Flex-MIG: Enabling Distributed Execution on MIG
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866917077847113728 |
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| author | Kim, Myeongsu Yeom, Ikjun Kim, Younghoon |
| author_facet | Kim, Myeongsu Yeom, Ikjun Kim, Younghoon |
| contents | GPU clusters in multi-tenant settings often suffer from underutilization, making GPU-sharing technologies essential for efficient resource use. Among them, NVIDIA Multi-Instance GPU (MIG) has gained traction for providing hardware-level isolation that enables concurrent workloads without interference. However, MIG's hardware rigidity and the conventional one-to-one allocation model jointly lead to severe fragmentation and cluster-wide underutilization. We present Flex-MIG, a software-only framework that replaces one-to-one with a one-to-many allocation model and enables host-shared-memory collectives across MIG instances without hardware modification. Flex-MIG eliminates drain-required reconfiguration, reduces fragmentation, and improves makespan by up to 17% across diverse traces, showing that rethinking MIG's operational model as a software-coordinated layer substantially improves cluster efficiency. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_09143 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Flex-MIG: Enabling Distributed Execution on MIG Kim, Myeongsu Yeom, Ikjun Kim, Younghoon Distributed, Parallel, and Cluster Computing D.4.7; C.1.4 GPU clusters in multi-tenant settings often suffer from underutilization, making GPU-sharing technologies essential for efficient resource use. Among them, NVIDIA Multi-Instance GPU (MIG) has gained traction for providing hardware-level isolation that enables concurrent workloads without interference. However, MIG's hardware rigidity and the conventional one-to-one allocation model jointly lead to severe fragmentation and cluster-wide underutilization. We present Flex-MIG, a software-only framework that replaces one-to-one with a one-to-many allocation model and enables host-shared-memory collectives across MIG instances without hardware modification. Flex-MIG eliminates drain-required reconfiguration, reduces fragmentation, and improves makespan by up to 17% across diverse traces, showing that rethinking MIG's operational model as a software-coordinated layer substantially improves cluster efficiency. |
| title | Flex-MIG: Enabling Distributed Execution on MIG |
| topic | Distributed, Parallel, and Cluster Computing D.4.7; C.1.4 |
| url | https://arxiv.org/abs/2511.09143 |