lru cache

**LRU Cache** is **an eviction strategy that removes the least recently used entry first** - It is a core method in modern semiconductor AI serving and inference-optimization workflows. **What Is LRU Cache?** - **Definition**: an eviction strategy that removes the least recently used entry first. - **Core Mechanism**: Recency-based heuristics approximate future reuse likelihood for many access patterns. - **Operational Scope**: It is applied in semiconductor manufacturing operations and AI-agent systems to improve autonomous execution reliability, safety, and scalability. - **Failure Modes**: Pure recency can underperform when access is bursty or periodic. **Why LRU Cache Matters** - **Outcome Quality**: Better methods improve decision reliability, efficiency, and measurable impact. - **Risk Management**: Structured controls reduce instability, bias loops, and hidden failure modes. - **Operational Efficiency**: Well-calibrated methods lower rework and accelerate learning cycles. - **Strategic Alignment**: Clear metrics connect technical actions to business and sustainability goals. - **Scalable Deployment**: Robust approaches transfer effectively across domains and operating conditions. **How It Is Used in Practice** - **Method Selection**: Choose approaches by risk profile, implementation complexity, and measurable impact. - **Calibration**: Combine LRU with frequency or TTL guards for mixed workload behavior. - **Validation**: Track objective metrics, compliance rates, and operational outcomes through recurring controlled reviews. LRU Cache is **a high-impact method for resilient semiconductor operations execution** - It is a simple baseline policy for practical cache management.