👉 Worker computing refers to the process where specialized machines, typically high-performance computers or GPUs, are utilized to perform computational tasks in parallel, often for complex and data-intensive applications such as machine learning, deep learning, and scientific simulations. These workers are part of a distributed computing system where multiple nodes work together to solve problems more efficiently than a single machine could. Each worker processes parts of the data or computations independently, and their results are combined to produce a final output. This approach leverages the collective power of many machines, significantly reducing computation time and enabling the handling of large-scale problems that would be infeasible for a single machine to manage.
