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Accelerating SVD computation on FPGAs for DSP systems

机译:在DSP系统的FPGA上加速SVD计算

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摘要

This paper presents a fast and generic hardware architecture for channel matrix singular value decomposition (SVD) in massive multiple-input multiple-output (MIMO) system. A fixed-pointed pipelined hardware architecture which implemented Hestenes-Jacobi method was developed to reduce the computing time in order to adapt real time processing requirements. Our proposed design was implemented on a Xilinx Kinect-7 series FPGA, which achieved an 8.5x to 15.3x improvement in speed when compared to software implementation by using MATALB and a 2.1x to 6.3x speed-up when compared to using general-purpose GPU programming scheme in processing 8×8 to 128×128 matrices.
机译:本文提出了一种用于大规模多输入多输出(MIMO)系统中的通道矩阵奇异值分解(SVD)的快速通用硬件体系结构。开发了采用Hestenes-Jacobi方法的定点流水线硬件架构,以减少计算时间,以适应实时处理要求。我们的拟议设计是在Xilinx Kinect-7系列FPGA上实现的,与使用MATALB的软件实现相比,速度提高了8.5倍至15.3倍,与使用通用软件相比,速度提高了2.1倍至6.3倍处理8×8至128×128矩阵的GPU编程方案。

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