39 research outputs found

    IP-Enabled C/C++ Based High Level Synthesis: A Step towards Better Designer Productivity and Design Performance

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    Intellectual property (IP) core based design is an emerging design methodology to deal with increasing chip design complexity. C/C++ based high level synthesis (HLS) is also gaining traction as a design methodology to deal with increasing design complexity. In the work presented here, we present a design methodology that combines these two individual methodologies and is therefore more powerful. We discuss our proposed methodology in the context of supporting efficient hardware synthesis of a class of mathematical functions without altering original C/C++ source code. Additionally, we also discuss and propose methods to integrate legacy IP cores in existing HLS flows. Relying on concepts from the domains of program recognition and optimized low level implementations of such arithmetic functions, the described design methodology is a step towards intelligent synthesis where application characteristics are matched with specific architectural resources and relevant IP cores in a transparent manner for improved area-delay results. The combined methodology is more aware of the target hardware architecture than the conventional HLS flow. Implementation results of certain compute kernels from a commercial tool Vivado-HLS as well as proposed flow are also compared to show that proposed flow gives better results

    The state of adoption and the challenges of systematic variability management in industry

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    Handling large-scale software variability is still a challenge for many organizations. After decades of research on variability management concepts, many industrial organizations have introduced techniques known from research, but still lament that pure textbook approaches are not applicable or efficient. For instance, software product line engineering—an approach to systematically develop portfolios of products—is difficult to adopt given the high upfront investments; and even when adopted, organizations are challenged by evolving their complex product lines. Consequently, the research community now mainly focuses on re-engineering and evolution techniques for product lines; yet, understanding the current state of adoption and the industrial challenges for organizations is necessary to conceive effective techniques. In this multiple-case study, we analyze the current adoption of variability management techniques in twelve medium- to large-scale industrial cases in domains such as automotive, aerospace or railway systems. We identify the current state of variability management, emphasizing the techniques and concepts they adopted. We elicit the needs and challenges expressed for these cases, triangulated with results from a literature review. We believe our results help to understand the current state of adoption and shed light on gaps to address in industrial practice.This work is supported by Vinnova Sweden, Fond Unique Interminist´eriel (FUI) France, and the Swedish Research Council. Open access funding provided by University of Gothenbur

    HAL-ASOS - Linux com aceleração em hardware para sistemas operativos dedicados à aplicação

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    Programa doutoral em Engenharia Eletrónica e de Computadores (PDEEC) (especialidade de Informática Industrial e Sistemas Embebidos)O ecossistema de sistemas embebidos de hoje tornou-se enorme, cobrindo vários e diferentes sistemas, exigindo desempenho e mobilidade completa enquanto atingem autonomias de bateria cada vez maiores. Mas a crescente frequência de relógio que resultou em dispositivos cada vez mais rápidos começou a estagnar antes dos transístores pararem de encolher. Plataformas Field Programmable Gate Array (FPGA) são uma solução alternativa para a implementação de sistemas completos e reconfiguráveis. Fornecem desempenho e eficiência computacional para satisfazer requisitos da aplicação e do sistema embebido. Vários Sistemas Operativos (SO) assistidos por FPGA foram propostos, mas ao estreitar seu foco na síntese do datapath do acelerador de hardware, a grande maioria ignora a integração semântica destes no SO. Ambientes de síntese de alto nível (HLS) elevaram a abstração além da linguagem de transferência de registo (RTL), seguindo uma abordagem específica de domínio enquanto misturam software e abstrações de hardware ad hoc, que dificultam as otimizações. Além disso, os modelos de programação para software e hardware reconfigurável carecem de semelhanças, o que com o tempo dificultará a Exploração do Ambiente de Design (DSE) e diminuirá o potencial de reutilização de código. Para responder a estas necessidades, propomos HAL-ASOS, uma ferramenta para implementar sistemas embebidos baseados em Linux que fornece (1) elasticidade no design em conformidade com a natureza evolutiva deste SO, (2) integração semântica profunda de tarefas de hardware nos modelos de programação do Linux, (3) facilidade na gestão de complexidade através de metodologia e ferramentas para apoiar o design, verificação e implementação, (4) orientada por princípios de design híbridos e eficiência no sistema. Para avaliar as funcionalidades da ferramenta, foi implementado um aplicativo criptográfico que demonstra alcance de desempenho enquanto se emprega a metodologia de design. Novos níveis de desempenho são atingidos numa aplicação de Visão por Computador que explora recursos de programação assíncrona-síncrona. Os resultados demonstram uma abordagem flexível na reconfiguração entre hardware e software, e desempenho que aumenta consistentemente com acréscimo de recursos ou frequência de relógio.Today’s embedded systems ecosystem became huge while covering several and different computer-based systems, demanding for performance and complete mobility while experiencing longer battery lives. But the rampant frequency that resulted in faster devices began hitting a wall even before transistors stopped shrinking. Field Programmable Gate Array (FPGA) platforms are an alternative solution towards implementing complete reconfigurable systems. They provide computational power, efficiency, in a lightweight solution to serve the application requirements and increase performance in the overall system. Several FPGA-assisted Operating Systems (OS) have been proposed, but by narrowing their focus on datapath synthesis of the hardware accelerator, they completely ignore the deep semantic integration of these accelerators into the OS. State-of-the-art High-Level Synthesis (HLS) environments have raised the level of abstraction beyond Register Transfer Language (RTL) by following a domain-specific approach while mixing ad hoc software and hardware abstractions, making harder for performance optimizations. Furthermore, the programming models for software and reconfigurable hardware lack commonalities, which in time will hinder the Design Space Exploration (DSE) and lower the potential for code reuse. To overcome these issues, we propose HAL-ASOS, a framework to implement Linux-based Embedded systems which provides (1) elasticity by design to comply with the evolutive nature of Linux, (2) deep semantic integration of the hardware tasks in the Linux programming models, (3) easy complexity management using methodology and tools to fully support design, verification and deployment, (4) hybrid and efficiency-oriented design principles. To evaluate the framework functionalities, a cryptographic application was implemented and demonstrates performance achievements while using the promoted application-driven design methodology. To demonstrate new levels of performance that can be achieved, a Computer Vision application explores several mixed asynchronous-synchronous programming features. Experiments demonstrate a flexible design approach in terms of hardware and software reconfiguration, and significant performance that increases consistently with the rising in processing resources or clock frequencies.Financial support received from Portuguese Foundation for Science and Technology (FCT) with the PhD grant SFRH/BD/82732/2011

    Routines and Applications of Symbolic Algebra Software

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    Computing has become an essential resource in modern research and has found application across a wide range of scientific disciplines. Developments in symbolic algebra tools have been particularly valuable in physics where calculations in fields such as general relativity, quantum field theory and physics beyond the standard model are becoming increasing complex and unpractical to work with by hand. The computer algebra system Cadabra is a tensor-first approach to symbolic algebra based on the programming language Python which has been used extensively in research in these fields while also having a shallow learning curve making it an excellent way to introduce students to methods in computer algebra. The work in this thesis has been concentrated on developing Cadabra, which has involved looking at two different elements which make up a computer algebra program. Firstly, the implementation of algebraic routines is discussed. This has primarily been focused on the introduction of an algorithm for detecting the equivalence of tensorial expressions related by index permutation symmetries. The method employed differs considerably from traditional canonicalisation routines which are commonly used for this purpose by using Young projection operators to make such symmetries manifest. The other element of writing a computer algebra program which is covered is the infrastruc- ture and environment. The importance of this aspect of software design is often overlooked by funding committees and academic software users resulting in an anti-pattern of code not being shared and contributed to in the way in which research itself is published and promulgated. The focus in this area has been on implementing a packaging system for Cadabra which allows the writing of generic libraries which can be shared by the community, and interfacing with other scientific computing packages to increase the capabilities of Cadabra

    Assist-as-needed exoskeleton for post-strokehand rehabilitation

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    El desarrollo del trabajo doctoral tiene cuatro etapas de desarrollo: i) estudio de la biomecánica de la mano y el sistema robótico utilizado en la rehabilitación del movimiento para definir los criterios de la estructura mecánica y del sistema. ii) Modelo del sistema robótico y construcción de dos bases de datos. El primero consiste en el modelo matemático utilizado como planta en los escenarios de simulación, y el segundo son las señales bioeléctricas y de movimiento utilizadas para calcular la clasificación de los modelos y realizar las pruebas al sistema completo. iii) Análisis de las señales mioeléctricas para detectar la intención de movimiento del sujeto y niveles de condición muscular. Se implementaron varias técnicas de reconocimiento de patrones para analizar las características y encontrar el modelo de clasificación con mejor desempeño. Ambos modelos son utilizados en el esquema del lazo cerrado propuesto en esta tesis. iv) El esquema de asistencia de lazo cerrado consiste en los módulos de aprendizaje, asistencia y seguimiento activo. El trabajo está dirigido a incluir la medición de la capacidad del sujeto para modular la asistencia dada por el exoesqueleto y manejar la posición de este. v) Los experimentos tienen como objetivo cuantificar el desempeño de la clasificación utilizando señales EMG de los pacientes, la modulación de la asistencia, y demostrar la hipótesis de proveer asistencia física específica a los requerimientos individuales a través de la modulación apropiada de la velocidad del robotThe PhD. thesis presents the development of a new closed-loop scheme to modulate the assistance given by an exoskeleton robot with a novel technique to measure subject capability. The closedloop scheme had been developed under the context of hand rehabilitation after stroke due to the hand functions are one of the most complicated to recover, and the stroke leads to several motion impairments. The current doctoral dissertation consists of four stages of development: i) study of the hand biomechanics and robotic system used in motion rehabilitation to define the mechanical structure and system criteria. ii) Robotic system modeling and datasets constructions. The former is the mathematical model used as the plant in the simulation scenarios, and the last is the myoelectrical motions signals used to compute the classification models and test the whole system. iii) Myoelectrical signals analysis to detect subject intention from stroke patients and muscular condition levels. Several pattern recognition techniques were implemented to analyze the feature influence and found the classification model with better performance. Both models are used in the closed-loop scheme. iv) The assistance closed-loop scheme consists of learning, assistance, and active-tracking modules. It is aimed to include the capability measurement to modulate the exoskeleton assistance and drive the exoskeleton position based on the trajectory reference and subject capability. v) Experiments are aimed at quantifying the classifier's performance using EMG signals from stroke patients, assistance modulation, and demonstrating the hypothesis of providing physical assistance specific to the individual requirements through proper modulation of the robot velocity.Doctor en IngenieríaDoctorad

    Feasibility Study of High-Level Synthesis : Implementation of a Real-Time HEVC Intra Encoder on FPGA

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    High-Level Synthesis (HLS) on automatisoitu suunnitteluprosessi, joka pyrkii parantamaan tuottavuutta perinteisiin suunnittelumenetelmiin verrattuna, nostamalla suunnittelun abstraktiota rekisterisiirtotasolta (RTL) käyttäytymistasolle. Erilaisia kaupallisia HLS-työkaluja on ollut markkinoilla aina 1990-luvulta lähtien, mutta vasta äskettäin ne ovat alkaneet saada hyväksyntää teollisuudessa sekä akateemisessa maailmassa. Hidas käyttöönottoaste on johtunut pääasiassa huonommasta tulosten laadusta (QoR) kuin mitä on ollut mahdollista tavanomaisilla laitteistokuvauskielillä (HDL). Uusimmat HLS-työkalusukupolvet ovat kuitenkin kaventaneet QoR-aukkoa huomattavasti. Tämä väitöskirja tutkii HLS:n soveltuvuutta videokoodekkien kehittämiseen. Se esittelee useita HLS-toteutuksia High Efficiency Video Coding (HEVC) -koodaukselle, joka on keskeinen mahdollistava tekniikka lukuisille nykyaikaisille mediasovelluksille. HEVC kaksinkertaistaa koodaustehokkuuden edeltäjäänsä Advanced Video Coding (AVC) -standardiin verrattuna, saavuttaen silti saman subjektiivisen visuaalisen laadun. Tämä tyypillisesti saavutetaan huomattavalla laskennallisella lisäkustannuksella. Siksi reaaliaikainen HEVC vaatii automatisoituja suunnittelumenetelmiä, joita voidaan käyttää rautatoteutus- (HW ) ja varmennustyön minimoimiseen. Tässä väitöskirjassa ehdotetaan HLS:n käyttöä koko enkooderin suunnitteluprosessissa. Dataintensiivisistä koodaustyökaluista, kuten intra-ennustus ja diskreetit muunnokset, myös enemmän kontrollia vaativiin kokonaisuuksiin, kuten entropiakoodaukseen. Avoimen lähdekoodin Kvazaar HEVC -enkooderin C-lähdekoodia hyödynnetään tässä työssä referenssinä HLS-suunnittelulle sekä toteutuksen varmentamisessa. Suorituskykytulokset saadaan ja raportoidaan ohjelmoitavalla porttimatriisilla (FPGA). Tämän väitöskirjan tärkein tuotos on HEVC intra enkooderin prototyyppi. Prototyyppi koostuu Nokia AirFrame Cloud Server palvelimesta, varustettuna kahdella 2.4 GHz:n 14-ytiminen Intel Xeon prosessorilla, sekä kahdesta Intel Arria 10 GX FPGA kiihdytinkortista, jotka voidaan kytkeä serveriin käyttäen joko peripheral component interconnect express (PCIe) liitäntää tai 40 gigabitin Ethernettiä. Prototyyppijärjestelmä saavuttaa reaaliaikaisen 4K enkoodausnopeuden, jopa 120 kuvaa sekunnissa. Lisäksi järjestelmän suorituskykyä on helppo skaalata paremmaksi lisäämällä järjestelmään käytännössä minkä tahansa määrän verkkoon kytkettäviä FPGA-kortteja. Monimutkaisen HEVC:n tehokas mallinnus ja sen monipuolisten ominaisuuksien mukauttaminen reaaliaikaiselle HW HEVC enkooderille ei ole triviaali tehtävä, koska HW-toteutukset ovat perinteisesti erittäin aikaa vieviä. Tämä väitöskirja osoittaa, että HLS:n avulla pystytään nopeuttamaan kehitysaikaa, tarjoamaan ennen näkemätöntä suunnittelun skaalautuvuutta, ja silti osoittamaan kilpailukykyisiä QoR-arvoja ja absoluuttista suorituskykyä verrattuna olemassa oleviin toteutuksiin.High-Level Synthesis (HLS) is an automated design process that seeks to improve productivity over traditional design methods by increasing design abstraction from register transfer level (RTL) to behavioural level. Various commercial HLS tools have been available on the market since the 1990s, but only recently they have started to gain adoption across industry and academia. The slow adoption rate has mainly stemmed from lower quality of results (QoR) than obtained with conventional hardware description languages (HDLs). However, the latest HLS tool generations have substantially narrowed the QoR gap. This thesis studies the feasibility of HLS in video codec development. It introduces several HLS implementations for High Efficiency Video Coding (HEVC) , that is the key enabling technology for numerous modern media applications. HEVC doubles the coding efficiency over its predecessor Advanced Video Coding (AVC) standard for the same subjective visual quality, but typically at the cost of considerably higher computational complexity. Therefore, real-time HEVC calls for automated design methodologies that can be used to minimize the HW implementation and verification effort. This thesis proposes to use HLS throughout the whole encoder design process. From data-intensive coding tools, like intra prediction and discrete transforms, to more control-oriented tools, such as entropy coding. The C source code of the open-source Kvazaar HEVC encoder serves as a design entry point for the HLS flow, and it is also utilized in design verification. The performance results are gathered with and reported for field programmable gate array (FPGA) . The main contribution of this thesis is an HEVC intra encoder prototype that is built on a Nokia AirFrame Cloud Server equipped with 2.4 GHz dual 14-core Intel Xeon processors and two Intel Arria 10 GX FPGA Development Kits, that can be connected to the server via peripheral component interconnect express (PCIe) generation 3 or 40 Gigabit Ethernet. The proof-of-concept system achieves real-time. 4K coding speed up to 120 fps, which can be further scaled up by adding practically any number of network-connected FPGA cards. Overcoming the complexity of HEVC and customizing its rich features for a real-time HEVC encoder implementation on hardware is not a trivial task, as hardware development has traditionally turned out to be very time-consuming. This thesis shows that HLS is able to boost the development time, provide previously unseen design scalability, and still result in competitive performance and QoR over state-of-the-art hardware implementations

    The Proceedings of the 23rd Annual International Conference on Digital Government Research (DGO2022) Intelligent Technologies, Governments and Citizens June 15-17, 2022

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    The 23rd Annual International Conference on Digital Government Research theme is “Intelligent Technologies, Governments and Citizens”. Data and computational algorithms make systems smarter, but should result in smarter government and citizens. Intelligence and smartness affect all kinds of public values - such as fairness, inclusion, equity, transparency, privacy, security, trust, etc., and is not well-understood. These technologies provide immense opportunities and should be used in the light of public values. Society and technology co-evolve and we are looking for new ways to balance between them. Specifically, the conference aims to advance research and practice in this field. The keynotes, presentations, posters and workshops show that the conference theme is very well-chosen and more actual than ever. The challenges posed by new technology have underscored the need to grasp the potential. Digital government brings into focus the realization of public values to improve our society at all levels of government. The conference again shows the importance of the digital government society, which brings together scholars in this field. Dg.o 2022 is fully online and enables to connect to scholars and practitioners around the globe and facilitate global conversations and exchanges via the use of digital technologies. This conference is primarily a live conference for full engagement, keynotes, presentations of research papers, workshops, panels and posters and provides engaging exchange throughout the entire duration of the conference

    Intelligent Energy-Savings and Process Improvement Strategies in Energy-Intensive Industries

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    S tím, jak se neustále vyvíjejí nové technologie pro energeticky náročná průmyslová odvětví, stávající zařízení postupně zaostávají v efektivitě a produktivitě. Tvrdá konkurence na trhu a legislativa v oblasti životního prostředí nutí tato tradiční zařízení k ukončení provozu a k odstavení. Zlepšování procesu a projekty modernizace jsou zásadní v udržování provozních výkonů těchto zařízení. Současné přístupy pro zlepšování procesů jsou hlavně: integrace procesů, optimalizace procesů a intenzifikace procesů. Obecně se v těchto oblastech využívá matematické optimalizace, zkušeností řešitele a provozní heuristiky. Tyto přístupy slouží jako základ pro zlepšování procesů. Avšak, jejich výkon lze dále zlepšit pomocí moderní výpočtové inteligence. Účelem této práce je tudíž aplikace pokročilých technik umělé inteligence a strojového učení za účelem zlepšování procesů v energeticky náročných průmyslových procesech. V této práci je využit přístup, který řeší tento problém simulací průmyslových systémů a přispívá následujícím: (i)Aplikace techniky strojového učení, která zahrnuje jednorázové učení a neuro-evoluci pro modelování a optimalizaci jednotlivých jednotek na základě dat. (ii) Aplikace redukce dimenze (např. Analýza hlavních komponent, autoendkodér) pro vícekriteriální optimalizaci procesu s více jednotkami. (iii) Návrh nového nástroje pro analýzu problematických částí systému za účelem jejich odstranění (bottleneck tree analysis – BOTA). Bylo také navrženo rozšíření nástroje, které umožňuje řešit vícerozměrné problémy pomocí přístupu založeného na datech. (iv) Prokázání účinnosti simulací Monte-Carlo, neuronové sítě a rozhodovacích stromů pro rozhodování při integraci nové technologie procesu do stávajících procesů. (v) Porovnání techniky HTM (Hierarchical Temporal Memory) a duální optimalizace s několika prediktivními nástroji pro podporu managementu provozu v reálném čase. (vi) Implementace umělé neuronové sítě v rámci rozhraní pro konvenční procesní graf (P-graf). (vii) Zdůraznění budoucnosti umělé inteligence a procesního inženýrství v biosystémech prostřednictvím komerčně založeného paradigmatu multi-omics.Zlepšení průmyslových procesů, Model založený na datech, Optimalizace procesu, Strojové učení, Průmyslové systémy, Energeticky náročná průmyslová odvětví, Umělá inteligence.

    Topics in Adaptive Optics

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    Advances in adaptive optics technology and applications move forward at a rapid pace. The basic idea of wavefront compensation in real-time has been around since the mid 1970s. The first widely used application of adaptive optics was for compensating atmospheric turbulence effects in astronomical imaging and laser beam propagation. While some topics have been researched and reported for years, even decades, new applications and advances in the supporting technologies occur almost daily. This book brings together 11 original chapters related to adaptive optics, written by an international group of invited authors. Topics include atmospheric turbulence characterization, astronomy with large telescopes, image post-processing, high power laser distortion compensation, adaptive optics and the human eye, wavefront sensors, and deformable mirrors
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