In this lesson, you will learn how to identify hidden performance drains caused by excessive heap allocations using the Unreal Insights Memory Insights tool.
As your game grows, frequently allocating and deallocating memory on the heap (using new or FMemory::Malloc) can cause severe performance stutters. When the engine's memory allocator is hit repeatedly within a single frame, you trigger heap fragmentation and potential CPU stalls. Memory Insights allows you to visualize exactly where and when these allocations occur, moving beyond simple total-usage stats to granular temporal analysis.
Capturing the Memory Snapshot
To begin, you must run your game with the memory tracing enabled. Add the -trace=memory command-line argument when launching your executable. Once you’ve reproduced a spike or a slow frame in-game, close the application and open the resulting .utrace file in the Unreal Insights browser.
Identifying Allocation Patterns
Inside the Memory Insights tab, look at the Allocation Timeline. You aren't just looking for high usage; you are looking for high frequency.
If you see a "sawtooth" pattern—where memory usage climbs rapidly and drops sharply—your game is likely performing heavy temporary allocations. This often happens inside Tick() functions. For example, if you are creating a temporary array to store results every frame:
// This is a common culprit for heap fragmentation
void AMyActor::Tick(float DeltaTime) {
TArray<FVector> TemporaryPositions;
// Populating this every frame forces a heap allocation each time
CalculateComplexData(TemporaryPositions);
}
By switching to the Allocations view in Insights, you can filter by "Allocation Size" and "Call Stack." If the call stack points to your Tick function, you have found a prime candidate for optimization. Instead of allocating memory every frame, you should declare your array as a member variable (UPROPERTY or standard TArray) and use TemporaryPositions.Reset() to clear the data without freeing the underlying heap memory.
By comparing your "Before" and "After" snapshots, you can confirm that your optimizations have flattened the allocation spikes, leading to a much smoother frame time.
Key Takeaway: Use Memory Insights to hunt for "sawtooth" allocation patterns in your timeline, as these high-frequency heap operations are often the silent killers of consistent frame pacing.