Rethinking Polling Efficiency in Service Core Network Stacks

2026-07-17

AI Summary

This work challenges the conventional focus on core utilization in resource management, which often overlooks the practical performance constraints imposed by power and thermal limits in modern multicore processors. Instead, it proposes a new paradigm centered on power budgeting, elevating idle-core waiting strategies to first-class design considerations. Rather than aggressively reclaiming idle cores—a practice that frequently overestimates benefits and incurs substantial scheduling overhead—the approach leverages efficient waiting mechanisms to release redistributable compute capacity. Empirical analysis on AMD EPYC platforms, accounting for processor topology, idle duration, and waiting policies, demonstrates that such strategies achieve a superior trade-off between energy efficiency and performance, offering greater practical advantages in real-world systems.

Abstract

Idle network service cores are treated as wasted compute. This assumption motivates increasingly sophisticated mechanisms that reclaim idle cores at microsecond timescales. We argue that this view no longer matches modern server hardware. On contemporary multicore processors, active cores compete for a shared package level power and thermal budget. Once that budget becomes the limiting resource, an idle core that waits efficiently returns compute capacity that hardware can redistribute to productive work. Measurements on a recent AMD EPYC processor show how waiting strategy, processor topology, and idle duration determine this tradeoff. Our results suggest that reclaiming idle cores often yields less benefit than commonly assumed while introducing substantial scheduling complexity. We propose a budget centric view of service core systems in which power, rather than core occupancy, becomes the fundamental resource and waiting policy becomes a first class systems design choice.

Problem

• polling efficiency
• service core
• power budget
• idle core
• multicore processors

Innovation

• power budget
• idle core efficiency
• waiting policy
• multicore scheduling
• service core network