500 research outputs found

    FlexWAFE - eine Architektur für rekonfigurierbare-Bildverarbeitungssysteme

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    Recently there has been an increase in demand for high-resolution digital media content in both cinema and television industries. Currently existing equipment does not meet the requirements, or is too costly. New hardware systems and new programming techniques are needed in order to meet the high-resolution, high-quality, image requirements and reduce costs. The industry seeks a flexible architecture capable of running multiple applications on top of standard off-the-shelf components, with reduced development time. Until now, standard practice has been to develop specialized architectures and systems that target a single application. This has little flexibility and leads to high developments costs, every new application is designed almost from scratch. Our focus was to develop an architecture that is suited to image stream processing and has the flexibility to run multiple applications using the same FPGA-based hardware platform. The novelty in our approach is that we reconfigure parts of the architecture at run-time, but without incurring in the time and added constraints penalty of FPGA-partial-reconfiguration techniques. The architecture uses a hierarchical control structure that is well suited to parallel processing, and allows single cycle latency reconfiguration of parts of the processing pipeline. This is achieved using relatively little resources for the distributed control structures. To test the developed architecture a complex film-grain noise reduction algorithm was implemented on an off-the-shelf hardware platform developed by Thomson-Grass Valley. The system meet all the requirements and had very little load on the hierarchical control structures, there is growth headroom for much complexer control demands. The architecture has been ported to other hardware platforms, and other applications have been implemented as well. The run-time reconfigurability has proven to be a key factor in the success of the FlexWAFE.Kürzlich gab es eine Zunahme der Nachfrage nach hochauflösenden digitalen Medieninhalten in den Kino- und Fernsehenindustrien. Derzeit vorhandene Systeme entsprechen nicht den Anforderungen, oder sind zu teuer. Neue Hardware-Systeme und neuer Programmiertechniken sind erforderlich, um den hochauflösenden, hochwertigen, Bildanforderungen zu genügen und Kosten zu verringern. Die Industrie sucht eine flexible Architektur zur Ausführung mehrerer Anwendungen auf Standard-Komponenten, mit reduzierten Entwicklungszeiten. Bis jetzt ist gängige Praxis, spezialisierten Architektur und Systeme zu entwickeln, die eine einzelne Anwendung zielen. Dieses hat wenig Flexibilität und führt zu hohe Entwicklungskosten, jede neue Anwendung ist fast von Grund auf neu konzipiert. Unser Fokus war es, eine für Bild Verarbeitung geeignet Architektur zu entwickeln dass die Flexibilität hat mehrere Anwendungen an dieselbe FPGA-basierte Hardware-Plattform zu laufen. Die Neuheit in unserem Ansatz ist, dass wir Teile der Architektur zur Laufzeit rekonfigurieren, aber, ohne das Zeit und constraints strafe von FPGA Partielle-Rekonfiguration-Techniken. Die Architektur verwendet eine hierarchische Kontrollstruktur, die zur parallel Verarbeitung gut geeignet ist, und Single-Cycle-Latenz Rekonfiguration von Teilen der Verarbeitungs-Pipeline ermöglicht. Dieses wird unter Verwendung relativ weniger Ressourcen für die verteiltes Steuerung Strukturen erzielt. Um das entwickelte Architektur zu testen ein komplexer Film-Korn-Rauschunterdrückung Algorithmus wurde auf einer von Thomson-Grass Valley entwickelt standard Hardware-Plattform umgesetzt. Das System erfüllt alle Anforderungen und hatte sehr wenig Last auf den hierarchischen Kontrollstrukturen, es gibt viel Wachstum Spielraum für viel kompliziertere Steuerunganforderungen. Die Architektur ist zu anderen Hardwareplattformen portiert worden, und andere Anwendungen wurden ebenfalls implementiert. Der Laufzeitreconfigurability ist ein Schlüsselfaktor im Erfolg des FlexWAFE gewesen

    Data Acquisition Applications

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    Data acquisition systems have numerous applications. This book has a total of 13 chapters and is divided into three sections: Industrial applications, Medical applications and Scientific experiments. The chapters are written by experts from around the world, while the targeted audience for this book includes professionals who are designers or researchers in the field of data acquisition systems. Faculty members and graduate students could also benefit from the book

    Efficient architectures of heterogeneous fpga-gpu for 3-d medical image compression

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    The advent of development in three-dimensional (3-D) imaging modalities have generated a massive amount of volumetric data in 3-D images such as magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), and ultrasound (US). Existing survey reveals the presence of a huge gap for further research in exploiting reconfigurable computing for 3-D medical image compression. This research proposes an FPGA based co-processing solution to accelerate the mentioned medical imaging system. The HWT block implemented on the sbRIO-9632 FPGA board is Spartan 3 (XC3S2000) chip prototyping board. Analysis and performance evaluation of the 3-D images were been conducted. Furthermore, a novel architecture of context-based adaptive binary arithmetic coder (CABAC) is the advanced entropy coding tool employed by main and higher profiles of H.264/AVC. This research focuses on GPU implementation of CABAC and comparative study of discrete wavelet transform (DWT) and without DWT for 3-D medical image compression systems. Implementation results on MRI and CT images, showing GPU significantly outperforming single-threaded CPU implementation. Overall, CT and MRI modalities with DWT outperform in term of compression ratio, peak signal to noise ratio (PSNR) and latency compared with images without DWT process. For heterogeneous computing, MRI images with various sizes and format, such as JPEG and DICOM was implemented. Evaluation results are shown for each memory iteration, transfer sizes from GPU to CPU consuming more bandwidth or throughput. For size 786, 486 bytes JPEG format, both directions consumed bandwidth tend to balance. Bandwidth is relative to the transfer size, the larger sizing will take more latency and throughput. Next, OpenCL implementation for concurrent task via dedicated FPGA. Finding from implementation reveals, OpenCL on batch procession mode with AOC techniques offers substantial results where the amount of logic, area, register and memory increased proportionally to the number of batch. It is because of the kernel will copy the kernel block refer to batch number. Therefore memory bank increased periodically related to kernel block. It was found through comparative study that the tree balance and unroll loop architecture provides better achievement, in term of local memory, latency and throughput

    Factories of the Future

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    Engineering; Industrial engineering; Production engineerin

    2022 roadmap on neuromorphic computing and engineering

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    Modern computation based on von Neumann architecture is now a mature cutting-edge science. In the von Neumann architecture, processing and memory units are implemented as separate blocks interchanging data intensively and continuously. This data transfer is responsible for a large part of the power consumption. The next generation computer technology is expected to solve problems at the exascale with 1018^{18} calculations each second. Even though these future computers will be incredibly powerful, if they are based on von Neumann type architectures, they will consume between 20 and 30 megawatts of power and will not have intrinsic physically built-in capabilities to learn or deal with complex data as our brain does. These needs can be addressed by neuromorphic computing systems which are inspired by the biological concepts of the human brain. This new generation of computers has the potential to be used for the storage and processing of large amounts of digital information with much lower power consumption than conventional processors. Among their potential future applications, an important niche is moving the control from data centers to edge devices. The aim of this roadmap is to present a snapshot of the present state of neuromorphic technology and provide an opinion on the challenges and opportunities that the future holds in the major areas of neuromorphic technology, namely materials, devices, neuromorphic circuits, neuromorphic algorithms, applications, and ethics. The roadmap is a collection of perspectives where leading researchers in the neuromorphic community provide their own view about the current state and the future challenges for each research area. We hope that this roadmap will be a useful resource by providing a concise yet comprehensive introduction to readers outside this field, for those who are just entering the field, as well as providing future perspectives for those who are well established in the neuromorphic computing community

    Predicting power scalability in a reconfigurable platform

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    This thesis focuses on the evolution of digital hardware systems. A reconfigurable platform is proposed and analysed based on thin-body, fully-depleted silicon-on-insulator Schottky-barrier transistors with metal gates and silicide source/drain (TBFDSBSOI). These offer the potential for simplified processing that will allow them to reach ultimate nanoscale gate dimensions. Technology CAD was used to show that the threshold voltage in TBFDSBSOI devices will be controllable by gate potentials that scale down with the channel dimensions while remaining within appropriate gate reliability limits. SPICE simulations determined that the magnitude of the threshold shift predicted by TCAD software would be sufficient to control the logic configuration of a simple, regular array of these TBFDSBSOI transistors as well as to constrain its overall subthreshold power growth. Using these devices, a reconfigurable platform is proposed based on a regular 6-input, 6-output NOR LUT block in which the logic and configuration functions of the array are mapped onto separate gates of the double-gate device. A new analytic model of the relationship between power (P), area (A) and performance (T) has been developed based on a simple VLSI complexity metric of the form ATσ = constant. As σ defines the performance “return” gained as a result of an increase in area, it also represents a bound on the architectural options available in power-scalable digital systems. This analytic model was used to determine that simple computing functions mapped to the reconfigurable platform will exhibit continuous power-area-performance scaling behavior. A number of simple arithmetic circuits were mapped to the array and their delay and subthreshold leakage analysed over a representative range of supply and threshold voltages, thus determining a worse-case range for the device/circuit-level parameters of the model. Finally, an architectural simulation was built in VHDL-AMS. The frequency scaling described by σ, combined with the device/circuit-level parameters predicts the overall power and performance scaling of parallel architectures mapped to the array

    NASA SBIR abstracts of 1991 phase 1 projects

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    The objectives of 301 projects placed under contract by the Small Business Innovation Research (SBIR) program of the National Aeronautics and Space Administration (NASA) are described. These projects were selected competitively from among proposals submitted to NASA in response to the 1991 SBIR Program Solicitation. The basic document consists of edited, non-proprietary abstracts of the winning proposals submitted by small businesses. The abstracts are presented under the 15 technical topics within which Phase 1 proposals were solicited. Each project was assigned a sequential identifying number from 001 to 301, in order of its appearance in the body of the report. Appendixes to provide additional information about the SBIR program and permit cross-reference of the 1991 Phase 1 projects by company name, location by state, principal investigator, NASA Field Center responsible for management of each project, and NASA contract number are included

    Addressing Tasks Through Robot Adaptation

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    Developing flexible, broadly capable systems is essential for robots to move out of factories and into our daily lives, functioning as responsive agents that can handle whatever the world throws at them. This dissertation focuses on two kinds of robot adaptation. Modular self-reconfigurable robots (MSRR) adapt to the requirements of their task and environments by transforming themselves. By rearranging the connective structure of their component robot modules, these systems can assume different morphologies: for example, a cluster of modules might configure themselves into a car to maneuver on flat ground, a snake to climb stairs, or an arm to pick and place objects. Conversely, environment augmentation is a strategy in which the robot transforms its environment to meet its own needs, adding physical structures that allow it to overcome obstacles. In both areas, the presented work includes elements of hardware design, algorithms, and integrated systems, with the common goal of establishing these methods of adaptation as viable strategies to address tasks. The research takes a systems-level view of robotics, placing particular emphasis on experimental validation in hardware
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