Donald Bren School of Information and Computer Sciences

Much of the study of text compression attempts to maximize the compression or reduction in the size of a body of text by removing redundancy. Another focus is on speed and on performing compression rapidly. Parallelism offers a myriad of resources for meeting these goals. This paper surveys algorithms, architectures and implementations for parallel text compression. Related concepts from text compression and parallel computation are discussed anda framework for evaluating parallel compression schemes is developed. This framework delineates parallel methods that boost system speed by compressing text concurrently, and approaches that employ multiple compression techniques to improve compression. Also, theoretical and empirical comparisons are reported and areas for future research are suggested.