N-ary Huffman Encoding Using High-Degree Trees -- A Performance Comparison

TL;DR

This paper compares the performance of n-ary Huffman encoding with different tree degrees, analyzing compression efficiency and decoding speed, and examines the effect of branch prediction on decoding performance.

Contribution

It provides a comprehensive performance comparison of Huffman encoding using high-degree trees versus traditional binary trees, including the impact of branch prediction.

Findings

Higher degree trees can improve decoding speed.

Performance varies with tree degree and branch prediction.

Optimal tree degree depends on specific application constraints.

Abstract

In this paper we implement an n-ary Huffman Encoding and Decoding application using different degrees of tree structures. Our goal is to compare the performance of the algorithm in terms of compression ratio, decompression speed and weighted path length when using higher degree trees, compared to the 2-ary Huffman Code. The Huffman tree degrees that we compare are 2-ary, 3-ary, 4-ary, 5-ary, 6-ary, 7-ary, 8-ary and 16-mal. We also present the impact that branch prediction has on the performance of the n-ary Huffman Decoding.