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Accelerating Verifiable Queries over Blockchain Database System Using Processing-in-memory
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AI
DOI：10.1145/3768318.png)
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Abstract
En 中文
Blockchain database systems, such as Ethereum and vChain, suffer from limited memory bandwidth and high memory access latency when retrieving user-requested data. Emerging processing-in-memory (PIM) technologies are promising to accelerate users' queries, by enabling low-latency memory access and aggregated memory bandwidth scaling with the number of PIM modules. In this article, we present Panther, the first PIM-based blockchain database system supporting efficient verifiable queries. Blocks are distributed to PIM modules for high parallelism with low inter-PIM communication cost, managed by a regression-based model. For load balance across PIM modules, data are adaptively promoted and demoted between the host and PIM sides. In multiple datasets, Panther achieves up to 23.6x speedup for verifiable queries and reduces metadata storage by orders of magnitude compared to state-of-the-art designs on real PIM hardware.
Keywords:
Processing in memory
blockchain
merkle hash tree
pointer chasing
verifiable query
Journal
A
IF:
1.8
Papers:
96
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1.1K
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