Examples of Explicit Parallelism
- Parallel loops: Parallel loops are defined as a construct that allows a loop to be executed in parallel. The sequence and condition of the loops are specified according to which they are executed.
- Message passing: Message passing is a technique that is used to enable communication that takes place between processes and the threads that are running on different processors.
- Data parallelism: Data parallelism is defined as a technique that is used to divide the present large datasets into smaller subsets. These divided subsets can then be processed in parallel.
Difference Between Implicit Parallelism and Explicit Parallelism in Parallel Computing
Implicit Parallelism is defined as a parallelism technique where parallelism is automatically exploited by the compiler or interpreter. The objective of implicit parallelism is the parallel execution of code in the runtime environment. In implicit parallelism, parallelism is being carried out without explicitly mentioning how the computations are parallelized. The compiler assigns the resources to target machines for performing parallel operations. Implicit parallelism requires less programming effort and has applications in shared memory multiprocessors.