419 citations · 518 across the 7 of their papers we have counts for
7 papers
Data Motifs: A Lens Towards Fully Understanding Big Data and AI Workloads
Wanling Gao, Jianfeng Zhan, Lei Wang +9
The complexity and diversity of big data and AI workloads make understanding them difficult and challenging. This paper proposes a new approach to modelling and characterizing big…
Data Dwarfs: A Lens Towards Fully Understanding Big Data and AI Workloads
Wanling Gao, Jianfeng Zhan, Lei Wang +6
The complexity and diversity of big data and AI workloads make understanding them difficult and challenging. This paper proposes a new approach to characterizing big data and AI wo…
A Dwarf-based Scalable Big Data Benchmarking Methodology
Wanling Gao, Lei Wang, Jianfeng Zhan +7
Different from the traditional benchmarking methodology that creates a new benchmark or proxy for every possible workload, this paper presents a scalable big data benchmarking meth…
Cosine Normalization: Using Cosine Similarity Instead of Dot Product in Neural Networks
Chunjie Luo, Jianfeng Zhan, Lei Wang +1
Traditionally, multi-layer neural networks use dot product between the output vector of previous layer and the incoming weight vector as the input to activation function. The resul…
Characterizing and Subsetting Big Data Workloads
Zhen Jia, Jianfeng Zhan, Lei Wang +5
Big data benchmark suites must include a diversity of data and workloads to be useful in fairly evaluating big data systems and architectures. However, using truly comprehensive be…
BDGS: A Scalable Big Data Generator Suite in Big Data Benchmarking
Zijian Ming, Chunjie Luo, Wanling Gao +4
Data generation is a key issue in big data benchmarking that aims to generate application-specific data sets to meet the 4V requirements of big data. Specifically, big data generat…