PyTorch Profiler is a comprehensive performance analysis tool for deep learning models that enables detailed CPU, GPU, and memory profiling with customizable recording schedules. It integrates with De
epSpeed, TensorBoard, and VS Code, offering visualization through Google's Perfetto trace viewer.
Reasons to Read -- Learn:
how to implement step-by-step performance profiling in PyTorch with specific code examples for training loops, including how to configure wait, warmup, and active recording periods
how to track and analyze both CPU and GPU activities in your deep learning models, with practical examples of memory consumption monitoring and visualization
how to integrate PyTorch Profiler with popular development tools like TensorBoard, VS Code, and Google's Perfetto trace viewer for better visualization and analysis of profiling data
publisher: deepspeed.ai
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