4 citations · 5 across the 4 of their papers we have counts for
4 papers · 1 filter
AIBench Scenario: Scenario-distilling AI Benchmarking
Wanling Gao, Fei Tang, Jianfeng Zhan +7
Modern real-world application scenarios like Internet services consist of a diversity of AI and non-AI modules with huge code sizes and long and complicated execution paths, which…
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…
AI-oriented Medical Workload Allocation for Hierarchical Cloud/Edge/Device Computing
Tianshu Hao, Jianfeng Zhan, Kai Hwang +2
In a hierarchically-structured cloud/edge/device computing environment, workload allocation can greatly affect the overall system performance. This paper deals with AI-oriented med…