Data-Level Parallelism (DLP) refers to a computing paradigm where multiple data elements are processed simultaneously. This approach is commonly used in applications that involve large datasets, such as image processing or scientific simulations, allowing for faster computation by dividing tasks across multiple processing units. In DLP, operations are performed on different pieces of data at the same time, rather than sequentially. This is often achieved through the use of vector processors or graphics processing units (GPUs), which are designed to handle multiple operations in parallel, significantly improving performance and efficiency in data-intensive tasks.