In computer architecture, a pipeline is associated with instruction-level parallelism in which multiple instructions can be processed simultaneously. As the computing landscape moves toward data-intensive tasks, there is a need for higher throughput of data processing. This is known as data-level parallelism (DLP).
The following lesson will explore data-level parallelism by:
- Defining three DLP approaches
- Connecting how DLP approaches influence each other
- Exploring the hardware implementations of each application
While things like big data and advanced machine learning algorithms are still relatively new, data-level parallelism has been around for a while. Its evolution has been influenced by research as well as industrial, corporate and consumer needs. The data-parallelism landscape is currently changing and it is important to know how it began and where it is going. Have fun and enjoy the lesson!
Go to the next exercise to start exploring data-level parallelism!