3,505 research outputs found

    Adaptive Latency Insensitive Protocols

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    Latency-insensitive design copes with excessive delays typical of global wires in current and future IC technologies. It achieves its goal via encapsulation of synchronous logic blocks in wrappers that communicate through a latency-insensitive protocol (LIP) and pipelined interconnects. Previously proposed solutions suffer from an excessive performance penalty in terms of throughput or from a lack of generality. This article presents an adaptive LIP that outperforms previous static implementations, as demonstrated by two relevant cases — a microprocessor and an MPEG encoder — whose components we made insensitive to the latencies of their interconnections through a newly developed wrapper. We also present an informal exposition of the theoretical basis of adaptive LIPs, as well as implementation detail

    Automated Synthesis of SEU Tolerant Architectures from OO Descriptions

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    SEU faults are a well-known problem in aerospace environment but recently their relevance grew up also at ground level in commodity applications coupled, in this frame, with strong economic constraints in terms of costs reduction. On the other hand, latest hardware description languages and synthesis tools allow reducing the boundary between software and hardware domains making the high-level descriptions of hardware components very similar to software programs. Moving from these considerations, the present paper analyses the possibility of reusing Software Implemented Hardware Fault Tolerance (SIHFT) techniques, typically exploited in micro-processor based systems, to design SEU tolerant architectures. The main characteristics of SIHFT techniques have been examined as well as how they have to be modified to be compatible with the synthesis flow. A complete environment is provided to automate the design instrumentation using the proposed techniques, and to perform fault injection experiments both at behavioural and gate level. Preliminary results presented in this paper show the effectiveness of the approach in terms of reliability improvement and reduced design effort

    GCC-Plugin for Automated Accelerator Generation and Integration on Hybrid FPGA-SoCs

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    In recent years, architectures combining a reconfigurable fabric and a general purpose processor on a single chip became increasingly popular. Such hybrid architectures allow extending embedded software with application specific hardware accelerators to improve performance and/or energy efficiency. Aiding system designers and programmers at handling the complexity of the required process of hardware/software (HW/SW) partitioning is an important issue. Current methods are often restricted, either to bare-metal systems, to subsets of mainstream programming languages, or require special coding guidelines, e.g., via annotations. These restrictions still represent a high entry barrier for the wider community of programmers that new hybrid architectures are intended for. In this paper we revisit HW/SW partitioning and present a seamless programming flow for unrestricted, legacy C code. It consists of a retargetable GCC plugin that automatically identifies code sections for hardware acceleration and generates code accordingly. The proposed workflow was evaluated on the Xilinx Zynq platform using unmodified code from an embedded benchmark suite.Comment: Presented at Second International Workshop on FPGAs for Software Programmers (FSP 2015) (arXiv:1508.06320

    FPGA-Based CNN Inference Accelerator Synthesized from Multi-Threaded C Software

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    A deep-learning inference accelerator is synthesized from a C-language software program parallelized with Pthreads. The software implementation uses the well-known producer/consumer model with parallel threads interconnected by FIFO queues. The LegUp high-level synthesis (HLS) tool synthesizes threads into parallel FPGA hardware, translating software parallelism into spatial parallelism. A complete system is generated where convolution, pooling and padding are realized in the synthesized accelerator, with remaining tasks executing on an embedded ARM processor. The accelerator incorporates reduced precision, and a novel approach for zero-weight-skipping in convolution. On a mid-sized Intel Arria 10 SoC FPGA, peak performance on VGG-16 is 138 effective GOPS

    A field programmable gate array based modular motion control platform

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    The expectations from motion control systems have been rising day by day. As the systems become more complex, conventional motion control systems can not achieve to meet all the specifications with optimized results. This creates the necessity of fundamental changes in the infrastructure of the system. Field programmable gate array (FPGA) technology enables the reconfiguration of the digital hardware, thus dissolving the necessity of infrastructural changes for minor manipulations in the hardware even if the system is deployed. An FPGA based hardware system shrinks the size of the hardware hence the cost. FPGAs also provide better power ratings for the systems as well as a more reliable system with improved performance. As a trade off, the development is rather more difficult than software based systems, which also affects the research and development time of the overall system. In this paper a level of abstraction is introduced in order to diminish the requirement of advanced hardware description language (HDL) knowledge for implementing motion control systems thoroughly on an FPGA. The intellectual property library consists of synthesizable hardware modules specifically implemented for motion control purposes. Other parts of a motion control system, like user interface and trajectory generation, are implemented as software functions in order to protect the modularity of the system. There are also several external hardware designs for interfacing and driving various types of actuators
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