Hardware PCA for gas identification systems using high level synthesis on the Zynq SoC

Ait Si Ali, Amine, Amira, Abbes, Bensaali, Faycal and Benammar, Mohieddine (2013) Hardware PCA for gas identification systems using high level synthesis on the Zynq SoC. In: 2013 IEEE 20th International Conference on Electronics, Circuits, and Systems (ICECS). IEEE, pp. 707-710. ISBN 978-1-4799-2452-3

Full text not available from this repository.
Official URL: http://dx.doi.org/10.1109/ICECS.2013.6815512


One of the significant stages in a gas identification system is dimensionality reduction to speed up the processing part. This is even more important when the system is implemented on a hardware platform where the resources are limited. This paper presents the design and the implementation of the learning and testing phases of principal component analysis (PCA) that can be used in a gas identification system on the heterogeneous Zynq platform. All steps of PCA starting from the mean computation to the projection of data onto the new space, passing by the normalization process, covariance matrix and the eigenvectors computation are developed in C and synthesized using the new Xilinx VIVADO high level synthesis (HLS). The computation of the eigenvectors was based on the iterative Jacobi method. The designed hardware for computing the learning part of PCA on the Zynq system on chip showed that it can be faster than its 64-bit Intel i7-3770 processor counterpart with a speed up of 1.41. Optimization techniques using HLS directives were also utilised in the hardware implementation of the testing part of the PCA to speed up the design and reduce its latency.

Item Type: Book Section
Subjects: H600 Electronic and Electrical Engineering
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Becky Skoyles
Date Deposited: 23 Jul 2018 14:06
Last Modified: 11 Oct 2019 19:45
URI: http://nrl.northumbria.ac.uk/id/eprint/35086

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