Latest revision as of 17:04, 3 February 2021

Abstract

Processing data received as a stream is a task commonly performed by modern embedded devices, in a wide range of applications such as multimedia (encoding/decoding/ playing media), networking (switching and routing), digital security, scientific data processing, etc. Such processing normally tends to be calculation intensive and therefore requiring significant processing power. Therefore, hardware acceleration methods to increase the performance of such applications constitute an important area of study. In this paper, we present an evaluation of one such method to process streaming data, namely multi-processor pipeline architecture. The hardware is based on a Multiple-Processor System on Chip (MPSoC), using a data encryption algorithm as a case study. The algorithm is partitioned on a coarse grained level and mapped on to an MPSoC with five processor cores in a pipeline, using specifically configured Xtensa LX3 cores. The system is then selectively optimized by strengthening and pruning the resources of each processor core. The optimized system is evaluated and compared against an optimal single-processor System on Chip (SoC) for the same application. The multiple-processor pipeline system for data encryption algorithms used was observed to provide significant speed ups, up to 4.45 times that of the single-processor system, which is close to the ideal speed up from a five-stage pipeline.

Original document

The different versions of the original document can be found in:

• http://arxiv.org/abs/1403.7299

• http://arxiv.org/pdf/1403.7299

• http://xplorestaging.ieee.org/ielx5/6027500/6037376/06038036.pdf?arnumber=6038036,

http://dx.doi.org/10.1109/iciinfs.2011.6038036

• https://dblp.uni-trier.de/db/journals/corr/corr1403.html#NawinneWRR14,

http://yadda.icm.edu.pl/yadda/element/bwmeta1.element.ieee-000006038036,

http://ui.adsabs.harvard.edu/abs/2014arXiv1403.7299N/abstract,

https://arxiv.org/abs/1403.7299,

https://arxiv.org/pdf/1403.7299,

https://ieeexplore.ieee.org/document/6038036,

https://128.84.21.199/abs/1403.7299,

http://export.arxiv.org/abs/1403.7299,

https://academic.microsoft.com/#/detail/2157692219