Laminar: A Probe-First Scheduling Paradigm with Deterministic Runtime Survival
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arXiv
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| Format: | Preprint |
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2026
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| _version_ | 1866915936956579840 |
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| author | Chu, Zhengyan |
| author_facet | Chu, Zhengyan |
| contents | In exascale-oriented GPU clusters, rigid-topology jobs leave behind a fragmented post-landing ecology in which long-resident workloads and highly transient tasks compete for unstable residual capacity. Existing centralized, hierarchical, and local-first decentralized schedulers incur growing coordination and retry-amplification costs in this regime and typically stop their explicit responsibility at execution start, leaving runtime survival to indiscriminate host-level OOM heuristics. We present Laminar, a decentralized probe-first, execute-later scheduling paradigm that keeps hot-path control-plane work near $\mathcal{O}(1)$ through Zone-level probabilistic flow splitting, bounded in-Zone probing by persistent lightweight agents, and node-local arbitration. Laminar further introduces Airlock, a bounded node-local runtime-survival layer that converts severe memory pressure into an ordered policy of suspension, in-situ recovery, bounded secondary re-addressing, or reclamation. By enforcing priority-ordered survival under pressure, Laminar enables lifecycle-aware scheduling that preserves high-value long-resident work and operates closer to physical saturation without relying on protocol-level overcommitment. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2602_13789 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Laminar: A Probe-First Scheduling Paradigm with Deterministic Runtime Survival Chu, Zhengyan Distributed, Parallel, and Cluster Computing C.2.4; D.4.1 In exascale-oriented GPU clusters, rigid-topology jobs leave behind a fragmented post-landing ecology in which long-resident workloads and highly transient tasks compete for unstable residual capacity. Existing centralized, hierarchical, and local-first decentralized schedulers incur growing coordination and retry-amplification costs in this regime and typically stop their explicit responsibility at execution start, leaving runtime survival to indiscriminate host-level OOM heuristics. We present Laminar, a decentralized probe-first, execute-later scheduling paradigm that keeps hot-path control-plane work near $\mathcal{O}(1)$ through Zone-level probabilistic flow splitting, bounded in-Zone probing by persistent lightweight agents, and node-local arbitration. Laminar further introduces Airlock, a bounded node-local runtime-survival layer that converts severe memory pressure into an ordered policy of suspension, in-situ recovery, bounded secondary re-addressing, or reclamation. By enforcing priority-ordered survival under pressure, Laminar enables lifecycle-aware scheduling that preserves high-value long-resident work and operates closer to physical saturation without relying on protocol-level overcommitment. |
| title | Laminar: A Probe-First Scheduling Paradigm with Deterministic Runtime Survival |
| topic | Distributed, Parallel, and Cluster Computing C.2.4; D.4.1 |
| url | https://arxiv.org/abs/2602.13789 |