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Resource Efficient Parallel Architectures for Linear Matrix Algebra in Real Time Adaptive Control Algorithms on Reconfigurable Logic

机译:在可重构逻辑上实时自适应控制算法中的线性矩阵代数的资源有效并行架构

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Parallel and systolic structures for matrix algebra algorithms have been around for quite a long time. Various implementations of different numerical techniques exist. With the advent of reconfigurable logic, especially FPGAs, a need has arisen to revisit these architectures and produce resource efficient versions of these algorithms. We have produced resource efficient parallel architectures for LU Decomposition and Triangular Matrix Inversion, keeping in view data computational rate requirements for real time control systems. These architectures decrease memory logic resources considerably and also maintain excellent clock period results. They also have the capability to be mapped over each other thereby further reducing resource usage and also providing us with the additional facility of Matrix Multiplication.
机译:矩阵代数算法的平行和收缩结构已经存在了很长时间。存在不同数值技术的各种实现。随着可重构逻辑,尤其是FPGA的出现,需要重新审视这些算法的这些架构并产生这些算法的资源有效版本。我们为LU分解和三角矩阵反转产生了资源有效的并行架构,保持了实时控制系统的数据计算率要求。这些架构显着降低了内存逻辑资源,并且还可以保持出色的时钟周期结果。它们还具有彼此映射的能力,从而进一步降低资源使用,并为我们提供矩阵乘法的附加设施。

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