Release Notes

Summary

This release removes HHR-based template processing in favor of explicit mmCIF template support and adds TensorRT integration for new GPU architectures.

Key Changes

• Enhanced GPU support: TensorRT integration for L40S, B200, and RTX 6000 Ada Generation

• Removed: Removed the following functionalities:

  • The downloading and decompressing of a bundled database of structure files at NIM startup
  • The web API accepting input fields containing HHR content
  • The input data processing code that uses the HHR content to select template structures from the de-compressed database of structure files

• Simplified: Template workflow now uses only mmCIF format using explicit_templates, where users can submit one or multiple mmCIF strings as part of their structure prediction requests.

• Reduced footprint: Smaller container size and faster startup without bundled databases

• Migration guide: Refer to the Migration Guide for upgrading from previous versions

Summary

This release introduces support for user-supplied mmCIF input features.

Key Features

• Users can now submit one or multiple mmCIF strings as part of their structure prediction requests.
• The structure prediction network can utilize these user-supplied mmCIF inputs for enhanced flexibility and custom workflows.
• This feature enables new use cases where users provide their own structural templates or data in mmCIF format.

Summary

This release introduces significant performance improvements through TensorRT (TRT) optimization.

Key Features

• Enhanced inference performance using TensorRT optimization
• Improved model execution speed
• Optimized memory usage during inference

Summary

This is the first release of NVIDIA NIM for OpenFold2.