419 citations · 430 across the 6 of their papers we have counts for
6 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…
10-millisecond Computing
Gang Lu, Jianfeng Zhan, Tianshu Hao +1
Despite computation becomes much complex on data with an unprecedented scale, we argue computers or smart devices should and will consistently provide information and knowledge to…
Isolate First, Then Share: a New OS Architecture for Datacenter Computing
Gang Lu, Jianfeng Zhan, Chongkang Tan +7
This paper presents the "isolate first, then share" OS model in which the processor cores, memory, and devices are divided up between disparate OS instances and a new abstraction,…
BigDataBench-MT: A Benchmark Tool for Generating Realistic Mixed Data Center Workloads
Rui Han, Shulin Zhan, Chenrong Shao +5
Long-running service workloads (e.g. web search engine) and short-term data analysis workloads (e.g. Hadoop MapReduce jobs) co-locate in today's data centers. Developing realistic…
BigDataBench: a Big Data Benchmark Suite from Internet Services
Lei Wang, Jianfeng Zhan, Chunjie Luo +12
As architecture, systems, and data management communities pay greater attention to innovative big data systems and architectures, the pressure of benchmarking and evaluating these…