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High throughput Cholesky decomposition based on FPGA

机译:基于FPGA的高吞吐量Cholesky分解

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Cholesky decomposition has wide applications in solving many engineering and scientific problems. Acceleration is an important issue in many of these problems. In this paper, a hardware-based LLT Cholesky decomposition featuring high throughput has been presented to solve wiener filtering based on the minimum square error criterion. To achieve the best efficiency, the hardware-based implementation has been realized by fixed-point multiple structures and various pipeline stages. Parallel properties have been exploited to improve the throughput. Results have shown that a significant speedup has been achieved compared to the software-based approach.
机译:霍尔斯基分解法在解决许多工程和科学问题方面具有广泛的应用。加速是许多这些问题中的重要问题。为了解决基于最小平方误差准则的维纳滤波,提出了一种具有高吞吐量的基于硬件的LL T Cholesky分解算法。为了获得最佳效率,已经通过定点多结构和各种流水线阶段实现了基于硬件的实现。已经利用并行属性来提高吞吐量。结果表明,与基于软件的方法相比,已实现了显着的加速。

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