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Lower precision for higher accuracy: Precision and resolution exploration for shallow water equations

机译:较低的精度以实现更高的精度:浅水方程的精度和分辨率探索

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Accurate forecasts of future climate with numerical models of atmosphere and ocean are of vital importance. However, forecast quality is often limited by the available computational power. This paper investigates the acceleration of a C-grid shallow water model through the use of reduced precision targeting FPGA technology. Using a double-gyre scenario, we show that the mantissa length of variables can be reduced to 14 bits without affecting the accuracy beyond the error inherent in the model. Our reduced precision FPGA implementation runs 5.4 times faster than a double precision FPGA implementation, and 12 times faster than a multi-threaded CPU implementation. Moreover, our reduced precision FPGA implementation uses 39 times less energy than the CPU implementation and can compute a 100×100 grid for the same energy that the CPU implementation would take for a 29×29 grid.
机译:利用大气和海洋的数值模型对未来气候进行准确的预测至关重要。但是,预测质量通常受到可用计算能力的限制。本文通过使用降低精度的FPGA技术来研究C网格浅水模型的加速。使用双回转方案,我们显示变量的尾数长度可以减少到14位,而不会影响超出模型固有误差的精度。我们降低精度的FPGA实施比双精度FPGA实施快5.4倍,比多线程CPU实施快12倍。此外,我们精度降低的FPGA实施所消耗的能量比CPU实施少39倍,并且能够以与CPU实施29×29网格所需的能量相同的能量来计算100×100网格。

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