Oct 14, 2019 · Results show that weight/gradient communication during training takes almost 62% of the total execution time among all our workloads on average.

In this paper, we characterize deep learning training workloads from Platform of Artificial Intelligence (PAI) in Alibaba. We establish an analytical framework ...

Oct 14, 2019 · In this paper, we characterize deep learning training workloads from Platform of Artificial Intelligence (PAI) in Alibaba. We establish an ...

An analytical framework is established to investigate detailed execution time breakdown of various workloads using different training architectures, ...

A series of studies have characterized training workloads from the production GPU datacenters, including Microsoft [71], SenseTime [62] and Alibaba [144, 149].

Apr 20, 2022 · Bibliographic details on Characterizing Deep Learning Training Workloads on Alibaba-PAI.

Characterizing deep learning training workloads on alibaba-pai. M Wang, C Meng, G Long, C Wu, J Yang, W Lin, Y Jia. 2019 IEEE international symposium on ...

We present a comprehensive study about the characteristics of DL jobs and resource management. First, we perform a large-scale analysis of real-world job ...

Characterizing deep learning training workloads on alibaba-pai. M Wang, C Meng, G Long, C Wu, J Yang, W Lin, Y Jia. 2019 IEEE International Symposium on ...

One critical issue for efficiently operating practical AI clouds, is to characterize the computing and data transfer demands of these workloads, and more ...