English

dpBento: Benchmarking DPUs for Data Processing

Distributed, Parallel, and Cluster Computing 2025-04-09 v1 Databases

Abstract

Data processing units (DPUs, SoC-based SmartNICs) are emerging data center hardware that provide opportunities to address cloud data processing challenges. Their onboard compute, memory, network, and auxiliary storage can be leveraged to offload a variety of data processing tasks. Although recent work shows promising benefits of DPU offloading for specific operations, a comprehensive view of the implications of DPUs for data processing is missing. Benchmarking can help, but existing benchmark tools lack the focus on data processing and are limited to specific DPUs. In this paper, we present dpBento, a benchmark suite that aims to uncover the performance characteristics of different DPU resources and different DPUs, and the performance implications of offloading a wide range of data processing operations and systems to DPUs. It provides an abstraction for automated performance testing and reporting and is easily extensible. We use dpBento to measure recent DPUs, present our benchmarking results, and highlight insights into the potential benefits of DPU offloading for data processing.

Keywords

Cite

@article{arxiv.2504.05536,
  title  = {dpBento: Benchmarking DPUs for Data Processing},
  author = {Jiasheng Hu and Chihan Cui and Anna Li and Raahil Vora and Yuanfan Chen and Philip A. Bernstein and Jialin Li and Qizhen Zhang},
  journal= {arXiv preprint arXiv:2504.05536},
  year   = {2025}
}