114 research outputs found

    A framework for FPGA functional units in high performance computing

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    FPGAs make it practical to speed up a program by defining hardware functional units that perform calculations faster than can be achieved in software. Specialised digital circuits avoid the overhead of executing sequences of instructions, and they make available the massive parallelism of the components. The FPGA operates as a coprocessor controlled by a conventional computer. An application that combines software with hardware in this way needs an interface between a communications port to the processor and the signals connected to the functional units. We present a framework that supports the design of such systems. The framework consists of a generic controller circuit defined in VHDL that can be configured by the user according to the needs of the functional units and the I/O channel. The controller contains a register file and a pipelined programmable register transfer machine, and it supports the design of both stateless and stateful functional units. Two examples are described: the implementation of a set of basic stateless arithmetic functional units, and the implementation of a stateful algorithm that exploits circuit parallelism

    A Micro Power Hardware Fabric for Embedded Computing

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    Field Programmable Gate Arrays (FPGAs) mitigate many of the problemsencountered with the development of ASICs by offering flexibility, faster time-to-market, and amortized NRE costs, among other benefits. While FPGAs are increasingly being used for complex computational applications such as signal and image processing, networking, and cryptology, they are far from ideal for these tasks due to relatively high power consumption and silicon usage overheads compared to direct ASIC implementation. A reconfigurable device that exhibits ASIC-like power characteristics and FPGA-like costs and tool support is desirable to fill this void. In this research, a parameterized, reconfigurable fabric model named as domain specific fabric (DSF) is developed that exhibits ASIC-like power characteristics for Digital Signal Processing (DSP) style applications. Using this model, the impact of varying different design parameters on power and performance has been studied. Different optimization techniques like local search and simulated annealing are used to determine the appropriate interconnect for a specific set of applications. A design space exploration tool has been developed to automate and generate a tailored architectural instance of the fabric.The fabric has been synthesized on 160 nm cell-based ASIC fabrication process from OKI and 130 nm from IBM. A detailed power-performance analysis has been completed using signal and image processing benchmarks from the MediaBench benchmark suite and elsewhere with comparisons to other hardware and software implementations. The optimized fabric implemented using the 130 nm process yields energy within 3X of a direct ASIC implementation, 330X better than a Virtex-II Pro FPGA and 2016X better than an Intel XScale processor

    Making a case for an ARM Cortex-A9 CPU interlay replacing the NEON SIMD unit

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    Automatic synthesis of reconfigurable instruction set accelerators

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    A C compiler for a processor with a reconfigurable functional unit

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    A pipelined configurable gate array for embedded processors

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    In recent years the challenge of high performance, low power retargettable embedded system has been faced with different technological and architectural solutions. In this paper we present a new configurable unit explicitly designed to imple-ment additional reconfigurable pipelined datapaths, suitable for the design of reconfigurable processors. A VLIW recon-figurable processor has been implemented on silicon in a standard 0.18 µm CMOS technology to prove the effective-ness of the proposed unit. Testing on a signal processing algorithms benchmark showed speedups from 4.3x to 13.5x and energy consumption reduction up to 92%

    Configuration prefetching techniques for partial reconfigurable coprocessor with relocation and defragmentation

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