Cost Model

Cost modeling aims to accurately predict the resource consumption (time, energy, storage) of computational tasks, enabling efficient resource allocation and optimization. Current research focuses on developing accurate and generalizable cost models using machine learning techniques, particularly neural networks, applied to diverse problems including query optimization, path planning, and hardware resource allocation. These models are increasingly employed to improve the efficiency of algorithms and systems across various domains, from database management to deep learning model deployment, leading to significant performance gains and cost reductions. The development of robust, explainable, and zero-shot capable cost models remains a key area of ongoing investigation.