PyTorch Profiler

An in-depth technical exploration of profiling the Attention mechanism in PyTorch, focusing on performance bottlenecks, CUDA kernels, and optimization strategies for modern LLMs like DeepSeek-V3 and Claude 3.5 Sonnet.

A technical deep dive into profiling PyTorch models, transitioning from standard nn.Linear layers to high-performance fused MLP kernels for LLM efficiency.