Reproduce “WorldPager: Zero-Stall Tiered Memory for Long-Horizon World Models on a Single Consumer GPU” on OpenResearch

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About this paper

Bingnan Liu, Ruini Xue

WorldPager extends interactive world models by storing compressed attention state across GPU, host memory, and NVMe, and prefetching needed chunks during generation. It predicts retrieval from camera pose and reuses the set after a miss. On an RTX 4090, it generated 3,000 chunks, or 37.5 minutes of video, within host-memory limits without stalls above 0.5 ms; the run took 63.2 minutes, not real-time.

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