TAPS: Topology-Aware Intra-Operator Parallelism Strategy Searching Algorithm for Deep Neural Networks

01/11/2023

∙

by   Peng Liang, et al.

∙

0

∙

share

TAPS is a Topology-Aware intra-operator Parallelism strategy Searching algorithm that generates intra-operator parallelism strategies by considering both intra-node and inter-node bandwidth. Most of the existing auto-parallelism works use the communication volume as the communication cost directly when generating strategies, which we prove to be sub-optimal in multi-nodes cases. We design a topology-aware cost model for multi-node intra-operator parallelism strategy searching. Numerical experiments demonstrate that TAPS can generate strategies with up to 85 latest baselines.