👉 Clearance computing is an architectural approach designed to enhance the efficiency and performance of data processing systems, particularly in cloud environments. It involves the strategic placement of computing resources, such as CPUs, GPUs, and specialized accelerators, in a manner that optimizes data locality and minimizes communication overhead between different parts of the system. By aligning workloads with the physical proximity of data storage and processing units, clearance computing reduces latency and improves throughput. This is achieved through techniques like data-aware scheduling, where tasks are assigned to nodes based on their proximity to the required data, and dynamic resource allocation, which adjusts resources in real-time based on workload demands. This approach not only boosts computational efficiency but also enhances energy efficiency and reduces operational costs, making it particularly valuable in large-scale distributed systems.
