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The success of Transformer models has pushed the deep learning model scale tobillions of parameters. Due to the limited memory resource of a single GPU,However, the best practice for choosing the optimal parallel strategy is stilllacking, since it requires domain expertise in both deep learning and parallelcomputing.  The Colossal-AI system addressed the above challenge by introducing a unifiedinterface to scale your sequential code of model training to distributedenvironments. It supports parallel training methods such as data, pipeline,tensor, and sequence parallelism, as well as heterogeneous training methodsintegrated with zero redundancy optimizer. Compared to the baseline system,Colossal-AI can achieve up to 2.76 times training speedup on large-scalemodels.

Colossal-AI: A Unified Deep Learning System For Large-Scale Parallel Training