Improved Branch Prediction for Just-in-Time Decompression of Canonical Huffman Bytecode Streams

Jeong, Chisoon; Su, Hang; Burgstaller, Bernd

doi:10.1007/978-94-017-8798-7_82

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2021

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“…In 2014, C. Jeong et al [11] presented a method for improved branch prediction in Huffman decoding for streams of data via elimination of indirect branching instructions.…”

Section: Introductionmentioning

confidence: 99%

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

Xezonakis¹,

Leivadaros²

2021

IJCA

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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.

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“…In 2014, C. Jeong et al [11] presented a method for improved branch prediction in Huffman decoding for streams of data via elimination of indirect branching instructions.…”

Section: Introductionmentioning

confidence: 99%

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

Xezonakis¹,

Leivadaros²

2021

IJCA

View full text Add to dashboard Cite

show abstract

Improved Branch Prediction for Just-in-Time Decompression of Canonical Huffman Bytecode Streams

Cited by 1 publication

References 14 publications

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

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

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