於可程式化系統晶片平台實現向量量化器快速碼字搜尋硬體電路之研究

Abstract

本論文針對向量量化器（VQ）編碼端的硬體實現提出了一個新的VLSI架構，採用部分距離搜尋（PDS）演算法作為編碼端最佳碼字搜尋的法則。在大多數的軟體應用中，部份距離搜尋演算法可以適度的加速碼字搜尋。本論文提出的新部份距離搜尋演算法適合硬體實現，使用子空間搜尋（Subspace search）、位元平面縮減（Bitplane reduction）和多係數累積（Multiple-coefficient accumulation）三種技術來有效的降低面積複雜度（Area complexity）以及計算latency（Computation latency）。多模組架構的PDS專用硬體電路可以同時針對不同的輸入向量進行編碼，以達到更進一步的編碼加速。我們提出的硬體架構被內嵌於軟體核心中央處理器（Softcore CPU）來進行實際的效能量測。實驗結果顯示出我們的架構提供了一個符合成本效益的向量量化器編碼系統硬體實作解決方案，並且擁有高吞吐量（throughput）和高正確性（fidelity）。

This paper presents a novel VLSI architecture for hardware realization of vector quantizer (VQ) encoders using partial distance search (PDS). In most applications, the PDS is adopted as a software approach for attaining moderate codeword search acceleration. In this paper, a novel PDS algorithm well-suited for hardware realization is proposed. The algorithm employs subspace search, bitplane reduction and multiple-coefficient accumulation techniques for the effective reduction of the area complexity and computation latency. Concurrent encoding of different input vectors for further encoding acceleration are also allowed by the employment of multiple-module PDS. The proposed architecture has been embedded in a softcore CPU for physical performance measurement. Experimental results shows that the architecture provides a cost-effective solution to the hardware realization of VQ encoding systems where both high throughput and high fidelity are desired.