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Parallel Matrix Multiplication Design for Monocular SLAM

机译:单眼血液的并联矩阵乘法设计

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摘要

As software profiling is conducted to determine which section of program demand high processing computation in monocular SLAM inverse depth estimation, matrix multiplication is identified to be one of the most time consuming process. The processing is more demanding when the number of features inserted to the image is increased. For that reason, this paper proposes a parallel matrix multiplier design which could accelerate the execution time. In this design, Field Programmable Gate Array (FPGA) technology which allows parallel design to be implemented is presented. The design manipulates existing classical matrix multiplication algorithm into an architecture that would enable data to be processed concurrently.
机译:作为软件分析,以确定单眼血液逆深度估计中的节目需要高处理计算,矩阵乘法被识别为最耗时的过程之一。当插入图像的特征数量增加时,处理更加苛刻。因此,本文提出了一种并行矩阵乘法器设计,可以加速执行时间。在这种设计中,呈现允许实施平行设计的现场可编程门阵列(FPGA)技术。该设计将现有的经典矩阵乘法算法操纵到能够同时处理数据的架构中。

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