Block-update parallel processing QRD-RLS algorithm for throughput improvement with low power consumption

Lijun Gao, K. Parhi
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引用次数: 3

Abstract

In this paper, a block-update parallel processing algorithm is proposed for increasing the throughput of the CORDIC-based QRD-RLS filtering with low power consumption. The proposed algorithm employs single-state-update parallel processing, and with this algorithm, the throughput of a block-by-block weight-update QRD-RLS filter can be increased at the cost of linear increase in hardware resource. However, the proposed algorithm does not change the iteration bounds and clock frequency of the QRD-RLS filters. As a result, the functional units need not be pipelined and the power consumption only increases linearly instead of quadratically. Due to non-pipelining and less power consumption, a higher folding factor can be used for a folding transformation and a great reduction in hardware resource can be achieved without exceeding the physical limitation on pipelining level and power density. Therefore, the proposed algorithm can serve as an important stage in designing and mapping a QRD-RLS filter onto physical hardware or computing resources, and thus is better for both ASIC chip design and parallel computing when block-by-block weight-update is applicable.
块更新并行处理QRD-RLS算法在低功耗下提高吞吐量
为了提高基于cordic的QRD-RLS滤波的吞吐量和低功耗,本文提出了一种块更新并行处理算法。该算法采用单状态更新并行处理,以硬件资源线性增加为代价,提高了逐块权重更新QRD-RLS滤波器的吞吐量。然而,该算法不改变QRD-RLS滤波器的迭代边界和时钟频率。因此,功能单元不需要流水线,功耗只增加线性而不是二次。由于非流水线化和低功耗,可以使用更高的折叠系数进行折叠转换,在不超过流水线化水平和功率密度的物理限制的情况下,可以大大减少硬件资源。因此,该算法可以作为设计QRD-RLS滤波器并将其映射到物理硬件或计算资源的重要阶段,因此在适用分块权重更新的情况下,更适合ASIC芯片设计和并行计算。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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