A framework for the integration of the development process of Linux FPGA System on Chip devices

Rigoni, A.; Manduchi, G.; Luchetta, A.; Taliercio, C.; Schröder, T.

doi:10.1016/j.fusengdes.2018.01.042

Cited by 8 publications

(4 citation statements)

References 10 publications

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“…The XILINX Vivado Integrated Development Environment (IDE) [ 16 ] and the ANACLETO framework [ 17 ] for orchestrating the toolchain in the project are used to generate the FPGA configuration. The FPGA definition is composed of several modules written in the VHDL Hardware Description Language and connected with other available Intellectual Properties (IP) cores.…”

Section: Architecturementioning

confidence: 99%

A Versatile Board for Event-Driven Data Acquisition

Manduchi,

Rigoni,

Trevisan

et al. 2024

Sensors

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Event-driven data acquisition is used to capture information from fast transient phenomena typically requiring a high sampling speed. This is an important requirement in the ITER Neutral Beam Test Facility for the development of one of the heating systems of the ITER nuclear fusion experiment. The Red Pitaya board has been chosen for this project because of its versatility and low cost. Versatility is provided by the hosted Zynq System on Chip (SoC), which allows full configuration of the module architecture and the OpenSource architecture of Red Pitaya. Price is an important factor, because the boards are installed in a hostile environment where devices can be damaged by EMI and radiation. A flexible solution for event-driven data acquisition has been developed in the Zynq SoC and interfaced to the Linux-based embedded ARM processor. It has been successfully adopted in a variety of data acquisition applications in the test facility.

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Section: Architecturementioning

confidence: 99%

A Versatile Board for Event-Driven Data Acquisition

Manduchi,

Rigoni,

Trevisan

et al. 2024

Sensors

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“…The LBs in the periphery are connected to the input/output blocks (IOB) to enable the FPGA to communicate with an external device. FPGA are normally used to implement applications with an embedded microprocessor [ 4 ] and/or applications with dedicated processing [ 5 , 6 ].…”

Section: Reconfigurable Electronics Platformsmentioning

confidence: 99%

Reconfigurable Electronic Platforms: A Top-Down Approach to Learn about Design and Integration of Electronic Systems

et al. 2022

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This case report presents a real example of a study which introduces the use of reconfigurable platforms in the teaching of electronics engineering to establish a bridge between theory and practice. This gap is one of the major concerns of the electronics engineering students. Different strategies, such as simulation tools or breadboard implementations, have been followed so far to make it easier for students to practice what they study in lectures. However, many students still claim to have problems when they face real practical implementations. The use of reconfigurable platforms as a teaching tool is proposed to provide the students the possibility of fast experimentation, reducing both development time and the learning curve. In addition, reconfigurable platforms available on the market make this methodology suitable to be applied throughout the different courses of their curricula. The feasibility of this approach is demonstrated in a course at the M.Eng. level, where the objective is the study, design and development of electronic sensor nodes. We firmly consider, based on the students’ results and reflections collected during the course, that this methodology helps students to address the theoretical framework from a practical viewpoint, as well as to acquire some of the fundamental skills for their professional careers, such as the usage of communication protocols and embedded systems programming, in a more intuitive way when compared to traditional teaching methodologies.

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“…A good candidate architecture has been found in the embedded boards equipped with SoC units that share a arm processing unit with a FPGA logic: the Xilinx Zynq 7k for instance. These boards match the optimal balance of flexibility, performance and costs required by our experiment and we are already planning to integrate them in the main stream of the acquisition system in RFX-mod2 [18], [19].…”

Section: A Proof-of-concept Implementation: Low Precision Fpga Deploy...mentioning

confidence: 99%

Diagnostic data integration using deep neural networks for real-time plasma analysis

Garola,

Cavazzana,

Gobbin

et al. 2020

Preprint

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Recent advances in acquisition equipment is providing experiments with growing amounts of precise yet affordable sensors. At the same time an improved computational power, coming from new hardware resources (GPU, FPGA, ACAP), has been made available at relatively low costs. This led us to explore the possibility of completely renewing the chain of acquisition for a fusion experiment, where many high-rate sources of data, coming from different diagnostics, can be combined in a wide framework of algorithms. If on one hand adding new data sources with different diagnostics enriches our knowledge about physical aspects, on the other hand the dimensions of the overall model grow, making relations among variables more and more opaque. A new approach for the integration of such heterogeneous diagnostics, based on composition of deep variational autoencoders, could ease this problem, acting as a structural sparse regularizer. This has been applied to RFX-mod experiment data, integrating the soft X-ray linear images of plasma temperature with the magnetic state.However to ensure a real-time signal analysis, those algorithmic techniques must be adapted to run in well suited hardware. In particular it is shown that, attempting a quantization of neurons transfer functions, such models can be modified to create an embedded firmware. This firmware, approximating the deep inference model to a set of simple operations, fits well with the simple logic units that are largely abundant in FPGAs. This is the key factor that permits the use of affordable hardware with complex deep neural topology and operates them in real-time.

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A framework for the integration of the development process of Linux FPGA System on Chip devices

Cited by 8 publications

References 10 publications

A Versatile Board for Event-Driven Data Acquisition

A Versatile Board for Event-Driven Data Acquisition

Reconfigurable Electronic Platforms: A Top-Down Approach to Learn about Design and Integration of Electronic Systems

Diagnostic data integration using deep neural networks for real-time plasma analysis

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