  Improving the performance and reducing the cost of cloud data systems is
increasingly challenging. Data processing units (DPUs) are a promising
solution, but utilizing them for data processing needs characterizing the new
hardware and recognizing their capabilities and constraints. We hence propose
DPDPU, a platform for holistically exploiting DPUs to optimize data processing
tasks that are critical to performance and cost. It seeks to fill 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.
