Parallel space saving on multi‐ and many‐core processors. (27th April 2017)

• Record Type: Journal Article
• Authors: Cafaro, Massimo; Pulimeno, Marco; Epicoco, Italo; Aloisio, Giovanni
• Other Names: Trunfio Giuseppe A. guestEditor.; Spataro William guestEditor.; Sirakoulis Georgios Ch. guestEditor.
• Is Part Of: Concurrency and computation. Volume 30:Number 7(2018)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2017-04-27
• Subjects: data stream -- frequent items -- multi‐core -- many‐core; Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.4160
• Languages: English
• ISSNs: 1532-0626

Abstract

Summary: Given an array A of n elements and a value 2≤ k ≤ n, a frequent item or k ‐majority element is an element occurring in A more than n / k times. The k ‐majority problem requires finding all of the k ‐majority elements. In this paper, we deal with parallel shared‐memory algorithms for frequent items; we present a shared‐memory version of the Space Saving algorithm, and we study its behavior with regard to accuracy and performance on many and multi‐core processors, including the Intel Phi accelerator. We also investigate a hybrid MPI/OpenMP version against a pure MPI‐based version. Through extensive experimental results, we prove that the MPI/OpenMP parallel version of the algorithm significantly enhances the performance of the earlier pure MPI version of the same algorithm. Results also prove that for this algorithm the Intel Phi accelerator does not introduce any improvement with respect to the Xeon octa–core processor.