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cs.LG2024
Breaking MLPerf Training: A Case Study on Optimizing BERT
Yongdeok Kim, Jaehyung Ahn, Myeongwoo Kim +11
Speeding up the large-scale distributed training is challenging in that it requires improving various components of training including load balancing, communication, optimizers, et…
cs.LG2023
vTrain: A Simulation Framework for Evaluating Cost-effective and Compute-optimal Large Language Model Training
Jehyeon Bang, Yujeong Choi, Myeongwoo Kim +2
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-ef…