Search results for "Field Programmable Gate Array"

showing 10 items of 13 documents

Sistema de transferencia de datos en el instrumento TilePPr del proyecto TileCal

2017

El proyecto surge de la implementación del nuevo sistema de lectura de datos FELIX, que aprovecha los Transceptores Gigabit incorporados en las FPGA XC7VX485T y XC7VX690T del fabricante Xilinx. Estos transceptores se usan para establecer enlaces de datos a través de fibra óptica entre la FPGA del Pre-procesador del TileCal o TilePPr (XC7VX485T) y la placa electrónica que está conectada por PCIe al servidor local (XC7VX690T), por lo que el trabajo consiste en alcanzar los siguientes objetivos: a) Poner en marcha en la FPGA XC7VX485T del Pre-procesador o TilePPr la interfaz de transferencia de datos para que sea compatible con el nuevo sistema “Enlace de intercambio en el límite frontal” o FE…

:CIENCIAS TECNOLÓGICAS::Tecnología electrónica ::Diseño de circuitos [UNESCO]:CIENCIAS TECNOLÓGICAS::Tecnología electrónica ::Microelectrónica. Diseño [UNESCO]pcb:CIENCIAS TECNOLÓGICAS::Tecnología electrónica ::Microelectrónica [UNESCO]fpga Mezzanine Card:FÍSICA::Electrónica ::Circuitos integrados [UNESCO]placa de circuito impresoUNESCO::CIENCIAS TECNOLÓGICAS::Tecnología electrónica ::Diseño de circuitoscomunicación digitalvhdltransferencia de datosfpgaUNESCO::FÍSICA::Electrónica ::Circuitos integradosprotocolo de comunicaciónUNESCO::CIENCIAS TECNOLÓGICAS::Tecnología electrónica ::Microelectrónica. Diseñoelectrónica Digitalseñal de relojmicrostripUNESCO::CIENCIAS TECNOLÓGICAS::Tecnología electrónica ::Microelectrónicafield programmable gate arrays
researchProduct

Efficient MLP Digital Implementation on FPGA

2005

The efficiency and the accuracy of a digital feed-forward neural networks must be optimized to obtain both high classification rate and minimum area on chip. In this paper an efficient MLP digital implementation. The key features of the hardware implementation are the virtual neuron based architecture and the use of the sinusoidal activation function for the hidden layer. The effectiveness of the proposed solutions has been evaluated developing different FPGA based neural prototypes for the High Energy Physics domain and the automatic Road Sign Recognition domain. The use of the sinusoidal activation function decreases hardware resource employment of about 32% when compared with the standar…

Artificial neural networkbusiness.industryComputer scienceActivation functionField programmable gate arrays (FPGA)Sigmoid functionartificial neuralMachine learningcomputer.software_genreTransfer functionDomain (software engineering)Feedforward neural networkSystem on a chipArtificial intelligencebusinessField-programmable gate arraycomputerComputer hardwareNeural networks
researchProduct

Parallelizing Epistasis Detection in GWAS on FPGA and GPU-Accelerated Computing Systems

2015

This is a post-peer-review, pre-copyedit version of an article published in IEEE - ACM Transactions on Computational Biology and Bioinformatics. The final authenticated version is available online at: http://dx.doi.org/10.1109/TCBB.2015.2389958 [Abstract] High-throughput genotyping technologies (such as SNP-arrays) allow the rapid collection of up to a few million genetic markers of an individual. Detecting epistasis (based on 2-SNP interactions) in Genome-Wide Association Studies is an important but time consuming operation since statistical computations have to be performed for each pair of measured markers. Computational methods to detect epistasis therefore suffer from prohibitively lon…

Computer scienceBioinformaticsDNA Mutational AnalysisGenome-wide association studyParallel computingPolymorphism Single NucleotideSensitivity and SpecificityComputational biologyComputer GraphicsGeneticsComputer architectureField-programmable gate arrayRandom access memoryApplied MathematicsChromosome MappingHigh-Throughput Nucleotide SequencingReproducibility of ResultsField programmable gate arraysEpistasis GeneticSignal Processing Computer-AssistedEquipment DesignRandom access memoryComputing systemsReconfigurable computingEquipment Failure AnalysisTask (computing)EpistasisHost (network)Graphics processing unitsGenome-Wide Association StudyBiotechnology
researchProduct

Live demonstration: multiplexing AER asynchronous channels over LVDS Links with Flow-Control and Clock-Correction for Scalable Neuromorphic Systems

2017

Paper presented at the 2017 IEEE International Symposium on Circuits and Systems (ISCAS), held in Baltimore, MD, USA, on 28-31 May 2017.

Computer scienceSerial communicationGabor filters02 engineering and technologyMultiplexingMultiplexing0202 electrical engineering electronic engineering information engineeringComputerSystemsOrganization_SPECIAL-PURPOSEANDAPPLICATION-BASEDSYSTEMSField-programmable gate arrayComputer Science::Operating SystemsMassively parallelNeuromorphicsReal-time systemsSpiking neural networkQuantitative Biology::Neurons and CognitionArtificial neural networkbusiness.industry020208 electrical & electronic engineeringField programmable gate arraysNeuromorphic engineeringAsynchronous communicationEmbedded systemVoltage controlbusinessComputer hardwareNeural networksHardware_LOGICDESIGN
researchProduct

Energy Efficiency Evaluation of Dynamic Partial Reconfiguration in Field Programmable Gate Arrays: An Experimental Case Study

2018

Both computational performances and energy efficiency are required for the development of any mobile or embedded information processing system. The Internet of Things (IoT) is the latest evolution of these systems, paving the way for advancements in ubiquitous computing. In a context in which a large amount of data is often analyzed and processed, it is mandatory to adapt node logic and processing capabilities with respect to the available energy resources. This paper investigates under which conditions a partially reconfigurable hardware accelerator can provide energy saving in complex processing tasks. The paper also presents a useful analysis of how the dynamic partial reconfiguration te…

Control and Optimizationvideo filteringComputer sciencedigital signal processingEnergy Engineering and Power TechnologyDigital signal processing; Dynamic partial reconfiguration; Energy efficiency; Field Programmable Gate Array; Video filtering02 engineering and technologylcsh:Technology0202 electrical engineering electronic engineering information engineeringElectrical and Electronic EngineeringField-programmable gate arrayEngineering (miscellaneous)Digital signal processingenergy efficiencyField Programmable Gate Arraybusiness.industryRenewable Energy Sustainability and the Environmentlcsh:Tenergy efficiency; dynamic partial reconfiguration; Field Programmable Gate Array; digital signal processing; video filteringControl reconfiguration020206 networking & telecommunicationsEnergy consumptionReconfigurable computingdynamic partial reconfigurationEmbedded system020201 artificial intelligence & image processingNode (circuits)businessEnergy (signal processing)Efficient energy useEnergy (miscellaneous)Energies
researchProduct

Exploring FPGA‐Based Lock‐In Techniques for Brain  Monitoring Applications

2017

Functional near‐infrared spectroscopy (fNIRS) systems for e‐health applications usually suffer from poor signal detection, mainly due to a low end‐to‐end signal‐to‐noise ratio of the electronics chain. Lock‐in amplifiers (LIA) historically represent a powerful technique helping to improve performance in such circumstances. In this work a digital LIA system, based on a Zynq® field programmable gate array (FPGA) has been designed and implemented, in an attempt to explore if this technique might improve fNIRS system performance. More broadly, FPGA‐based solution flexibility has been investigated, with particular emphasis applied to digital filter parameters, needed in the digital LIA, and its …

Engineeringhardware description language (HDL) near‐infrared  spectroscopy (NIRS)light emitting diode (LED)Computer Networks and Communicationslcsh:TK7800-836002 engineering and technologysilicon photomultiplier (SiPM)Settore ING-INF/01 - Elettronica01 natural sciencesSignaldigital lock‐in amplifier (DLIA)law.invention hardware description language (HDL)microprocessorslawVHDL0202 electrical engineering electronic engineering information engineeringElectronic engineeringDetection theoryElectrical and Electronic EngineeringField-programmable gate arraycomputer.programming_languagebusiness.industryNoise (signal processing)lcsh:Electronics010401 analytical chemistryEmphasis (telecommunications)near‐infrared spectroscopy (NIRS)020206 networking & telecommunications0104 chemical sciences light emitting diode (LED) microprocessorsfield programmable gate array (FPGA)Microprocessordigital lock‐in amplifier (DLIA)Hardware and ArchitectureControl and Systems EngineeringSignal Processingbusinessdigital lock‐in amplifier (DLIA); field programmable gate array (FPGA); near‐infrared  spectroscopy (NIRS); hardware description language (HDL); light emitting diode (LED); silicon  photomultiplier (SiPM); microprocessors field programmable gate array (FPGA) silicon  photomultiplier (SiPM)Digital filtercomputerComputer hardwareElectronics
researchProduct

Resource-efficient hardware implementation of a neural-based node for automatic fingerprint classification

2017

Modern mobile communication networks and Internet of Things are paving the way to ubiquitous and mobile computing. On the other hand, several new computing paradigms, such as edge computing, demand for high computational capabilities on specific network nodes. Ubiquitous environments require a large number of distributed user identification nodes enabling a secure platform for resources, services and information management. Biometric systems represent a useful option to the typical identification systems. An accurate automatic fingerprint classification module provides a valuable indexing scheme that allows for effective matching in large fingerprint databases. In this work, an efficient em…

Fingerprint classificationField programmable gate array (FPGA)INF/01 - INFORMATICAWeightless neural networkWeightless neural networksMobile and ubiquitous ComputingField programmable gate array (FPGA); Fingerprint classification; Mobile and ubiquitous Computing; Virtual neuron; Weightless neural networksVirtual neuronMobile and Ubiquitous Computing Fingerprint Classification Weightless Neural Net- works Virtual Neuron Field Programmable Gate Array (FPGA)
researchProduct

PNeuro: A scalable energy-efficient programmable hardware accelerator for neural networks

2018

Proceedings of a meeting held 19-23 March 2018, Dresden, Germany; International audience; Artificial intelligence and especially Machine Learning recently gained a lot of interest from the industry. Indeed, new generation of neural networks built with a large number of successive computing layers enables a large amount of new applications and services implemented from smart sensors to data centers. These Deep Neural Networks (DNN) can interpret signals to recognize objects or situations to drive decision processes. However, their integration into embedded systems remains challenging due to their high computing needs. This paper presents PNeuro, a scalable energy-efficient hardware accelerat…

Neural network hardwareComputer sciencePooling02 engineering and technologyLow power0202 electrical engineering electronic engineering information engineeringSIMDField-programmable gate arrayFPGAComputer architecturesRoutingArtificial neural networkASIC[SCCO.NEUR]Cognitive science/Neuroscience020208 electrical & electronic engineering[SCCO.NEUR] Cognitive science/NeuroscienceField programmable gate arraysConvolution020202 computer hardware & architectureGeneratorsComputer architectureScalabilityHardware accelerationRouting (electronic design automation)Neural networksEfficient energy use
researchProduct

The Mu3e Data Acquisition

2020

The Mu3e experiment aims to find or exclude the lepton flavour violating decay $\mu^+\to e^+e^-e^+$ with a sensitivity of one in 10$^{16}$ muon decays. The first phase of the experiment is currently under construction at the Paul Scherrer Institute (PSI, Switzerland), where beams with up to 10$^8$ muons per second are available. The detector will consist of an ultra-thin pixel tracker made from High-Voltage Monolithic Active Pixel Sensors (HV-MAPS), complemented by scintillating tiles and fibres for precise timing measurements. The experiment produces about 100 Gbit/s of zero-suppressed data which are transported to a filter farm using a network of FPGAs and fast optical links. On the filte…

Nuclear and High Energy PhysicsParticle physicsPhysics - Instrumentation and DetectorsMesonPhysics::Instrumentation and Detectorsdata acquisitionfibre: opticalFOS: Physical scienceshigh energy physics instrumentationprinted circuits7. Clean energycomputer: networkOptical fiber communicationData acquisitionsemiconductor detector: pixelOptical switchesmultiprocessor: graphicshardwareSensitivity (control systems)muon+: decay[PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det]Electrical and Electronic EngineeringGeneralLiterature_REFERENCE(e.g.dictionariesencyclopediasglossaries)scintillation counterFPGAClocksPhysicsData acquisition (DAQ)MuonPixelMesonsDetectorlepton: flavor: violationField programmable gate arraysDetectorsInstrumentation and Detectors (physics.ins-det)sensitivityNuclear Energy and EngineeringFilter (video)field programmable gate arrays (FPGAs)Data acquisition (DAQ); field programmable gate arrays (FPGAs); high energy physics instrumentation; printed circuitselectronics: readoutHigh Energy Physics::ExperimentLeptonelectronics: design
researchProduct

Efficient FPGA Implementation of a Knowledge-Based Automatic Speech Classifier

2005

Speech recognition has become common in many application domains, from dictation systems for professional practices to vocal user interfaces for people with disabilities or hands-free system control. However, so far the performance of Automatic Speech Recognition (ASR) systems are comparable to Human Speech Recognition (HSR) only under very strict working conditions, and in general far lower. Incorporating acoustic-phonetic knowledge into ASR design has been proven a viable approach to rise ASR accuracy. Manner of articulation attributes such as vowel, stop, fricative, approximant, nasal, and silence are examples of such knowledge. Neural networks have already been used successfully as dete…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniArtificial neural networkDictationComputer sciencebusiness.industrySpeech recognitionField programmable gate arrays (FPGA)artificial neuralPerceptronManner of articulationKnowledge baseUser interfacebusinessField-programmable gate arrayClassifier (UML)Neural networks
researchProduct