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Real time phase-slopes calculations by correlations using FPGAs

机译:实时相位斜坡通过使用FPGA的相关性计算

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ELT laser guide star wavefront sensors are planned to handle an expected amount of data to be overwhelmingly large(1600x1600 pixels at 700 fps). According to the calculations involved, the solutions must consider to run on specializedhardware as Graphical Processing Units (GPUs) or Field Programmable Gate Arrays (FPGAs), among others. In the case of a Shack-Hartmann wavefront sensor is finally selected, the wavefront slopes can be computed usingcentroid or correlation algorithms. Most of the developments are designed using centroid algorithms, but precision oughtto be taken in account too, and then correlation algorithms are really competitive. This paper presents an FPGA-based wavefront slope implementation, capable of handling the sensor output stream in amassively parallel approach, using a correlation algorithm previously tested and compared to the centroid algorithm.Time processing results are shown, and they demonstrate the ability of the FPGA integer arithmetic in the resolution ofAO problems. The selected architecture is based in today's commercially available FPGAs which have a very limited amount ofinternal memory. This limits the dimensions used in our implementation, but this also means that there is a lot of marginto move real-time algorithms from the conventional processors to the future FPGAs, obtaining benefits from itsflexibility, speed and intrinsically parallel architecture.
机译:计划采用ELT激光导灯波前传感器处理预期的数据量,以压倒性大(1600x1600像素为700 fps)。根据所涉及的计算,解决方案必须考虑在专业硬件上运行作为图形处理单元(GPU)或现场可编程门阵列(FPGA)等。在最终选择Shack-Hartmann波前传感器的情况下,可以使用cortroid或相关算法计算波前斜率。大多数发展都是使用质心算法设计的,但也考虑到精度,然后相关算法真正具有竞争力。本文提出了一种基于FPGA的波前倾斜实现,能够使用先前测试的相关算法并与质心算法进行比较的相关算法来处理传感器输出流。显示结果,并证明了FPGA的能力oa问题分辨率的整数算术。所选架构基于当今的商业上可用的FPGA,该FPGA具有非常有限的Internal Memory。这限制了我们实施中使用的尺寸,但这也意味着有很多Marginto从传统处理器移动到未来FPGA的实时算法,从其象限,速度和本质上平行架构中获益。

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