Question
Which strategy prevents memory spikes during high-volume AssetManager loading?
Dev Maple
0 reputation · 14 Feb 2025, 02:12 UTC
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0 reputation · 14 Feb 2025, 02:12 UTC
The libGDX AssetManager utilizes an asynchronous queue to load resources like textures and shaders without blocking the render thread. While update() handles the progression of this queue, there is a potential for significant memory spikes when a large volume of assets is queued simultaneously before they are uploaded to the GPU and the CPU-side buffers are cleared.
In scenarios requiring the loading of hundreds of high-resolution assets, simply calling load() for all items may exceed available heap space before the manager can process the queue efficiently.
AssetManager support a native way to throttle the number of concurrent loading tasks?32275 reputation · 14 Feb 2025, 09:27 UTC
The strategy that prevents memory spikes is to throttle the number of concurrently loading assets – load assets in small batches and let AssetManager.update() process them each frame.
libgdxAssetManager loads assets asynchronously; data stays in CPU memory until the GPU upload finishes.load() calls are queued before update() processes them, each asset’s buffer occupies heap simultaneously, causing a spike.Limiting concurrent loads reduces the number of active CPU buffers at any moment, smoothing memory usage and avoiding the peak that triggers GC or OOM.
manager.update() to advance any ongoing loads.manager.load() for the next asset.manager.getProgress() or manager.update() returning true when all queued assets are done.Are you currently calling finishLoadingAsset() (or finishLoading()) immediately after queuing all load() calls, or are you already invoking update() each frame? Knowing this determines whether you need to introduce the batching loop or simply adjust your existing update timing.
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32,275 reputation · 14 Feb 2025, 11:12 UTC
Since libGDX 1.10 the AssetManager exposes a setConcurrentLoading(int) method. Setting it to a modest value (e.g., 2–4) caps the number of assets that are read from disk and buffered simultaneously. update() will only advance that many loads per call, so the CPU‑side buffers stay small.
Even with this throttle, very large textures can still bloat the heap if you queue them all at once. The safest pattern is to:
load() for a small batch.update() each frame until it returns true.Monitoring heap usage with VisualVM while experimenting with different setConcurrentLoading values gives a clear picture of the trade‑off between load time and memory footprint.