AI Matrix: A Deep Learning Benchmark for Alibaba Data Centers
This work addresses the need for tailored benchmarks to optimize data center performance for Alibaba's specific deep learning workloads, but it is incremental as it focuses on a single company's applications.
The paper tackles the problem of designing efficient data centers for deep learning applications at Alibaba by introducing AI Matrix, a benchmark to represent their computational needs, with the result being a tool to guide future infrastructure design.
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.