论文标题
通过离线分析模拟ML系统的性能
Simulating Performance of ML Systems with Offline Profiling
论文作者
论文摘要
我们提倡基于离线分析的模拟是一种更好地理解和改善复杂ML系统的有前途的方法。我们的方法使用基于操作级别的分析和基于数据流的仿真来确保其为所有框架和ML模型提供统一和自动化的解决方案，并且通过考虑真实系统中的各种并行化策略也可以准确。
We advocate that simulation based on offline profiling is a promising approach to better understand and improve the complex ML systems. Our approach uses operation-level profiling and dataflow based simulation to ensure it offers a unified and automated solution for all frameworks and ML models, and is also accurate by considering the various parallelization strategies in a real system.
