Heterogeneous systems-on-chip (HeSoC) based on reconfigurable accelerators, such as Field-Programmable Gate Arrays (FPGA), represent an appealing option to deliver the performance/Watt required by the advanced perception and localization tasks employed in the design of Autonomous Vehicles. Different from software-programmed GPUs, FPGA development involves significant hardware design effort, which in the context of HeSoCs is further complicated by the system-level integration of HW and SW blocks. High-Level Synthesis is increasingly being adopted to ease hardware IP design, allowing engineers to quickly prototype their solutions. However, automated tools still lack the required maturity to efficiently build the complex hard-ware/software interaction between the host CPU and the FPGA accelerator(s). In this paper we present a fully integrated system design where a particle filter for LiDAR-based localization is efficiently deployed as FPGA logic, while the rest of the compute pipeline executes on programmable cores. This design constitutes the heart of a fully-functional 1/10th-scale racing autonomous car. In our design, accelerated IPs are controlled locally to the FPGA via a proxy core. Communication between the two and with the host CPU happens via shared memory banks also implemented as FPGA IPs. This allows for a scalable and easy-to-deploy solution both from the hardware and software viewpoint, while providing better performance and energy efficiency compared to state-of-the-art solutions.

An FPGA Overlay for Efficient Real-Time Localization in 1/10th Scale Autonomous Vehicles / Bernardi, A.; Brilli, G.; Capotondi, A.; Marongiu, A.; Burgio, P.. - (2022), pp. 915-920. ((Intervento presentato al convegno 2022 Design, Automation and Test in Europe Conference and Exhibition, DATE 2022 tenutosi a Virtual, Online nel 14 - 23 March 2022 [10.23919/DATE54114.2022.9774517].

An FPGA Overlay for Efficient Real-Time Localization in 1/10th Scale Autonomous Vehicles

Capotondi A.;Marongiu A.;Burgio P.
2022

Abstract

Heterogeneous systems-on-chip (HeSoC) based on reconfigurable accelerators, such as Field-Programmable Gate Arrays (FPGA), represent an appealing option to deliver the performance/Watt required by the advanced perception and localization tasks employed in the design of Autonomous Vehicles. Different from software-programmed GPUs, FPGA development involves significant hardware design effort, which in the context of HeSoCs is further complicated by the system-level integration of HW and SW blocks. High-Level Synthesis is increasingly being adopted to ease hardware IP design, allowing engineers to quickly prototype their solutions. However, automated tools still lack the required maturity to efficiently build the complex hard-ware/software interaction between the host CPU and the FPGA accelerator(s). In this paper we present a fully integrated system design where a particle filter for LiDAR-based localization is efficiently deployed as FPGA logic, while the rest of the compute pipeline executes on programmable cores. This design constitutes the heart of a fully-functional 1/10th-scale racing autonomous car. In our design, accelerated IPs are controlled locally to the FPGA via a proxy core. Communication between the two and with the host CPU happens via shared memory banks also implemented as FPGA IPs. This allows for a scalable and easy-to-deploy solution both from the hardware and software viewpoint, while providing better performance and energy efficiency compared to state-of-the-art solutions.
2022 Design, Automation and Test in Europe Conference and Exhibition, DATE 2022
Virtual, Online
14 - 23 March 2022
915
920
Bernardi, A.; Brilli, G.; Capotondi, A.; Marongiu, A.; Burgio, P.
An FPGA Overlay for Efficient Real-Time Localization in 1/10th Scale Autonomous Vehicles / Bernardi, A.; Brilli, G.; Capotondi, A.; Marongiu, A.; Burgio, P.. - (2022), pp. 915-920. ((Intervento presentato al convegno 2022 Design, Automation and Test in Europe Conference and Exhibition, DATE 2022 tenutosi a Virtual, Online nel 14 - 23 March 2022 [10.23919/DATE54114.2022.9774517].
File in questo prodotto:
File Dimensione Formato  
An_FPGA_Overlay_for_Efficient_Real-Time_Localization_in_1_10th_Scale_Autonomous_Vehicles.pdf

non disponibili

Tipologia: Versione dell'editore (versione pubblicata)
Dimensione 1.12 MB
Formato Adobe PDF
1.12 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

Caricamento pubblicazioni consigliate

Licenza Creative Commons
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11380/1280824
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? ND
social impact