How does Julia handle parallel computing?

Julia supports parallelism via multi-threading, distributed computing, and GPU acceleration.

Julia provides multiple concurrency models: multi-threading for shared-memory parallelism, distributed computing via multiple processes, and GPU programming via packages like CUDA.jl. The language is designed to minimize overhead in parallel execution by avoiding global interpreter locks and enabling fine-grained task scheduling.