Abstract
In this work, the influence of the dynamic task scheduling process is examined. Out-of-order (OoO) implementation processes exhibit remarkable guarantee for task-level parallelism in multiprocessor system-on-chip (MPSOC) designs. The superior performance can be attained with the help of a precise mapping of tasks onto the right processors. Hence, to obtain this performance, a SPIDER-based task parallelism is presented in this work. The software related dynamic operations are illustrated on a heterogeneous MPSOC (Ht-MPSOC). SPIDER abides by a cooperative population-based search, which demonstrates upon the social activities of SPIDER grouping. SPIDER system merges local search approaches with global search approaches. This implementation decreases the issue of task management. The performance of the proposed design is compared with the existing work for power, area and speed analysis.
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