A GPU kernel operates concurrently across numerous processing units. In transformer models such as LLaMA or GPT-2, computational resources are primarily consumed by kernels handling matrix multiplication, softmax, layer normalization, and attention mechanisms. These components reside within specialized libraries or are automatically produced by PyTorch's compilation system.
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