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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Acceso en línea: | https://arxiv.org/abs/2510.15882 |
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| _version_ | 1866911218192613376 |
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| author | Shen, Ao Zhang, Rui Zhao, Junping |
| author_facet | Shen, Ao Zhang, Rui Zhao, Junping |
| contents | As large language models (LLMs) continue to scale, multi-node deployment has become a necessity. Consequently, communication has become a critical performance bottleneck. Current intra-node communication libraries, like NCCL, typically make use of a single interconnect such as NVLink. This approach creates performance ceilings, especially on hardware like the H800 GPU where the primary interconnect's bandwidth can become a bottleneck, and leaves other hardware resources like PCIe and Remote Direct Memory Access (RDMA)-capable Network Interface Cards (NICs) largely idle during intensive workloads. We propose FlexLink, the first collective communication framework to the best of our knowledge designed to systematically address this by aggregating these heterogeneous links-NVLink, PCIe, and RDMA NICs-into a single, high-performance communication fabric. FlexLink employs an effective two-stage adaptive load balancing strategy that dynamically partitions communication traffic across all available links, ensuring that faster interconnects are not throttled by slower ones. On an 8-GPU H800 server, our design improves the bandwidth of collective operators such as AllReduce and AllGather by up to 26% and 27% over the NCCL baseline, respectively. This gain is achieved by offloading 2-22% of the total communication traffic to the previously underutilized PCIe and RDMA NICs. FlexLink provides these improvements as a lossless, drop-in replacement compatible with the NCCL API, ensuring easy adoption. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_15882 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | FlexLink: Boosting your NVLink Bandwidth by 27% without accuracy concern Shen, Ao Zhang, Rui Zhao, Junping Hardware Architecture Artificial Intelligence Distributed, Parallel, and Cluster Computing Machine Learning As large language models (LLMs) continue to scale, multi-node deployment has become a necessity. Consequently, communication has become a critical performance bottleneck. Current intra-node communication libraries, like NCCL, typically make use of a single interconnect such as NVLink. This approach creates performance ceilings, especially on hardware like the H800 GPU where the primary interconnect's bandwidth can become a bottleneck, and leaves other hardware resources like PCIe and Remote Direct Memory Access (RDMA)-capable Network Interface Cards (NICs) largely idle during intensive workloads. We propose FlexLink, the first collective communication framework to the best of our knowledge designed to systematically address this by aggregating these heterogeneous links-NVLink, PCIe, and RDMA NICs-into a single, high-performance communication fabric. FlexLink employs an effective two-stage adaptive load balancing strategy that dynamically partitions communication traffic across all available links, ensuring that faster interconnects are not throttled by slower ones. On an 8-GPU H800 server, our design improves the bandwidth of collective operators such as AllReduce and AllGather by up to 26% and 27% over the NCCL baseline, respectively. This gain is achieved by offloading 2-22% of the total communication traffic to the previously underutilized PCIe and RDMA NICs. FlexLink provides these improvements as a lossless, drop-in replacement compatible with the NCCL API, ensuring easy adoption. |
| title | FlexLink: Boosting your NVLink Bandwidth by 27% without accuracy concern |
| topic | Hardware Architecture Artificial Intelligence Distributed, Parallel, and Cluster Computing Machine Learning |
| url | https://arxiv.org/abs/2510.15882 |