CPU Pinning Impact on Performance and Power Consumption of Mixed Workloads at Edge

Telecoms operators are increasingly adopting principles of cloudification and virtualisation to optimise the delivery of existing services, while leveraging features of flexibility and elasticity to unlock value from new services. The extension of cloud infrastructure to deeper edge locations creates a challenge around optimal workload placement. One of the major issues to address is how to handle diverse and competing workload types – processor and memory hungry applications on the one hand, versus network-oriented applications on the other – within a resource-constrained edge compute footprint. While aiming to drive maximal performance, it is crucial to understand power consumption ramifications. This paper explores some fundamental performance and power tradeoffs linked to the placement of workloads across a dual socket edge server via CPU pinning in different ways. By devising a range of experimental test scenarios for distinct workload types, we reveal key insights. In one example, pinned placement of a process-intensive singleton workload using cores across sockets achieves 28% improved performance, but at the expense of 89W extra power consumption. In another example, pinned placement of workloads that are part of a service chain achieves 66% better performance and a power reduction of 11.4W when pinned to the same socket, rather than cross socket. Key insights such as these can inform either a rudimentary approach to workload placement based on heuristics or can provide the foundation for a more intelligence-based and automated approach.