An efficient parallelization of longest prefix match and application on data compression

Abstract

In this article, we describe a new approach to parallelize longest prefix match (LPM) algorithm through bit parallelism, also known as bit-vector approach. This approach makes use of bit-wise computations and leverages bit parallelism. The proposed parallel algorithm will be demonstrated in dictionary-based lossless data compression on general-purpose graphics processing units (GPGPUs). One of the main contributions of this work is redesigning the core part of the data compression algorithm and replacing it with the newly proposed bit-vector LPM solution. Using bit parallelism is a fundamentally new approach for data compression and promising in performance for hybrid CPU-GPU environments. The implementation of the new compression algorithm on GPUs improves the performance of the compression process compared to the previous attempts. Moreover, the bit-vector approach opens new opportunities for improvement and increases the applicability to popular heterogeneous environments.