Runtime Performance

Runtime performance analysis focuses on evaluating and optimizing the speed and efficiency of computational processes, encompassing diverse applications from robotics and large language models (LLMs) to evolutionary algorithms. Current research emphasizes benchmarking and improving performance across various hardware and software platforms, exploring techniques like quantization, recomputation, and specialized operators for LLMs, and developing non-intrusive monitoring systems for efficient performance tracking in Python-based applications. These advancements are crucial for improving the scalability and reliability of complex systems, enabling faster development cycles and more efficient resource utilization in fields ranging from AI to robotics.