Efficient acceleration of complex DSP applications on reconfigurable devices

Στρατάκος, Ιωάννης; Stratakos, Ioannis

dc.contributor.author	Στρατάκος, Ιωάννης	el
dc.contributor.author	Stratakos, Ioannis	en
dc.date.accessioned	2024-08-27T10:14:22Z
dc.date.available	2024-08-27T10:14:22Z
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/60018
dc.identifier.uri	http://dx.doi.org/10.26240/heal.ntua.27714
dc.rights	Default License
dc.subject	Embedded Systems	en
dc.subject	SoC-FPGA	en
dc.subject	Hardware/Software Co-design	en
dc.subject	Hardware Accelerators	en
dc.subject	Digital Signal Processing	en
dc.subject	Ενσωματωμένα Συστήματα	el
dc.subject	Ψηφιακή Επεξεργασία Σήματος	el
dc.subject	Επιταχυντές Υλικού	el
dc.subject	Συ-σχεδιασμός Υλικού/Λογισμικού	el
dc.title	Efficient acceleration of complex DSP applications on reconfigurable devices	en
dc.title	Αποτελεσματική επιτάχυνση πολύπλοκων εφαρμογών ψηφιακής επεξεργασίας σημάτων σε επαναδιαμορφώσιμες συσκευές	el
dc.contributor.department	Microprocessors and Digital Systems Lab	el
heal.type	doctoralThesis
heal.secondaryTitle	Platform and Architecture Optimizations	en
heal.secondaryTitle	Βελτιστοποιήσεις Πλατφόρμας και Αρχιτεκτονικής	el
heal.classification	Computer Engineering	en
heal.language	en
heal.access	campus
heal.recordProvider	ntua	el
heal.publicationDate	2023-12-15
heal.abstract	In recent years, there has been a remarkable surge in the field of embedded systems, especially in the consumer electronics sector. The growing demand for high-performance and energy-efficient systems has motivated researchers to come up with innovative design techniques to meet these challenging requirements. Among various aspects, streaming Digital Signal Processing (DSP) has gained particular attention, involving complex mathematical computations such as matrix inversions, filtering, and basic arithmetic operations. As DSP continues to gain importance in various devices, certain factors like time-to-market and flexibility for late design changes have become critical considerations. Software-based solutions provide flexibility and the ability to make adjustments even in the later stages, but they often lag behind hardware in terms of performance due to the limitations of serial processing. On the other hand, developing custom Application-Specific Integrated Circuits (ASICs) can be a time-consuming process and lacks reconfigurability once the fabrication is completed. This dissertation revolves around accelerating demanding and complex digital signal processing applications on re-configurable devices, with a particular emphasis on SoC-FPGAs. The applications covered in this research span two domains: image/video processing and telecommunications. In the image/video processing domain, the main focus is on accelerating 1) Medical Imaging and 2) Vision-based navigation applications for space deployments. In the telecom domain, the research centers on low-level physical layer processing, specifically targeting the next-generation 5G/B5G mobile networks. These applications share common characteristics, requiring strict adherence to latency requirements while keeping power consumption at a minimum. To achieve these objectives, extensive Design Space Exploration (DSE) is carried out, and advanced design techniques are employed. The utilization of the unique features of the underlying SoC-FPGA device further enhances the effectiveness of the proposed solutions.	en
heal.advisorName	Σούντρης, Δημήτριος	el
heal.advisorName	Soudris, Dimitrios	en
heal.committeeMemberName	Soudris, Dimitrios	en
heal.committeeMemberName	Pekmestzi, Kiamal	en
heal.committeeMemberName	Reisis, Dionysios	en
heal.committeeMemberName	Avramopoulos, Hercules	en
heal.committeeMemberName	Panagopoulos, Athanasios D.	en
heal.committeeMemberName	Pleros, Nikolaos	en
heal.committeeMemberName	Xydis, Sotirios
heal.committeeMemberName	Αβραμόπουλος, Ηρακλής	el
heal.committeeMemberName	Παναγόπουλος, Αθανάσιος	el
heal.committeeMemberName	Πλερός, Νικόλαος	el
heal.committeeMemberName	Ξύδης, Σωτήριος	el
heal.academicPublisher	Εθνικό Μετσόβιο Πολυτεχνείο. Σχολή Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών.	el
heal.academicPublisherID	ntua
heal.numberOfPages	214 σ.	el
heal.fullTextAvailability	false