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Parallel Scalability

Distributed computing has become an essential mode of big data computing. By contrast, single-user computing is difficult to overcome the high computational complexity of big data orders. On the other side, distributed computing will also increase the communication overhead of parallel computing resources due to data interactivity, thus decreasing the efficiency of big data computing. We are engaged in a novel strategy of balancing computing resources and efficiency, thus cutting overhead costs, including the computing and communication time, producing from distributed computing.

Research Areas

We are engaged in building models of parallel scalability with different complexity level for various computing problems, manage to determine and identify parallel scalability problems of the same complexity, and study design methods of parallel scalable algorithms for types of computing problems. We are devoting to offering an integrated approach to balance relationships between multiple factors when computation performance gets improved.

Related Publications

  • Accelerating Truss Decomposition on Heterogeneous Processors

    Authors: Yulin Che, Zhuohang Lai, Shixuan Sun, Yue Wang, Qiong Luo Name of Conference: International Conference on Very Large Data Bases (VLDB 2020), Aug 31-...

    Yulin Che, Zhuohang Lai, Shixuan Sun, Yue Wang, Qiong Luo International Conference on Very Large Data Bases (VLDB 2020) International Conference on Very Large Data Bases (VLDB 2020), Aug 31- Sept 4, 2020, Tokyo, Japan
  • Dynamic Scaling for Parallel Graph Computations

    Authors: Wenfei Fan, Chunming Hu, Muyang Liu, Ping Lu, Qiang Yin, Jingren Zhou Published in: International Conference on Very Large Data Bases (VLDB 2019),Au...

    Wenfei Fan, Chunming Hu, Muyang Liu, Ping Lu, Qiang Yin, Jingren Zhou International Conference on Very Large Data Bases (VLDB 2019) International Conference on Very Large Data Bases (VLDB 2019),Aug 26-30, 2019, Los Angeles, USA
  • Fast and Accurate SimRank Computation via Forward Local Push and Its Parallelization

    Authors: Yue Wang, Yulin Che, Xiang Lian, Lei Chen, Qiong Luo Published in: IEEE Transactions on Knowledge and Data Engineering(TKDE 2020) Date of Publicat...

    Yue Wang, Yulin Che, Xiang Lian, Lei Chen, Qiong Luo IEEE Transactions on Knowledge and Data Engineering(TKDE 2020) IEEE Transactions on Knowledge and Data Engineering(TKDE 2020)
  • Dynamic Scaling for Parallel Graph Computations

    Authors: Wenfei Fan, Chunming Hu, Muyang Liu, Ping Lu, Qiang Yin, Jingren Zhou Published in: International Conference on Very Large Data Bases (VLDB 2019),Au...

    Wenfei Fan, Chunming Hu, Muyang Liu, Ping Lu, Qiang Yin, Jingren Zhou International Conference on Very Large Data Bases (VLDB 2019) International Conference on Very Large Data Bases (VLDB 2019),Aug 26-30, 2019, Los Angeles, USA
  • Parallelizing Sequential Graph Computations

    Authors: Wenfei Fan, Jingbo Xu , Wenyuan Yu , Jingren Zhou, Xiaojian Luo, Ping Lu, Qiang Yin, Yang Cao, and Ruiqi Xu Published in: ACM Transactions on Databa...

    Wenfei Fan, Jingbo Xu , Wenyuan Yu , Jingren Zhou, Xiaojian Luo, Ping Lu, Qiang Yin, Yang Cao, Ruiqi Xu ACM Transactions on Database Systems (TODS 2018) ACM Transactions on Database Systems (TODS 2018)

 

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