# Hummingbird: SLO-Oriented GPU Preemption at Microsecond-scale

arXiv: https://arxiv.org/abs/2601.04071 · HTML: https://mlsanity.com/paper/2601.04071/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 7 Jan 2026.

## Built on by (most cited first, 1 of 1)

- [Tessera: Unlocking Heterogeneous GPUs through Kernel-Granularity Disaggregation](https://mlsanity.com/paper/2604.10180/) (2026)

## Abstract (arXiv)

Existing GPU-sharing techniques, including spatial and temporal sharing, aim to improve utilization but face challenges in simultaneously ensuring SLO adherence and maximizing efficiency due to the lack of fine-grained task scheduling on closed-source GPUs. This paper presents Hummingbird, an SLO-oriented GPU scheduling system that overcomes these challenges by enabling microsecond-scale preemption on closed-source GPUs while effectively harvesting idle GPU time slices. Comprehensive evaluations across diverse GPU architectures reveal that Hummingbird improves the SLO attainment of high-priority tasks by 9.7x and 3.5x compared to the state-of-the-art spatial and temporal-sharing approaches. When compared to executing exclusively, the SLO attainment of the high-priority task, collocating with low-priority tasks on Hummingbird, only drops by less than 1%. Meanwhile, the throughput of the low-priority task outperforms the state-of-the-art temporal-sharing approaches by 2.4x. Hummingbird demonstrates significant effectiveness in ensuring the SLO while enhancing GPU utilization.