HeteroPod: XPU-Accelerated Infrastructure Offloading for Commodity Cloud-Native Applications
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866915219223085056 |
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| author | Yang, Bicheng He, Jingkai Du, Dong Xia, Yubin Chen, Haibo |
| author_facet | Yang, Bicheng He, Jingkai Du, Dong Xia, Yubin Chen, Haibo |
| contents | Cloud-native systems increasingly rely on infrastructure services (e.g., service meshes, monitoring agents), which compete for resources with user applications, degrading performance and scalability. We propose HeteroPod, a new abstraction that offloads these services to Data Processing Units (DPUs) to enforce strict isolation while reducing host resource contention and operational costs. To realize HeteroPod, we introduce HeteroNet, a cross-PU (XPU) network system featuring: (1) split network namespace, a unified network abstraction for processes spanning CPU and DPU, and (2) elastic and efficient XPU networking, a communication mechanism achieving shared-memory performance without pinned resource overhead and polling costs. By leveraging HeteroNet and the compositional nature of cloud-native workloads, HeteroPod can optimally offload infrastructure containers to DPUs. We implement HeteroNet based on Linux, and implement a cloud-native system called HeteroK8s based on Kubernetes. We evaluate the systems using NVIDIA Bluefield-2 DPUs and CXL-based DPUs (simulated with real CXL memory devices). The results show that HeteroK8s effectively supports complex (unmodified) commodity cloud-native applications (up to 1 million LoC) and provides up to 31.9x better latency and 64x less resource consumption (compared with kernel-bypass design), 60% better end-to-end latency, and 55% higher scalability compared with SOTA systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_23952 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | HeteroPod: XPU-Accelerated Infrastructure Offloading for Commodity Cloud-Native Applications Yang, Bicheng He, Jingkai Du, Dong Xia, Yubin Chen, Haibo Operating Systems Cloud-native systems increasingly rely on infrastructure services (e.g., service meshes, monitoring agents), which compete for resources with user applications, degrading performance and scalability. We propose HeteroPod, a new abstraction that offloads these services to Data Processing Units (DPUs) to enforce strict isolation while reducing host resource contention and operational costs. To realize HeteroPod, we introduce HeteroNet, a cross-PU (XPU) network system featuring: (1) split network namespace, a unified network abstraction for processes spanning CPU and DPU, and (2) elastic and efficient XPU networking, a communication mechanism achieving shared-memory performance without pinned resource overhead and polling costs. By leveraging HeteroNet and the compositional nature of cloud-native workloads, HeteroPod can optimally offload infrastructure containers to DPUs. We implement HeteroNet based on Linux, and implement a cloud-native system called HeteroK8s based on Kubernetes. We evaluate the systems using NVIDIA Bluefield-2 DPUs and CXL-based DPUs (simulated with real CXL memory devices). The results show that HeteroK8s effectively supports complex (unmodified) commodity cloud-native applications (up to 1 million LoC) and provides up to 31.9x better latency and 64x less resource consumption (compared with kernel-bypass design), 60% better end-to-end latency, and 55% higher scalability compared with SOTA systems. |
| title | HeteroPod: XPU-Accelerated Infrastructure Offloading for Commodity Cloud-Native Applications |
| topic | Operating Systems |
| url | https://arxiv.org/abs/2503.23952 |