Reproduce “Vectorized Sequence-Based Chunking for Data Deduplication” on OpenResearch
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About this paper
Sreeharsha Udayashankar, Samer Al-Kiswany
SeqCDC, a new content-defined chunking algorithm from the University of Waterloo, significantly boosts data deduplication throughput by detecting monotonic byte sequences and leveraging vector acceleration. It achieves up to 30.5 GB/s with AVX-512, representing a 10x improvement over the fastest unaccelerated methods, while maintaining competitive deduplication efficiency within 4% of existing algorithms.
Key insights
- Chunk boundaries can be effectively identified using lightweight monotonic byte sequence detection instead of complex hash functions or extremum searches.
- Content-aware data skipping, by identifying and jumping over "unfavorable regions," significantly improves throughput at a minimal cost to deduplication efficiency.
- Developing algorithms from the ground up to be vector-friendly, rather than retrofitting existing ones, is crucial for maximizing performance on modern CPU architectures.
Summary by alphaXiv.
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