Data compression: methods and theory
Data compression: methods and theory
A parallel architecture for high-speed data compression
Journal of Parallel and Distributed Computing
P-complete problems in data compression
Theoretical Computer Science
Image and Text Compression
Parallel algorithms for the static dictionary compression
DCC '95 Proceedings of the Conference on Data Compression
Work-Optimal Parallel Decoders for LZ2 Data Compression
DCC '00 Proceedings of the Conference on Data Compression
DCC '00 Proceedings of the Conference on Data Compression
Discrete Applied Mathematics - 12th annual symposium on combinatorial pattern matching (CPM)
Discrete Applied Mathematics
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We consider sublinear massively parallel algorithms for compressing text with respect to a static dictionary. Algorithms for the PRAM model can do this optimally in O(m+log(n)) time with n processors, where m is the length of the longest entry in the dictionary and n is the length of the input string. We consider what is perhaps the most practical model of massively parallel computation imaginable: a linear array of processors where each processor is connected only to its left and right neighbors. We present an algorithm which in time O(km+mlog(m)) with n/(km) processors is guaranteed to be within a factor of (k+1)/k of optimal, for any integer k/spl ges/1. We also present experiments indicating that performance may be even better in practice.