👉 Lee computing is an architectural paradigm that focuses on the integration of heterogeneous computing resources, such as CPUs, GPUs, FPGAs, and specialized accelerators, into a unified system to optimize performance and energy efficiency. It emphasizes the dynamic allocation of tasks to these diverse processing units based on their strengths, enabling efficient parallel processing and real-time data handling. By leveraging the unique capabilities of each component, Lee computing aims to overcome traditional bottlenecks associated with data movement and synchronization, thereby enhancing the overall computational throughput and flexibility. This approach is particularly beneficial in applications requiring high-speed data processing, such as artificial intelligence, machine learning, and real-time analytics, where the ability to adaptively utilize available resources can significantly improve performance and reduce power consumption.
