Monday 08 September 2025
A team of researchers has developed a novel method for accelerating data chunking in deduplication systems, which could significantly improve the performance and efficiency of cloud storage.
Deduplication is a crucial technology used to reduce the amount of storage space needed by identifying and eliminating duplicate files. It works by breaking down large files into smaller chunks, called hashes, and then comparing these hashes to identify duplicates. However, this process can be slow and computationally intensive, especially for large datasets.
To address this issue, researchers have developed a new algorithm that uses vector CPU instructions, such as SSE/AVX, to accelerate the data chunking phase of deduplication. This approach is designed to take advantage of modern CPU architectures by leveraging the power of parallel processing.
The new algorithm, called VectorCDC, works by dividing the incoming data into small chunks and then using vector instructions to calculate the hash values for each chunk in parallel. This allows the algorithm to process multiple chunks simultaneously, resulting in significant performance improvements over traditional deduplication methods.
The researchers tested their algorithm on a range of different CPU architectures, including Intel, AMD, ARM, and IBM, and found that it achieved an average speedup of 8.35 times compared to existing vector-accelerated techniques. This could translate into substantial reductions in storage costs and improved system performance for cloud storage providers.
The implications of this research are significant, as it has the potential to improve the efficiency and scalability of cloud storage systems. With the amount of data being generated and stored online continuing to grow at an exponential rate, any improvements in deduplication technology could have a major impact on the ability of cloud storage providers to meet demand.
The researchers believe that their algorithm is particularly well-suited for use in large-scale cloud storage systems, where the need for efficient deduplication is greatest. They also suggest that it could be used in combination with other optimization techniques to further improve system performance.
Overall, this research has the potential to make a significant contribution to the field of data deduplication and cloud storage, and could have important implications for the way we store and manage digital data in the future.
Cite this article: “Accelerating Data Chunking in Deduplication Systems with VectorCDC”, The Science Archive, 2025.
Data Deduplication, Cloud Storage, Vector Cpu Instructions, Parallel Processing, Hash Values, Chunking, Algorithm, Vectorcdc, Performance Improvement, Scalability
