High Performance Parallel Sort for Shared and Distributed Memory MIMD
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We present four high performance hybrid sorting methods developed for various parallel platforms: shared memory multiprocessors, distributed multiprocessors, and clusters taking advantage of existence of both shared and distributed memory. Merge sort, known for its stability, is used to design several of our algorithms. We improve its parallel performance by combining it with Quicksort. We present two models designed for shared memory MIMD (OpenMP): (a) a non-recursive Merge sort and (b) a hybrid Quicksort and Merge sort. The third model presented is designed for distributed memory MIMD (MPI) using a hybrid Quicksort and Merge sort. Our fourth model is designed to take advantage of the shared memory within individual nodes of todays cluster systems, and to eliminate all internal data transfers between different nodes, Our model implements a one-step MSD-Radix to distribute data in ten packets (MPI) while parallel cores of each node use Quicksort to sort their data partitions sequentially then merge and sort them in parallel employing the OpenMp. The performances of all developed models outperform the baseline performance. Hybrid Quicksort and Merge sort outperformed Hybrid Memory Parallel Merge Sort using Hybrid MSD-Radix and Quicksort in Cluster Platforms when sorting small size data, but with larger data the speedup of Hybrid Memory Parallel Merge Sort Using Hybrid MSD-Radix and Quicksort in Cluster Platforms becomes bigger and it keeps improving. The speedup of Distributed Memory Parallel Hybrid Quicksort and Merge Sort is the best.
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