Approximating Huffman Codes in Parallel
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Using Lin-Kernighan algorithm for look-up table compression to improve code density
GLSVLSI '06 Proceedings of the 16th ACM Great Lakes symposium on VLSI
Approximating Huffman codes in parallel
Journal of Discrete Algorithms
Efficient code density through look-up table compression
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Instruction splitting for efficient code compression
Proceedings of the 44th annual Design Automation Conference
Instruction re-encoding facilitating dense embedded code
Proceedings of the conference on Design, automation and test in Europe
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ACM Transactions on Design Automation of Electronic Systems (TODAES)
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IEEE Transactions on Very Large Scale Integration (VLSI) Systems
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ACSAC'07 Proceedings of the 12th Asia-Pacific conference on Advances in Computer Systems Architecture
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We describe an efficient algorithm for decoding canonical Huffman codes with look-up tables. Further, the dependence between the probability of the least frequent symbol and the length of its codeword in a Huffman code is investigated. We design a method for estimating the source file size for a given Huffman code. We show how this method can be used to estimate a 驴good驴 size for the look-up table, used in the decoding.