31 citations · 46 across the 5 of their papers we have counts for
5 papers
AIBench Training: Balanced Industry-Standard AI Training Benchmarking
Fei Tang, Wanling Gao, Jianfeng Zhan +30
Earlier-stage evaluations of a new AI architecture/system need affordable benchmarks. Only using a few AI component benchmarks like MLPerfalone in the other stages may lead to misl…
AIBench: An Agile Domain-specific Benchmarking Methodology and an AI Benchmark Suite
Wanling Gao, Fei Tang, Jianfeng Zhan +31
Domain-specific software and hardware co-design is encouraging as it is much easier to achieve efficiency for fewer tasks. Agile domain-specific benchmarking speeds up the process…
AIBench: An Industry Standard Internet Service AI Benchmark Suite
Wanling Gao, Fei Tang, Lei Wang +22
Today's Internet Services are undergoing fundamental changes and shifting to an intelligent computing era where AI is widely employed to augment services. In this context, many inn…
Benchmarking Big Data Systems: State-of-the-Art and Future Directions
Rui Han, Zhen Jia, Wanling Gao +2
The great prosperity of big data systems such as Hadoop in recent years makes the benchmarking of these systems become crucial for both research and industry communities. The compl…
Identifying Dwarfs Workloads in Big Data Analytics
Wanling Gao, Chunjie Luo, Jianfeng Zhan +5
Big data benchmarking is particularly important and provides applicable yardsticks for evaluating booming big data systems. However, wide coverage and great complexity of big data…