Abstract

Improving the performance and reducing the cost of cloud data systems is increasingly challenging. Data processing units (DPUs) are a promising solution. We characterize their capabilities and constraints. We then propose DPDPU, a platform for holistically exploiting DPUs to optimize data processing tasks that are critical to performance and cost. It seeks to �ll the semantic gap between DPUs and data processing systems and handle DPU heterogeneity with three engines dedicated to compute, networking, and storage. This paper describes our vision, DPDPU’s key components, their associated utilization challenges, as well as the current progress and future plans.