We develop a novel solution, zero redundancy optimizer (zero), to optimize memory, vastly improving training speed while increasing the model size that can be efficiently. Zero has two sets of optimizations: We develop a novel solution, zero redundancy optimizer (zero), to optimize memory, vastly improving training speed while increasing the model size that can be efficiently trained.
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We develop a novel solution, zero redundancy optimizer (zero), to optimize memory, vastly improving training speed while increasing the model size that can be efficiently. ( zero 是 deepspeed 中的一个开源 dl 训练优化库，对大模型训练加速有非常好的优化效果 ) 由于 device memory 是. We develop a novel solution, zero redundancy optimizer (zero), to optimize memory, vastly improving training speed while increasing the model size that can be efficiently trained.
Memory optimizations toward training trillion parameter models.
Existing solutions such as data an. 本文提出了zero redundancy optimizer (zero)来优化内存，不但可以更快的训练模型，而且还可以训练更大的模型。 zero消除了数据并行和模型并行中的冗余内存使用同时维. Large deep learning models offer significant accuracy gains, but training billions to trillions of parameters is challenging.
