DPUBench: An application-driven scalable benchmark suite for comprehensive DPU evaluation

Abstract

With the development of data centers, network bandwidth has rapidly increased, reaching hundreds of Gbps. However, the network I/O processing performance of CPU improvement has not kept pace with this growth in recent years, which leads to the CPU being increasingly burdened by network applications in data centers. To address this issue, Data Processing Unit (DPU) has emerged as a hardware accelerator designed to offload network applications from the CPU. As a new hardware device, the DPU architecture design is still in the exploration stage. Previous DPU benchmarks are not neutral and comprehensive, making them unsuitable as general benchmarks. To showcase the advantages of their specific architectural features, DPU vendors tend to provide some particular architecture-dependent evaluation programs. Moreover, they fail to provide comprehensive coverage and cannot adequately represent the full range of network applications. To address this gap, we propose an application-driven scalable benchmark suite called DPUBench. DPUBench classifies DPU applications into three typical scenarios — network, storage, and security, and includes a scalable benchmark framework that contains essential Operator Set in these scenarios and End-to-end Evaluation Programs in real data center scenarios. DPUBench can easily incorporate new operators and end-to-end evaluation programs as DPU evolves. We present the results of evaluating the NVIDIA BlueField-2 using DPUBench and provide optimization recommendations. DPUBench are publicly available from https://www.benchcouncil.org/DPUBench.