AI Matrix: A Deep Learning Benchmark for Alibaba Data Centers
arXiv:1909.10562
Abstract
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.
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Cited by in corpus (5)
- XSP: Across-Stack Profiling and Analysis of Machine Learning Models on GPUs
- The Design and Implementation of a Scalable DL Benchmarking Platform
- AI Tax: The Hidden Cost of AI Data Center Applications
- CPR: Understanding and Improving Failure Tolerant Training for Deep Learning Recommendation with Partial Recovery
- AIPerf: Automated machine learning as an AI-HPC benchmark