  Traditional cluster designs were originally server-centric, and have evolved
recently to support hardware acceleration and storage disaggregation. In
applications that leverage acceleration, the server CPU performs the role of
orchestrating computation and data movement and data-intensive applications
stress the memory bandwidth. Applications that leverage disaggregation can be
adversely affected by the increased PCIe and network bandwidth resulting from
disaggregation. In this paper, we advocate for a specialized cluster design for
important data intensive applications, such as analytics, query processing and
ML training. This design, Lovelock, replaces each server in a cluster with one
or more headless smart NICs. Because smart NICs are significantly cheaper than
servers on bandwidth, the resulting cluster can run these applications without
adversely impacting performance, while obtaining cost and energy savings.

Distributed, Parallel, and Cluster Computing