👉 Attached computing refers to the distributed processing of data across multiple interconnected computing nodes, which can be physical machines or virtualized environments, to solve complex computational problems more efficiently than a single machine could handle alone. This approach leverages the collective power of these nodes, often spread across different locations or even cloud infrastructures, to perform parallel computations, share resources, and manage data more effectively. By distributing tasks, attached computing enhances scalability, reduces latency, and increases fault tolerance, making it particularly valuable for big data analytics, machine learning, and other resource-intensive applications. This model allows for dynamic allocation of resources based on demand, optimizing performance and cost-efficiency in handling large-scale computational tasks.
