[en] The current interest in moving the bulk of the computing of a multitude of applications to the edge (Edge Computing), particularly in systems based on Artificial Intelligence and Machine Learning (AI/ML), responds to the need to ensure real-time response and security of systems in case of information leakage, requirements that Cloud Computing cannot satisfy. ADAS systems are a growing field of application that responds to this demand, with very demanding requirements in terms of cost, consumption, speed and security, which a system at the edge can satisfy. This work is part of a research proyect about the applicability of hyperspectral imaging to improve the performance and robustness of ADAS. Specifically, different options of open license microprocessor IPs are studied for the design of SoCs (System-On-Chip) on low/mid-range FPGAs with application to hyperspectral image processing.As an alternative to "Softcore" microprocessors, a SoC based on a "Hardcore" microprocessor, in particular a Xilinx PSoC of the Zynq-7000 Family, has also been studied. First, the work characterizes the performance of the analyzed microprocessors on an image preprocessing task required on 25-band snapshot-type hyperspectral cameras with mosaic filtering. Secondly, a generic SoC architecture with DMAs is used to analyze the optimal way to transfer information between the different IP Cores that make up the design and the external memory. During the development of the work, several open source design tools used in the synthesis/simulation/verification of HDL designs have also been explored as an alternative to more widely deployed commercial tools.

[eu] Egun, aplikazio ugarien konputazio-zamak ertzera eramateko (Edge Computing) interes handia dago, bereziki Adimen Artifizialean eta Machine Learning-ean (AA/ML) oinarritutako sistemetan. Joera horren arrazoi nagusia informazio-ihesak ekiditea, segurtasuna bermatzea eta sistemen denbora errealeko erantzuna bermatzea dira, hodeian konputatzeak (Cloud Computing) ezin bai ditu baldintza horiek bete. Gidatzen laguntzeko sistema aurreratuak edo ADAS (Advanced Driving Assistance Systems) gero eta aplikazio-eremu garrantzitsuagoa da, eta eskari horiei erantzun behar dioten sistemak garatzea eskatzen du, oso eskakizun zorrotzak bai dituzte kostuari, kontsumoari, abiadurari eta segurtasunari dagokienez. Lan hau ADASen prestazioak eta sendotasuna hobetzeko irudi hiper-espektralen aplikagarritasuna ikertzen duen proiektu baten parte da. Zehazki, gama baxu/ertaineko FPGAtan irudi hiper-espektralak prozesatzeko SoCak (System–On-Chip) gauzatzeko lizentzia irekiko mikroprozesadoreen IPen hainbat aukera aztertzen dira. Nukleo "bigun" edo softcore mikroprozesadoreen alternatiba gisa, nukleo zurrun edo hardcore mikroprozesadorean oinarritutako SoC bat ere aztertu da, zehazki Zynq-7000 familiako Xilinxen PSoC bat. Lehenik eta behin, lana honek analizatutako mikroprozesadoreen errendimendua ezaugarritzen du mosaiko iragazkia duten snapshot motako 25 bandako kamera hiper-espektraletan beharrezkoa den irudien aurre-prozesamenduko ataza batean. Bigarrenik, DMAak dituen SoC generikoko arkitektura bat erabili egin da kanpoko memoria eta sistema osatzen duten IP nukleo desberdinen artean informazioa transferitzeko modurik egokiena aztertzeko. Lana garatu bitartean, HDL diseinuen sintesian/simulazioan/egiaztapenean erabiltzen diren kode irekiko diseinu-tresnak ere aztertu dira, ezarpen handieneko tresna komertzialen alternatiba gisa.