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Breaking MLPerf Training: A Case Study on Optimizing BERT
Speeding up the large-scale distributed training is challenging in that it requires improving various components of training including load balancing, communication, optimizers, etc.
vTrain: A Simulation Framework for Evaluating Cost-effective and Compute-optimal Large Language Model Training
As large language models (LLMs) become widespread in various application domains, a critical challenge the AI community is facing is how to train these large AI models in a cost-effective manner.
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