As the demand for information and communication technologies (ICT) continues to rise, the environmental impact of computing systems is becoming an increasingly critical concern. Although newer hardware often improves performance and energy efficiency, these gains do not always offset the carbon cost of premature replacement, particularly under low-utilization workloads or low-carbon electricity grids. We present CarbonSim, a lifecycle-aware simulation framework for evaluating carbon tradeoffs in hardware upgrade decisions. CarbonSim combines workload execution profiles, machine-level power characteristics, embodied carbon inventories, scheduling policies, and time-varying grid carbon intensity to estimate total emissions under alternative deployment scenarios. The framework supports multiple embodied-carbon accounting strategies, including uniform amortization and front-loaded lifecycle attribution, enabling analysis under different hardware lifespan assumptions. Using heterogeneous CPU generations as calibration platforms, we demonstrate that newer machines do not always minimize total emissions: under lightly loaded workloads or cleaner electricity mixes, extending the useful life of existing hardware can reduce lifecycle carbon despite lower operational efficiency. These results highlight that hardware refresh decisions should be workload-aware, location-aware, and lifecycle-aware.

翻译：随着信息与通信技术需求的持续增长，计算系统对环境的影响日益成为关键性问题。尽管新型硬件通常能提升性能与能效，但这些优势并不总能抵消过早更换硬件产生的碳成本，尤其是在低负载工作负载或低碳电力网络场景下。我们提出碳模拟——一个面向硬件升级决策中碳权衡评估的全生命周期感知仿真框架。该框架整合工作负载执行特征、机器级功耗特性、隐含碳库存清单、调度策略及随时间变化的电网碳强度，以估算不同部署方案下的总排放量。框架支持多种隐含碳核算策略，包括均匀摊销与前置型生命周期归因法，可在不同硬件使用寿命假设下进行分析。以异构CPU代际作为校准平台，我们验证了新型设备并非总能最小化总排放量：在轻负载工作负载或更清洁的电力组合条件下，延长现有硬件的使用寿命可减少生命周期碳排放，即便其运行效率较低。这些结果表明，硬件更新决策应具备工作负载感知、地理位置感知与全生命周期感知能力。