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High-Performance System-on-Chip-Based Accelerator System for Polynomial Matrix Multiplications

机译:用于多项式矩阵乘法的高性能基于芯片的加速器系统

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Polynomial matrix computations, such as polynomial matrix multiplication (PMM) and eigenvalue factorization of parahermitian matrices, have played an important role in a growing number of applications, in recent times. However, the computational complexity and expense of such operations impose a profound limit on their applicability. In a recent paper, we introduced a systolic array-based parallel architecture for PMM, which was adequately efficient, but limited in its application. In this paper, we propose a second-generation hardware solution which boasts more versatility, efficiency and scalability compared to our previous design. This is achieved through the design of a highly versatile PMM accelerator which supports polynomial matrices of any size, as a component of the embedded system developed within the Xilinx Zynq-7000 AP SoC. Experimental results demonstrate the efficiency and effectiveness of our novel SoC-based PMM accelerator in the context of subband coding, where maximum speedups of 85x and 33x are accomplished, without compromising the accuracy, in comparison with two highly optimized and multi-threaded software-only implementations running on a dual-core ARM Cortex-A9 processor and a Intel Core i7-4510U CPU, respectively.
机译:近年来,多项式矩阵计算(如多项式矩阵乘法(PMM)和准hermitian矩阵的特征值分解)在越来越多的应用程序中发挥了重要作用。但是,这种操作的计算复杂性和费用对其应用性施加了很大的限制。在最近的一篇论文中,我们为PMM引入了一种基于脉动阵列的并行体系结构,该体系结构虽然效率很高,但是其应用受到限制。在本文中,我们提出了第二代硬件解决方案,与我们以前的设计相比,它具有更多的通用性,效率和可扩展性。这是通过设计高度通用的PMM加速器来实现的,该加速器支持任何大小的多项式矩阵,作为Xilinx Zynq-7000 AP SoC内开发的嵌入式系统的组成部分。实验结果表明,与两个高度优化的多线程纯软件相比,在子带编码的情况下,我们新颖的基于SoC的PMM加速器的效率和有效性得以实现,在不影响精度的情况下,可以实现85x和33x的最大加速。实现分别在双核ARM Cortex-A9处理器和Intel Core i7-4510U CPU上运行。

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