International Business Machines Corporation

Evangelia Sitaridi

Rene Mueller

Tim Kaldewey

One embodiment provides a method comprising receiving an input data stream, partitioning the input data stream into a plurality of data blocks, and compressing the data blocks utilizing a plurality of processor sets. Each processor set is assigned a data block to compress. The processor sets compress in parallel to exploit inter-block parallelism. Each processor set comprises one or more processors that collaborate in compressing an assigned data block to exploit intra-block parallelism. The method further comprises writing a plurality of compressed data blocks resulting from the compressing to a storage device in encoded form.

Parallel Lempel-Ziv compression for highly-parallel computer architectures

One embodiment provides a method comprising receiving a plurality of encoded and compressed data blocks, decoding the data blocks, and decompressing the data blocks utilizing a plurality of processor sets. Each processor set is assigned a data block to decompress. The processor sets decompress in parallel to exploit inter-block parallelism. Each processor set comprises one or more processors that collaborate in decompressing an assigned data block to exploit intra-block parallelism. The method further comprises generating a final uncompressed output sequence based on uncompressed data blocks resulting from the decompressing.

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Palo Alto, CA, United States of America

Evangelia Sitaridi