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EnglishPrincipal Component Analysis (PCA) is a widely used approach for dimensionality reduction in image processing. In microwave imaging, for example, it is used as an intermediate step toward image reconstruction. An FPGA hardware implementation of PCA is highly beneficial, especially as an accelerator for a low-cost embedded environment. In this paper we propose a flexible PCA hardware accelerator that can be used for different input data dimensions and input precisions. In addition, it supports both floating-point and fixed-point arithmetic representations. The target hardware is a ZYNQ SoC. We used High Level Synthesis (HLS) to quickly explore the design space and so to find the best implementation for a given setting of the application parameters and given the characteristics of the target hardware. We show the impact on performance of different hardware optimization techniques enabled by HLS. The proposed method outperforms a similar state-of-the-art HLS design in terms of latency and resource usage.
HLS-Based Flexible Hardware Accelerator for PCA Algorithm on a Low-Cost ZYNQ SoC / Mansoori, Mohammadamir; Casu, Mario R.. - ELETTRONICO. - (2019), pp. 1-7. ((Intervento presentato al convegno 2019 IEEE Nordic Circuits and Systems Conference, NORCAS 2019: NORCHIP and International Symposium of System-on-Chip, SoC 2019 tenutosi a Helsinki, Finland nel 29-30 October 2019 [10.1109/NORCHIP.2019.8906893].
| Titolo: | HLS-Based Flexible Hardware Accelerator for PCA Algorithm on a Low-Cost ZYNQ SoC | |
| Autori: | ||
| Data di pubblicazione: | 2019 | |
| Abstract: | Principal Component Analysis (PCA) is a widely used approach for dimensionality reduction in imag...e processing. In microwave imaging, for example, it is used as an intermediate step toward image reconstruction. An FPGA hardware implementation of PCA is highly beneficial, especially as an accelerator for a low-cost embedded environment. In this paper we propose a flexible PCA hardware accelerator that can be used for different input data dimensions and input precisions. In addition, it supports both floating-point and fixed-point arithmetic representations. The target hardware is a ZYNQ SoC. We used High Level Synthesis (HLS) to quickly explore the design space and so to find the best implementation for a given setting of the application parameters and given the characteristics of the target hardware. We show the impact on performance of different hardware optimization techniques enabled by HLS. The proposed method outperforms a similar state-of-the-art HLS design in terms of latency and resource usage. | |
| ISBN: | 978-1-7281-2769-9 | |
| Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
File in questo prodotto:
| File | Descrizione | Tipologia | Licenza | |
|---|---|---|---|---|
| Final.pdf | Main article | 2. Post-print / Author's Accepted Manuscript | PUBBLICO - Tutti i diritti riservati | Visibile a tuttiVisualizza/Apri |
| CameraReady.pdf | Main article | 2a Post-print versione editoriale / Version of Record | Non Pubblico - Accesso privato/ristretto | Administrator Richiedi una copia |
http://hdl.handle.net/11583/2779752
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