1,721,138 research outputs found

    Automatic Generation of Dataflow-Based Reconfigurable Co-processing Units

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    Abstract—Hardware accelerators are widely adopted to speed up computationally onerous applications. However their design is not trivial, especially if multiple applications/kernels need to be served. To this aim the Multi-Dataflow Composer (MDC) tool can be adopted to generate the internal computing core of flexible and reconfigurable hardware accelerators. Nevertheless, MDC is not able, as it is, to deploy ready to use accelerators. To address this lack, we conceived a fully automated design flow for coarse-grained reconfigurable and memory-mapped hardware accelerators, which required: a) the definition of a generic co-processing template, the Template Interface Layer; b) the extension of the MDC tool to characterize such a template and deploy the accelerators. This methodology represents, within MPEG Reconfigurable Video Coding studies, the first framework for the automatic generation of reconfigurable hardware accelerators and, as it will be discussed, it may be beneficial also in other contexts of execution with fairly limited adjustments. Results validated the proposed approach in a real use case scenario, comparing the automatically generated co-processor with a previous custom one

    Coarse-grained reconfiguration: dataflow-based power management

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    Power reduction in modern embedded systems design is a challenging issue exacerbated by the complexity and heterogeneity of their architecture. In the field of Reconfigurable Video Coding (RVC), to challenge these issues and cut-down time to market, dataflow-based techniques have been adopted. In particular, to master management and composability of dynamically reconfigurable systems, the authors have developed the multi-dataflow composer. Nevertheless, despite the RVC offers several different tools, in its reference design framework power management is still an open issue. To make some steps forward towards filling this gap, in this study, they address power management for coarse-grained reconfigurable systems combining structural and dynamic strategies, both to be applied at the dataflow level. © The Institution of Engineering and Technology 2015

    Coarse-grained reconfiguration: dataflow-based power management

    No full text
    Power reduction in modern embedded systems design is a challenging issue exacerbated by the complexity and heterogeneity of their architecture. In the field of Reconfigurable Video Coding (RVC), to challenge these issues and cut-down time to market, dataflow-based techniques have been adopted. In particular, to master management and composability of dynamically reconfigurable systems, the authors have developed the multi-dataflow composer. Nevertheless, despite the RVC offers several different tools, in its reference design framework power management is still an open issue. To make some steps forward towards filling this gap, in this study, they address power management for coarse-grained reconfigurable systems combining structural and dynamic strategies, both to be applied at the dataflow level. © The Institution of Engineering and Technology 2015

    A multithread AES accelerator for Cyber-Physical Systems

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    Computing elements of CPSs must be flexible to ensure interoperability; and adaptive to cope with the evolving internal and external state, such as battery level and critical tasks. Cryptography is a common task needed in CPSs to guarantee private communication among different devices. In this work, we propose a reconfigurable FPGA accelerator for AES workloads with different key lengths. The accelerator architecture exploits tagged-dataflow models to support the concurrent execution of multiple threads on the same accelerator. This solution demonstrates to be more resource- and energy-efficient than a set of non-reconfigurable accelerators while keeping high performance and flexibility of execution

    DSE and profiling of multi-context coarse-grained reconfigurable systems

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    The implementation of multi-context systems over coarse-grained reconfigurable platforms could bring several benefits in terms of efficient resource usage and power management. Nevertheless on-the-fly reconfiguration and mapping are not so straightforward and the optimal configuration of the substrate could be extremely time consuming. In this paper we present an early stage design space exploration methodology intended for dataflow-based design flows where multiple input specifications have to be taken into account. The proposed approach, coupled to the Multi-Dataflow Composer tool, has been exploited to assemble the central reconfigurable computing core of an accelerator for video/image processing
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