RDMA Reliability Evaluation Model for Large-Scale Data Center Networks

Abstract

The increasing demand for high-performance storage and machine learning services in data center networks has led to the adoption of RDMA (Remote Direct Memory Access) as a replacement for the traditional TCP protocol stack. To ensure the reliability of RDMA in real-world deployments, it is crucial to perform a comprehensive reliability evaluation before deploying it in a production environment. However, current reliability evaluations of RDMA in data center networks are often limited to small-scale experiments and models, making it difficult to validate the reliability of RDMA in large-scale deployments. To address this issue, we propose a reliability evaluation model for RDMA in large-scale data center networks. The model calculates the reliability of RDMA transmission flows in complex large-scale topologies. Our experiments demonstrate that the model accurately predicts the reliability of RDMA, providing quick and convergent evaluation results on a large scale.