1,250 research outputs found

    Smart technologies for effective reconfiguration: the FASTER approach

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    Current and future computing systems increasingly require that their functionality stays flexible after the system is operational, in order to cope with changing user requirements and improvements in system features, i.e. changing protocols and data-coding standards, evolving demands for support of different user applications, and newly emerging applications in communication, computing and consumer electronics. Therefore, extending the functionality and the lifetime of products requires the addition of new functionality to track and satisfy the customers needs and market and technology trends. Many contemporary products along with the software part incorporate hardware accelerators for reasons of performance and power efficiency. While adaptivity of software is straightforward, adaptation of the hardware to changing requirements constitutes a challenging problem requiring delicate solutions. The FASTER (Facilitating Analysis and Synthesis Technologies for Effective Reconfiguration) project aims at introducing a complete methodology to allow designers to easily implement a system specification on a platform which includes a general purpose processor combined with multiple accelerators running on an FPGA, taking as input a high-level description and fully exploiting, both at design time and at run time, the capabilities of partial dynamic reconfiguration. The goal is that for selected application domains, the FASTER toolchain will be able to reduce the design and verification time of complex reconfigurable systems providing additional novel verification features that are not available in existing tool flows

    Toolflows for Mapping Convolutional Neural Networks on FPGAs: A Survey and Future Directions

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    In the past decade, Convolutional Neural Networks (CNNs) have demonstrated state-of-the-art performance in various Artificial Intelligence tasks. To accelerate the experimentation and development of CNNs, several software frameworks have been released, primarily targeting power-hungry CPUs and GPUs. In this context, reconfigurable hardware in the form of FPGAs constitutes a potential alternative platform that can be integrated in the existing deep learning ecosystem to provide a tunable balance between performance, power consumption and programmability. In this paper, a survey of the existing CNN-to-FPGA toolflows is presented, comprising a comparative study of their key characteristics which include the supported applications, architectural choices, design space exploration methods and achieved performance. Moreover, major challenges and objectives introduced by the latest trends in CNN algorithmic research are identified and presented. Finally, a uniform evaluation methodology is proposed, aiming at the comprehensive, complete and in-depth evaluation of CNN-to-FPGA toolflows.Comment: Accepted for publication at the ACM Computing Surveys (CSUR) journal, 201

    Design and application of reconfigurable circuits and systems

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    Speed-up run-time reconfiguration implementation on FPGAs

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    International audienceReconfigurable computing is certainly one of the most important emerging research topics over the last few years, in the field of digital processing architectures. The introduction of run-time reconfiguration (RTR) on FPGAs requires appropriate design flows and methodologies to fully exploit this new functionality. For that purpose we present an automatic design generation methodology for heterogeneous architectures based on Network on Chip (NoC) and FPGAs that eases and speed-up RTR implementation. We focus on how to take into account specificities of partially reconfigurable components during the design generation steps. This method automatically generates designs for both fixed and partially reconfigurable parts of a FPGA with automaticmanagement of the reconfiguration process. Furthermore this automatic design generation enables reconfiguration pre-fetching techniques to minimize reconfiguration latency and buffer merging techniques to minimize memory requirements of the generated design. This concept has been applied to different wireless access schemes, based on a combination of OFDM and CDMA techniques. The implementation example illustrates the benefits of the proposed design methodology

    FPGA dynamic and partial reconfiguration : a survey of architectures, methods, and applications

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    Dynamic and partial reconfiguration are key differentiating capabilities of field programmable gate arrays (FPGAs). While they have been studied extensively in academic literature, they find limited use in deployed systems. We review FPGA reconfiguration, looking at architectures built for the purpose, and the properties of modern commercial architectures. We then investigate design flows, and identify the key challenges in making reconfigurable FPGA systems easier to design. Finally, we look at applications where reconfiguration has found use, as well as proposing new areas where this capability places FPGAs in a unique position for adoption

    10281 Abstracts Collection -- Dynamically Reconfigurable Architectures

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    From 11.07.10 to 16.07.10, Dagstuhl Seminar 10281 ``Dynamically Reconfigurable Architectures \u27\u27 was held in Schloss Dagstuhl~--~Leibniz Center for Informatics. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

    Reconfiguration of field programmable logic in embedded systems

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