Tai Chi: A General High-Efficiency Scheduling Framework for SmartNICs in Hyperscale Clouds

Cloud service providers increasingly adopt SmartNICs to offload data-plane services (e.g., DPDK and SPDK) and control-plane tasks (such as disk and NIC initialization). Our analysis of production environments reveals that data-plane services statically provision CPUs for peak load, resulting in 67.5% idle CPU cycles during 99% of their runtime in IaaS clouds, leading to wasted CPU resources. On the other hand, control-plane tasks fail to meet critical Service Level Objectives (SLOs), such as virtual machine startup time. Unfortunately, achieving control-plane SLO improvements through co-scheduling with idle data-plane services remains highly challenging, due to the combined effects of intrinsic scheduling latency and the substantial architectural complexity inherent to control-plane ecosystems.