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Re-pair is a grammar-based compression algorithm. It achieves higher compression rates for text, graph, and tree than other general compression algorithms. While Re-pair is linear-time algorithm, it is slower than other algorithms in practice. In this paper, we present Parallel Re-pair, a novel variant that enables parallel processing of Re-pair. In Parallel Re-pair, Re-pair is executed on CPU cores with a shared dictionary to synchronize allocations of variables. Thus, compressed strings can be simply merged without reallocation of variables. Our experiments show that Parallel Re-Pair significantly reduces compression time with up to 16 or 32 CPU cores.
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |