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Determinism-Preserving GPU Spatial Sharing with Vitamin-E
[Submitted on 16 Mar 2026 (v1), last revised 5 Aug 2026 (this ve · 2026-03-16 · via cs.DC updates on arXiv.org

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Abstract:GPU sharing faces a determinism--utilization tradeoff: fixed bindings can strand capacity as demand fluctuates, while resource-driven kernel reshaping improves utilization by altering a launch's parallel structure, potentially changing output bits. We rethink modern GPU scheduling and observe that it decouples logical structure from physical width: one unmodified launch spans a family of widths through changes in block placement and wave count. From this observation, we derive the parallel-structure invariant: for fixed-structure deterministic workloads, keeping each launch immutable makes its output bits independent of physical width.
Guided by this invariant, Vitamin-E late-binds immutable launches to pooled physical contexts, preserving bitwise equality across allocations, whereas resource-driven reshaping can alter the selected token under temperature-zero greedy decoding. Across all workload--baseline comparisons, Vitamin-E achieves up to 3.50$\times$ the aggregate normalized LLM training throughput, 62.5\% lower inference p99 latency, and 1.43$\times$ the background-training throughput. With the same mechanism, \textsc{TPOT-First} reduces TPOT SLO violations by up to 46.1\% over \textsc{Throughput-Oriented} on three serving workloads, demonstrating mechanism effectiveness and policy flexibility.

Submission history

From: Zhenyuan Yang [view email]
[v1] Mon, 16 Mar 2026 09:48:34 UTC (3,121 KB)
[v2] Tue, 17 Mar 2026 08:51:40 UTC (3,121 KB)
[v3] Fri, 3 Apr 2026 11:51:07 UTC (3,212 KB)
[v4] Wed, 5 Aug 2026 05:18:06 UTC (796 KB)