Energy Implications of Mitigating Side-Channel Attacks on Branch Prediction

Spectre variants 1 and 2 pose grave security threats to dynamic branch predictors in modern CPUs. While extensive research has focused on mitigating these attacks, little attention has been given to their energy and power implications. This study presents an empirical analysis of how compiler-based Spectre mitigation techniques influence energy consumption. We collect fine-grained energy readings from an HPC-class CPU via embedded sensors, allowing us to quantify the trade-offs between security and power efficiency. By utilizing a standard suite of microbenchmarks, we evaluate the impact of Spectre mitigations across three widely used compilers, comparing them to a no-mitigation baseline. The results show that energy consumption varies significantly depending on the compiler and workload characteristics. Loop unrolling influences power consumption by altering branch distribution, while speculative execution, when unrestricted, plays a role in conserving energy. Since Spectre mitigations inherently limit speculative execution, they should be applied selectively to vulnerable code patterns to optimize both security and power efficiency. Unlike previous studies that primarily focus on security effectiveness, this work uniquely evaluates the energy costs associated with Spectre mitigations at the compiler level, offering insights for power-efficient security strategies. Our findings underscore the importance of tailoring mitigation techniques to application needs, balancing performance, energy consumption, and security. The study provides practical recommendations for compiler developers to build more secure and energy-efficient software.