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MICRO2023顶会

Path Forward Beyond Simulators: Fast and Accurate GPU Execution Time Prediction for DNN Workloads

Ying Li, Yifan Sun, Adwait Jog

2023年份
16被引次数
5顶会引用

摘要

Today, DNNs’ high computational complexity and sub-optimal device utilization present a major roadblock to democratizing DNNs. To reduce the execution time and improve device utilization, researchers have been proposing new system design solutions, which require performance models (especially GPU models) to help them with pre-product concept validation. Currently, researchers have been utilizing simulators to predict execution time, which provides high flexibility and acceptable accuracy, but at the cost of a long simulation time. Simulators are becoming increasingly impractical to model today’s large-scale systems and DNNs, urging us to find alternative lightweight solutions.

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