The AXIOM platform is built with, in mind, the possibility of executing an application not only on a single board but also, in a distributed fashion, on multiple boards. While this is a classic problem with some solutions in the case of no constraints, it becomes interesting for embedded computing and cyber-physical systems where we aim to accelerate applications while maintaining energy efficency and also easy programmability. Currently, the AXIOM platform consists of a custom board based on the Xilinx Zynq Ultrascale+ ZU9EG which incorporates the largest FPGA avaialable on that System-on-Chip at the moment, four 64-bit ARM cores and two 32-bit ARM cores, up to 32GiB of main memory and several 12.5Gbit/s tranceivers. We relyed on this hardware to develop our novel concept, which exploits dataflow execution in multiple ways for programs that are written in an OpenMP extension, known as OmpSs. A key aspect relates to the adopted memory consistency model, which allows the programmer to focus on aspects other than taking care of the communication among nodes. The lower level of our communication stack relies on a fast interconnect based on inexpensive USB-C type connectors rather than on other proprietary interfaces. The reconfigurable logic provides a complete Network Interface Card (NIC) to allow fast routing of the data and code of the system. We envision many applications for this platform although we are currently focused on developing two basic scenarios based on the Smart-Home and on Smart-Videosurveillance. Our initial results confirm good scalability of the platform and a speed-up compared to other programming models such as Cilk and OpenMPI.

Giorgi, R. (2017). AXIOM: A 64-bit reconfigurable hardware/software platform for scalable embedded computing. In 2017 6th Mediterranean Conference on Embedded Computing, MECO 2017 - Including ECYPS 2017, Proceedings (pp.113-116). New York : IEEE [10.1109/MECO.2017.7977173].

AXIOM: A 64-bit reconfigurable hardware/software platform for scalable embedded computing

Giorgi, R.
2017-01-01

Abstract

The AXIOM platform is built with, in mind, the possibility of executing an application not only on a single board but also, in a distributed fashion, on multiple boards. While this is a classic problem with some solutions in the case of no constraints, it becomes interesting for embedded computing and cyber-physical systems where we aim to accelerate applications while maintaining energy efficency and also easy programmability. Currently, the AXIOM platform consists of a custom board based on the Xilinx Zynq Ultrascale+ ZU9EG which incorporates the largest FPGA avaialable on that System-on-Chip at the moment, four 64-bit ARM cores and two 32-bit ARM cores, up to 32GiB of main memory and several 12.5Gbit/s tranceivers. We relyed on this hardware to develop our novel concept, which exploits dataflow execution in multiple ways for programs that are written in an OpenMP extension, known as OmpSs. A key aspect relates to the adopted memory consistency model, which allows the programmer to focus on aspects other than taking care of the communication among nodes. The lower level of our communication stack relies on a fast interconnect based on inexpensive USB-C type connectors rather than on other proprietary interfaces. The reconfigurable logic provides a complete Network Interface Card (NIC) to allow fast routing of the data and code of the system. We envision many applications for this platform although we are currently focused on developing two basic scenarios based on the Smart-Home and on Smart-Videosurveillance. Our initial results confirm good scalability of the platform and a speed-up compared to other programming models such as Cilk and OpenMPI.
2017
978-1-5090-6743-5
978-1-5090-6742-8
Giorgi, R. (2017). AXIOM: A 64-bit reconfigurable hardware/software platform for scalable embedded computing. In 2017 6th Mediterranean Conference on Embedded Computing, MECO 2017 - Including ECYPS 2017, Proceedings (pp.113-116). New York : IEEE [10.1109/MECO.2017.7977173].
File in questo prodotto:
File Dimensione Formato  
07977173.pdf

non disponibili

Tipologia: PDF editoriale
Licenza: NON PUBBLICO - Accesso privato/ristretto
Dimensione 257.02 kB
Formato Adobe PDF
257.02 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11365/1011357