Floating-Point 8: An Introduction to Efficient, Lower-Precision AI Training

With the growth of large language models (LLMs), deep learning is advancing both model architecture design and computational efficiency. Mixed precision…

With the growth of large language models (LLMs), deep learning is advancing both model architecture design and computational efficiency. Mixed precision training, which strategically employs lower precision formats like brain floating point 16 (BF16) for computationally intensive operations while retaining the stability of 32-bit floating-point (FP32) where needed, has been a key strategy for…

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Source:: NVIDIA