Accelerating Cross-correlation Applications via Parallel Computing

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Author(s)

M.I. Khalil 1,*

1. Nuclear Research Center, Atomic Energy Authority, Cairo, Egypt

* Corresponding author.

DOI: https://doi.org/10.5815/ijigsp.2013.12.04

Received: 13 Jun. 2013 / Revised: 17 Jul. 2013 / Accepted: 22 Aug. 2013 / Published: 8 Oct. 2013

Index Terms

Signal processing, cross-correlation, parallel computing

Abstract

Software dealing with large-scale signal processing takes long time even on modern hardware. Cross-correlation applications are mostly algorithms rather than data-intensive (that is, they are more CPU-bound than I/O-bound). Parallel implementation of the cross-correlation execution over the local network, or in some cases over a Wide Area Network (WAN), helps reducing the processing time. The aim of this paper is to discuss the possibility of distributing the cross-correlation computational process over the available PCs in the local network. Moreover, the algorithm portion that is sent to a remote PC, within the LAN, will be redistributed over the available CPU cores on that computer yielding to maximum utilization of all available cores in the local area network. The load balancing problem will be addressed as well.

Cite This Paper

M.I. Khalil,"Accelerating Cross-correlation Applications via Parallel Computing", IJIGSP, vol.5, no.12, pp.26-31, 2013. DOI: 10.5815/ijigsp.2013.12.04

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