Parallel processing involves performing multiple calculations simultaneously by dividing large problems into smaller subproblems that can be solved concurrently. This allows parallel systems to achieve faster execution times using multiple processing elements that perform concurrent data processing. Parallel processing can occur at the instruction level, data level, or both. Common parallel processing architectures include single instruction single data (SISD), single instruction multiple data (SIMD), multiple instruction single data (MISD), and multiple instruction multiple data (MIMD). Pipelining is a technique used in parallel processing where multiple instructions are overlapped in their execution across different functional units of a processor.