The huge data volumes and the emergence of new parallel architectures, e.g. multicore CPUs lead to revisiting classic computer science topics such as in-place sequence rotation. In-place sequence rotation is a basic step in several fundamental computing tasks. The sequential algorithms of the in-place sequence rotation effect are classic and well-studied, which are classified into three classes. Recently, Intel introduced the parallel standard template library (STL) implementation for multicore CPU systems; it has an in-place rotation function based on the rotation by copy, but its space complexity is . In this work, we propose the blend rotation, which is a parallel-friendly and in-place algorithm that combines the merits of these three rotation algorithm classes. Besides, we propose a set of for Parallel In-place SeQuence RoTation (PI-sqrt) implementations. The performance of PI-sqrt is examined through several experiments. To the best of our knowledge, the obtained running times show that the implementations of blend and reversal rotations are by far the fastest parallel implementations; they are faster on average, through different experiments, by 7.85 and 5.52 , respectively, compared to the parallel rotation function of Intel parallel STL.