👉 Rays computing is an innovative approach to distributed computing that leverages the power of multiple geographically dispersed data centers, often referred to as "rays," to process and analyze large datasets in parallel. Each ray operates independently, performing computations on a subset of the data, and communicates with neighboring rays to aggregate results. This decentralized architecture enhances scalability, fault tolerance, and data locality, significantly reducing latency and improving overall system efficiency. By distributing the computational load across these rays, Rays computing can handle massive data volumes and complex tasks more effectively than traditional centralized systems, making it particularly suitable for big data analytics, machine learning, and real-time processing applications.
