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Evaluation of variable precision computing with variable precision FFT implementation on FPGA

机译:在FPGA上实现可变精度FFT的可变精度计算的评估

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In the workflow of SKA-SDP (Square Kilometer Array Radio Telescope-Scientific Data Processing), FFT (Fast Fourier Transform) calculation takes a significant proportion of computation overhead. Moreover, FFT computation has to be done within the tight power budget, which existing generic high performance computing architectures cannot meet. To explore power efficiency of FFT computation, this study is designed with initial evaluation of FFT implementation in variable precision on Xilinx ML605 FPGA (field programmable gate array). The FPGA-based implementation of FFT includes a Xilinx IP Core version 7.1, which supports fixed-point and floating-point computation in single precision. The input data width and phase factor width of fixed-point computation can be varied from 8 bits to 34 bits, allowing that calculation accuracy can be adjusted by setting the width. Since single precision is redundant to accuracy requirement of SKA-SDP, fixed-point calculation is designed to emulate single-precision floating point computation. Calculational power dissipation and throughput with different phase factors on FPGA was measured respectively. The final result demonstrates that the implementation on FPGA ensures sufficient precision at a much less power cost compared with floating-point FFT. In other words, this study indicates variable precision computation would be an efficient way to improve power efficiency.
机译:在SKA-SDP(平方公里阵列射电望远镜-科学数据处理)的工作流程中,FFT(快速傅立叶变换)计算占用了大量计算开销。此外,FFT计算必须在紧凑的功率预算内完成,而现有的通用高性能计算架构无法满足这些要求。为了探究FFT计算的能效,本研究在Xilinx ML605 FPGA(现场可编程门阵列)上以可变精度对FFT实现进行了初步评估。基于FPGA的FFT实现包括Xilinx IP内核7.1版,该版本支持单精度的定点和浮点计算。定点计算的输入数据宽度和相位因子宽度可以在8位到34位之间变化,从而可以通过设置宽度来调整计算精度。由于单精度对于SKA-SDP的精度要求而言是多余的,因此定点计算旨在模拟单精度浮点计算。在FPGA上分别测量了具有不同相位因子的计算功耗和吞吐量。最终结果表明,与浮点FFT相比,FPGA上的实现可确保以更低的功耗实现足够的精度。换句话说,这项研究表明可变精度计算将是提高功率效率的有效方法。

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