mirror of
https://github.com/MLSysBook/TinyTorch.git
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45a9cef548
- Removed 01_setup module (archived to archive/setup_module) - Renumbered all modules: tensor is now 01, activations is 02, etc. - Added tito setup command for environment setup and package installation - Added numeric shortcuts: tito 01, tito 02, etc. for quick module access - Fixed view command to find dev files correctly - Updated module dependencies and references - Improved user experience: immediate ML learning instead of boring setup
25 lines
946 B
YAML
25 lines
946 B
YAML
description: "Build professional profiling infrastructure to measure and analyze performance.\n\
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Students learn to create timing, memory, and operation profilers that reveal\nbottlenecks\
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\ and guide optimization decisions. Performance detective work that \nmakes optimization\
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\ exciting through data-driven insights.\n"
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difficulty: advanced
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estimated_hours: 8-10
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exports:
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- tinytorch.profiling
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learning_objectives:
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- Build accurate timing infrastructure with statistical rigor
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- Implement memory profiling and allocation tracking
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- Create FLOP counting for computational analysis
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- Master profiling methodology for bottleneck identification
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- Connect profiling insights to ML systems optimization decisions
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name: Profiling
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number: 15
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prerequisites:
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- Module 14: Transformers (need models to profile)
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skills_developed:
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- Performance measurement
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- Bottleneck identification
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- Profiling tool development
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- Statistical analysis
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type: systems
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