本文提出了一种Cholesky分解细粒度流水线并行算法，该算法可以处理任意规模的数据，可以充分开发FPGA加速器提供的细粒度并行。实验表明，该算法具有很好的可扩展性，在Xilinx XC5VLX330 FPGA上能够集成36个处理单元（PE），当矩阵的阶为16 384、运行频率为200MHz时性能达到14.3 GFLOPS。

This paper presents a finegrained pipeline parallel algorithm for the Cholesky decomposition, which is applicable to the matrices of arbitrary orders and can exploit finegrained parallelism of the FPGA accelerators. The experimental results show this algorithm has good scalability. 36 processing elements (PEs) can be integrated into a Xilinx XC5VLX330 FPGA, achieving a performance of 14.3 Gflops when the matrix order is 16 384 at the clock speed of 200 MHz.