In the face of growing performance and energy-conservation
demands, the industry moves towards dedicated hardware for
demanding workloads such as networking and AI. One in-
stance of this trend is the use of data-processing units (DPUs)
in datacenters: NVIDIA BlueField, AWS Nitro, and Azure
Boost exemplify a widening trend.

So far, development on DPUs involves the use of low-level
APIs with little abstraction from the underlying hardware,
spreading application logic across many different C callback
functions. This approach is cumbersome and error-prone.

We introduce SHOC, a simpler-to-use programming model
for DPUs built around C++20 coroutines. This paper explains
the model, how to implement it, and demonstrates that its high
level of abstraction can be achieved with negligible perfor-
mance overhead.