419 citations · 920 across the 71 of their papers we have counts for
13 papers · 1 filter
A Linear Combination-based Method to Construct Proxy Benchmarks for Big Data Workloads
Yikang Yang, Lei Wang, Jianfeng Zhan
During early stages of CPU design, benchmarks can only run on simulators to evaluate CPU performance. However, most big data benchmarks are too huge at code size scale, which cause…
HPC AI500: Representative, Repeatable and Simple HPC AI Benchmarking
Zihan Jiang, Wanling Gao, Fei Tang +6
Recent years witness a trend of applying large-scale distributed deep learning algorithms (HPC AI) in both business and scientific computing areas, whose goal is to speed up the tr…
HPC AI500: The Methodology, Tools, Roofline Performance Models, and Metrics for Benchmarking HPC AI Systems
Zihan Jiang, Lei Wang, Xingwang Xiong +6
The recent years witness a trend of applying large-scale distributed deep learning in both business and scientific computing areas, whose goal is to speed up the training time to a…
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: 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…
BenchCouncil's View on Benchmarking AI and Other Emerging Workloads
Jianfeng Zhan, Lei Wang, Wanling Gao +1
This paper outlines BenchCouncil's view on the challenges, rules, and vision of benchmarking modern workloads like Big Data, AI or machine learning, and Internet Services. We concl…