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arXiv · 2602.21248

BuffCut: Prioritized Buffered Streaming Graph Partitioning

Linus Baumgärtner·Adil Chhabra·Marcelo Fonseca Faraj·Christian Schulz
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Abstract

Streaming graph partitioners enable resource-efficient and massively scalable partitioning, but one-pass assignment heuristics are highly sensitive to stream order and often yield substantially higher edge cuts than in-memory methods. We present BuffCut, a buffered streaming partitioner that narrows this quality gap, particularly when stream ordering is adversarial, by combining prioritized buffering with batch-wise multilevel assignment. BuffCut maintains a bounded priority buffer to delay poorly informed decisions and regulate the order in which nodes are considered for assignment. It incrementally constructs high-locality batches of configurable size by iteratively inserting the highest-priority nodes from the buffer into the batch, effectively recovering locality structure from the stream. Each batch is then assigned via a multilevel partitioning algorithm. Experiments on diverse real-world and synthetic graphs show that BuffCut consistently outperforms state-of-the-art buffered streaming methods. Compared to the strongest prioritized buffering baseline, BuffCut achieves 20.8% fewer edge cuts while running 2.9 times faster and using 11.3 times less memory. Against the next-best buffered method, it reduces edge cut by 15.8% with only modest overheads of 1.8 times runtime and 1.09 times memory.

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Linus Baumgärtner, Adil Chhabra, Marcelo Fonseca Faraj, Christian Schulz. 2026-02-18. BuffCut: Prioritized Buffered Streaming Graph Partitioning. https://arxiv.org/abs/2602.21248

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