Parallel computing emerges as a promising strategy to address the computational demands of numerous present and evolving applications. It involves the simultaneous execution of multiple tasks across multiple processors, with the primary aim of enhancing computational speed. Efficient task scheduling and mapping pose significant challenges in homogeneous and heterogeneous parallel computing environments. This paper explores various algorithm classes tailored for homogeneous and heterogeneous processors and delves into the roles and significance of performance parameters.