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Tradeoff of FPGA design of floating-point transcendental functions

机译:浮点超越函数的FPGA设计折衷

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Several scientific applications need a high precision computation of transcendental functions. This paper presents a hardware implementation of a parameterizable floating-point library for computing sine, cosine and arctangent functions using both CORDIC algorithm and Taylor series expansion for different bit-width representations. The results include the accuracy as a design criterion of the proposed hardware architectures; therefore, a tradeoff analysis between the cost in area and the number of iterations against the error associated is done in order to choose a suitable format for computing transcendental functions. The proposed architectures were validated using the Matlab results as a statistical estimator in order to compute the Mean Square Error (MSE). Synthesis and simulation results demonstrate the correctness and effectiveness of the implemented hardware transcendental functions.
机译:一些科学应用需要对先验函数进行高精度计算。本文介绍了可参数化浮点库的硬件实现,该库可使用CORDIC算法和泰勒级数展开针对不同的位宽表示来计算正弦,余弦和反正切函数。结果包括将精度作为所提出的硬件体系结构的设计标准。因此,需要在面积成本和迭代次数之间进行权衡分析,以克服相关的误差,以便选择合适的格式来计算先验函数。为了计算均方误差(MSE),使用Matlab结果作为统计估计量对提出的体系结构进行了验证。综合和仿真结果证明了所实现的硬件先验功能的正确性和有效性。

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