Information Retrieval (IR) systems often must manage large-scale datasets while requiring efficient response times. This paper presents a summary of optimization techniques aimed at improving performance and scalability in IR algorithms. We explore methods such as parallel processing, memory hierarchy optimizations, and GPU acceleration. Our analysis identifies key factors influencing the effectiveness of these optimizations, including workload adaptability and hardware constraints. We also discuss the challenges of implementing these techniques and their impact on modern IR pipelines.
Bocces et al. (Wed,) studied this question.