AI Matrix: A Deep Learning Benchmark for Alibaba Data Centers
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Abstract (arXiv)
Alibaba has China's largest e-commerce platform. To support its diverse businesses, Alibaba has its own large-scale data centers providing the computing foundation for a wide variety of software applications. Among these applications, deep learning (DL) has been playing an important role in delivering services like image recognition, objection detection, text recognition, recommendation, and language processing. To build more efficient data centers that deliver higher performance for these DL applications, it is important to understand their computational needs and use that information to guide the design of future computing infrastructure. An effective way to achieve this is through benchmarks that can fully represent Alibaba's DL applications.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 23 Sep 2019.
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Citing papers per year: 2022: 4.
4 papers.
- 2022Towards Fair Federated Recommendation Learning: Characterizing the Inter-Dependence of System and Data Heterogeneitycited by 17
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- 2022SAIH: A Scalable Evaluation Methodology for Understanding AI Performance Trend on HPC Systemscited by 0
- 2022SAIH: A Scalable Evaluation Methodology for Understanding AI Performance Trend on HPC Systems7 Dec 2022
- 2022Deep Learning Inference Frameworks Benchmark9 Oct 2022
- 2022An Overview of the Data-Loader Landscape: Comparative Performance Analysis27 Sep 2022
- 2022Towards Fair Federated Recommendation Learning: Characterizing the Inter-Dependence of System and Data Heterogeneity30 May 2022