Runtime Optimization

Runtime optimization focuses on improving the efficiency of algorithms and systems by reducing execution time and resource consumption. Current research emphasizes techniques like machine learning to predict optimal configurations (e.g., thread counts in parallel computing), utilitarian algorithm configuration to balance performance and user experience, and leveraging large language models to enhance search-based optimization methods. These advancements are crucial for accelerating scientific computations, improving the performance of resource-constrained devices (like mobile phones), and enabling real-time processing in applications such as medical imaging and speech recognition.