octoml-profile

Overview

octoml-profile is a community-maintained PyTorch profiler from OctoML. It provides tools to measure and analyze the performance of PyTorch models, helping developers identify bottlenecks in training or inference.

Best for

Best for
PyTorch developers needing a simple, open-source profiler for model performance analysis

Use cases

• Profiling PyTorch model training loops to find slow operations
• Analyzing GPU utilization and memory usage during inference
• Comparing performance across different model architectures or batch sizes

Notes

octoml-profile is a community-maintained PyTorch profiler from OctoML. It provides tools to measure and analyze the performance of PyTorch models, helping developers identify bottlenecks in training or inference.

114 stars on GitHub. Last updated 2023-04-24. Licensed Apache-2.0.

Use cases

• Profiling PyTorch model training loops to find slow operations
• Analyzing GPU utilization and memory usage during inference
• Comparing performance across different model architectures or batch sizes

Pros

• Lightweight and focused specifically on PyTorch workflows
• Open source with 114 GitHub stars, indicating community interest
• Integrates with existing PyTorch code with minimal changes

Cons

• Limited to PyTorch, not usable with other frameworks like TensorFlow
• Community project may have less frequent updates or support than vendor-backed tools
• Documentation and examples may be sparse compared to more mature profilers

Indexed from awesome-llmops and enriched against its public facts.