👉 Seed computing is a distributed computing model where a small set of pre-initialized data, known as seeds, is used to start the computation process. These seeds are typically chosen based on specific criteria such as geographic location, time, or user preferences, and they serve as the foundation for generating a large volume of computational tasks. When these seeds are fed into a computing framework, they trigger the execution of various algorithms or services, leading to the creation of numerous parallel tasks. This approach allows for efficient resource utilization and scalability, as the seeds can be distributed across multiple computing nodes, enabling parallel processing and faster task completion. Seed computing is particularly useful in scenarios requiring high computational power, such as data analytics, machine learning, and large-scale simulations.
