G
Gang Chen
Researcher at Zhejiang University
Publications - 48
Citations - 2642
Gang Chen is an academic researcher from Zhejiang University. The author has contributed to research in topics: Tree (data structure) & Deep learning. The author has an hindex of 15, co-authored 48 publications receiving 1755 citations. Previous affiliations of Gang Chen include Beijing Institute of Technology.
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Journal ArticleDOI
Untangling Blockchain: A Data Processing View of Blockchain Systems
TL;DR: This paper conducts a comprehensive evaluation of three major blockchain systems based on BLOCKBENCH, namely Ethereum, Parity, and Hyperledger Fabric, and discusses several research directions for bringing blockchain performance closer to the realm of databases.
Proceedings ArticleDOI
BLOCKBENCH: A Framework for Analyzing Private Blockchains
TL;DR: Blockbench as mentioned in this paper is an evaluation framework for analyzing private blockchains, which can be used to assess blockchains' viability as another distributed data processing platform, while helping developers to identify bottlenecks and accordingly improve their platforms.
Posted Content
Untangling Blockchain: A Data Processing View of Blockchain Systems
TL;DR: In this article, the authors present a benchmarking framework for understanding performance of private blockchains against data processing workloads, and conduct a comprehensive evaluation of three major blockchain systems based on BLOCKBENCH, namely Ethereum, Parity and Hyperledger Fabric.
Journal ArticleDOI
Database Meets Deep Learning: Challenges and Opportunities
TL;DR: Possible improvements for deep learning systems from a database perspective are discussed, and database applications that may benefit from deep learning techniques are analyzed.
Posted Content
BLOCKBENCH: A Framework for Analyzing Private Blockchains
TL;DR: BLOCKBENCH is described, the first evaluation framework for analyzing private blockchains and it serves as a fair means of comparison for different platforms and enables deeper understanding of different system design choices, and is released for public use.