Validating Optimization Results

In this lesson, you will learn how to verify the effectiveness of your optimizations by systematically comparing your post-optimization data against your established initial performance baseline.

The Science of Validation

Optimization is an iterative process, but it is easy to fall into the trap of "blind optimization"—where you implement a fix without verifying that it actually improved the targeted bottleneck. To validate your results, you must rely on the performance baseline you created earlier. Without a recorded "before" state, you cannot mathematically prove your "after" state provides the gains you expect.

Establishing the "Diff"

When validating, consistency is everything. You should capture your trace data using the exact same hardware, game build, and environmental conditions (e.g., same camera path, same number of actors) used for your initial baseline.

Once you have your new Unreal Insights trace, load both the baseline and the optimized version into the Insights Timing View. Look specifically at the Frame Time and the relevant GameThread or RenderThread markers you identified as the bottleneck.

For example, if you optimized a custom network serialization function:

1. Compare Average Execution Time: Use the Stats tab to view the mean, min, and max execution times of the function.
2. Check for Regressions: Sometimes an optimization reduces CPU usage but increases memory overhead or cache misses. Check your memory markers to ensure your fix didn't introduce a new bottleneck.
3. Automate Comparison: You can use console commands like stat unit or stat game while running the same recorded gameplay sequence to perform a quick visual verification:

# In the console, execute to compare
stat startfile  # Start capturing
# Run your standardized test sequence
stat stopfile   # Save the trace

Interpreting the Results

If the delta (the difference) shows your targeted function is faster, you have successfully optimized. However, if the overall frame time hasn't budged, you haven't solved the actual bottleneck; you’ve simply optimized a non-critical path. Always ensure the "Time Spent" reduction in your function correlates to a proportional increase in your frame rate or decrease in frame time.

Key Takeaway: Optimization is only successful if you can mathematically demonstrate a reduction in latency or resource consumption using a consistent, repeatable performance baseline.