High-accuracy and video-rate lifetime extraction from time correlated single photon counting data on a graphical processing unit

Margara, Alessandro; Peronio, Pietro; Acconcia, Giulia; Cugola, Gianpaolo; Rech, Ivan

doi:10.1063/1.5115349

Cited by 6 publications

(2 citation statements)

References 26 publications

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“…Additionally, IoT sensors facilitate predictive maintenance practices, extending the lifespan of assets and reducing the environmental footprint of manufacturing processes by minimizing downtime (Davenport, 2018, pp. 73–75; Margara et al, 2019). And also the integration of data analytics into Industry 4.0 further strengthens sustainability endeavors.…”

Section: Theoretical Frameworkmentioning

confidence: 99%

Industry 4.0 and sustainable business models: An intercontinental sample

Kılıç,

Atilla

2023

Bus Strat Env

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In the rapidly evolving contemporary business landscape, the Industry 4.0 revolution has emerged as an immense and transformative force, fundamentally reshaping industries and presenting significant challenges to prevailing business models. As technology components continued to evolve in response to this revolution, it became increasingly evident that understanding the multifaceted implications of these changes for organizational sustainability is of paramount importance. The overarching goal of this research was to elucidate the intricate interplay between Industry 4.0 technologies and organizational sustainability. To achieve this objective, we conducted a comprehensive exploration of real‐world instances where companies boldly embraced Industry 4.0 technologies, subjecting their specific practices and processes to thorough examination. This methodological approach yielded a wealth of invaluable insights into the practical implications of Industry 4.0 on organizational sustainability, effectively bridging the gap between theory and practice. This research underscores the urgent need to provide businesses and decision‐makers with insights of paramount significance. The findings of the study aim to serve as a guiding compass for organizations, offering clarity on potential benefits and challenges associated with Industry 4.0 adoption. Notably, within the scope study, the utilization of semi‐structured interview technique added a unique dimension, enabling in‐depth insights. Interviews were conducted with individuals from diverse nations across different continents, thoughtfully selected based on predefined criteria, setting this research apart in terms of both the sample's size and the remarkable diversity within the participant profile. This diversity enriched the research findings by encompassing various perspectives and experiences, significantly enhancing the depth and breadth of the study's insights.

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Section: Theoretical Frameworkmentioning

confidence: 99%

Industry 4.0 and sustainable business models: An intercontinental sample

Kılıç,

Atilla

2023

Bus Strat Env

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“…It can be noted how, in [34], for example, the implemented method is based on an external GPU setup. This guarantees (based on the GPU performance) large parallel processing capabilities, in terms of overall throughput, but also implies that a structure that is able to readout, communicate and send the data to a host PC at those high data rates (10Gb/s) needs to be put in place: a high speed networking card and cables that interface with the data-generating FPGA, a costly and power hungry dedicated GPU to process the data, all running on a host computer that needs to be powerful enough to keep up with the data rates involved.…”

Section: Trend Of Implementation Strategy and State-of-the-artmentioning

confidence: 99%

High-Performance Computing of Real-Time and Multichannel Histograms: A Full FPGA Approach

et al. 2022

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In a world heading towards applications, in science and industry, based on big data processing, the ability to elaborate streams of data is becoming more important every day. Applications of various natures, ranging from biology to chemistry, from medical imaging to spectroscopy, need systems able to detect, process and store huge amounts of data in real-time. In this context, techniques such as histogramming come into play. Histograms are able to represent data shapes and retrieve statistical information, favoring further processing. This kind of processing is usually done with the help of general purpose processors, relying on temporal computing, with their pros (simplicity and fast operating frequencies) and cons (inability to exploit parallel computation). Both Industry and Academia have, however, proposed many solutions to this need, delivering histogram generators both in full-custom Application-Specific Integrated Circuits (ASICs) and Field-Programmable Gate Array (FPGA) IP-Cores, preferred over processors thanks to their superior parallel computing power. In this work, we present a full FPGA approach to this issue, resulting in a high-performance IP-Core for generating and managing multiple histograms in real time, each supporting a data flow up to 224 MSps, with a strong focus on overall flexibility and area efficiency, using as low as < 250 LUTs and 300 FFs resources for a 16 bit-wide, 4096-bin histogram implementation. The IP-Core has been successfully integrated and validated in a high-performance time-mode application: an FPGA-based Time-to-Digital Converter. The resulting IP-Core is, more in general, a single solution perfectly adaptable to any field of application and FPGA device.INDEX TERMS Field-programmable gate array (FPGA), histograms, real-time systems, IP-Cores, throughput.

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An integrated and scalable experimental system for nitrogen-vacancy ensemble magnetometry

Song

Zhu

et al. 2023

Review of Scientific Instruments

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Nitrogen-vacancy (NV) centers in diamond are extremely promising solid-state spin quantum sensors for magnetic field in recent years. The rapid development of NV-ensemble magnetometry has put forward higher requirements for high-speed data acquisition, real-time signal processing and analyzing, etc. However, the existing commercial instruments are bulky and expensive, which brings extra complexity to the weak magnetic field detection experiment and hinders the practicality and miniaturization of NV-ensemble magnetometry. Here, we report on an integrated and scalable experimental system based on a field-programmable-gate-array (FPGA) chip assisted with high-speed peripherals for NV-ensemble magnetometry, which presents a compact and compatible design containing high-speed data acquisition, oscilloscopes, signal generator, spectrum analyzer, lock-in amplifier, proportional-integral-derivative feedback controller, etc. To verify its applicability and reliability in experiments, various applications, such as optical magnetic resonance detection, optical cavity locking, and lock-in NV magnetometry, are conducted. We further realize the pump-enhanced magnetometry based on NV center ensembles using the optical cavity. Through the flexible FPGA design approach, this self-developed device can also be conveniently extended into atomic magnetometer and other quantum systems.

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High-accuracy and video-rate lifetime extraction from time correlated single photon counting data on a graphical processing unit

Abstract: Nanoscale tensile strain in perfect silicon crystals studied by high-resolution X-ray diffraction Review of Scientific Instruments 90, 100901 (2019);

Cited by 6 publications

References 26 publications

Industry 4.0 and sustainable business models: An intercontinental sample

Industry 4.0 and sustainable business models: An intercontinental sample

High-Performance Computing of Real-Time and Multichannel Histograms: A Full FPGA Approach

An integrated and scalable experimental system for nitrogen-vacancy ensemble magnetometry

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