The compress() function performs similar operations on a collection of text, however it relies on a dictionary and an expanding string to be tokenized in a dictrionary. This could potentially be paralellized through a divide and conquer strategy where gpu blocks with shared caches share their own dictionary dictionaries and iterate over their own block of text. This, however would not be particularly useful because LZW compression relies on a globally accessible dictionary that can be continuously modified. Having multiple threads try to access the same dictionary tokens in global memory would create race conditions, and creating block-local dictionaries in shared memory would reduce the efficacy of having a large globally available dictionary to tokenize strings. What all of this means is that LZW compression would probably be a poor candidate for parallelization due to the way that parallel memory would try to update the token dictionary.