Abstract

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.

Autore Pugliese

• Epicoco Italo , Aloisio Giovanni , Cafaro Massimo

Tutti gli autori

• Cafaro M. , Pulimeno M. , Epicoco I. , Aloisio G.

Titolo volume/Rivista

CONCURRENCY AND COMPUTATION

Anno di pubblicazione

2017

ISSN

1532-0626

ISBN

Non Disponibile

Numero di citazioni Wos

Nessuna citazione

Ultimo Aggiornamento Citazioni

Non Disponibile

Numero di citazioni Scopus

2

Ultimo Aggiornamento Citazioni

28/04/2018

Settori ERC

Non Disponibile

Codici ASJC

Non Disponibile