh rates increase power usage (90 Hz consistently higher than 60 Hz under identical conditions)
An unexpected finding is that screen content itself also affects power consumption significantly:
- Black frames consume less power
- High-saturation frames consume more power
In most games, screen power consumption typically ranges between:
150–200 mW
Values significantly above this range may indicate abnormal display behavior or configuration issues.
4. Network: Background Communication Still Matters
Network activity contributes measurable power consumption during both Wi-Fi and cellular data transfers.
Key observations:
- Network downloads increase both network and CPU power usage
- Typical network-related power consumption ranges between 100–200 mW
In production game tests, even under low-interaction or idle conditions (anti-AFK scenarios), network power consumption can remain unexpectedly high.
This suggests unnecessary or excessive background communication should be investigated and optimized.
5. CPU: Frequency and Thread Distribution Are Critical
CPU power consumption is strongly influenced by operating frequency.
Using Gears for profiling, comparisons between main-thread execution and Job System execution show:
- Heavy computation on the main thread keeps big CPU cores at high frequency
- This leads to significantly increased power consumption
- Moving workloads into Job System reduces big-core frequency and lowers overall power usage
This behavior is expected because CPU power consumption increases non-linearly with frequency due to the voltage-frequency relationship.
Key Insight
CPU power is not only frequency-dependent but also strongly affected by voltage scaling, making high-frequency operation disproportionately expensive in terms of energy usage.
Optimization Guidance
- Avoid long-term high-frequency usage on big cores
- Distribute workloads across threads properly
- Monitor abnormal CPU time distribution in subthreads
In real-world cases, fixing an abnormal network subthread alone reduced total power consumption by nearly 1W.
6. Profiling Consistency Issue: Release vs Debug Builds
During analysis using SimplePerf, a discrepancy was observed:
- GOT Online reports showed nearly 10× differences in function contribution
- SimplePerf results showed similar values
This was traced back to build configuration differences:
- GOT Online used Release builds
- SimplePerf used Debug builds (for symbol visibility)
Later verification confirmed:
- Release builds with IL2CPP still allow function-level visibility in SimplePerf
- Results become consistent with expectations when using proper Release configuration
This highlights the importance of consistent build settings in performance analysis.
Conclusion
Game power consumption does not have a single root cause or “silver bullet”.
It is the combined result of multiple interacting factors:
- GPU workload
- Memory bandwidth
- CPU frequency behavior
- Screen configuration
- Network activity
Only through data-driven analysis can developers accurately identify the dominant sources of power consumption and apply targeted optimizations.
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