Sreeharsha Udayashankar, Abdelrahman Baba, and Samer Al-Kiswany, University of Waterloo
Content-defined Chunking (CDC) algorithms are critical to data deduplication and can be categorized into two families: hash-based and hashless. Hashless chunking algorithms are faster than their hash-based counterparts, especially when accelerated using the Single Instruction Multiple Data (SIMD) capabilities of modern CPUs. However, they achieve lower deduplication space savings on certain datasets.
We present WideCDC, a technique to improve the deduplication efficiency of hashless CDC algorithms by using wide regions of multiple bytes to determine chunk boundaries instead of individual bytes. Existing SIMD acceleration techniques for hashless CDC miss chunk boundaries when using wide regions, as they do not account for overlaps. To address this while preserving performance, WideCDC uses novel Accumulated Extreme Byte Searches and Gated Range Scans. By evaluating WideCDC on real-world datasets, we show that it improves the deduplication ratios of hashless chunking algorithms up to 2.95× while achieving 2.04× higher chunking throughput than existing vector-accelerated techniques.
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