Release Notes#

Release 2.1.0#

Summary#

This release focuses on security improvements, performance enhancements for newer GPU architectures, and extended sequence length support.

Key Features#

  • Security: Addressed all CVE (Common Vulnerabilities and Exposures) issues

  • cuEquivariance integration: Updated to cuEquivariance 0.7.0 for improved equivariant operations

  • Enhanced B200 support: Enabled trimul kernel optimization for B200 SKUs in PyTorch backend

  • Extended sequence length: Support for longer sequences up to 2048 residues on A100, H100, and B200 GPUs with TensorRT-BioNeMo

  • Telemetry control: NIM Telemetry helps NVIDIA deliver a faster, more reliable experience with greater compatibility across a wide range of environments, while maintaining strict privacy protections and giving users full control.

    Benefits:

    • Enhances performance and reliability: Provides anonymous system and NIM-level insights that help NVIDIA identify bottlenecks, tune performance across hardware configurations, and improve runtime stability.

    • Improves compatibility across deployments: Helps detect and resolve version, driver, and environment compatibility issues early, reducing friction across diverse infrastructure setups.

    • Accelerates troubleshooting and bug resolution: Allows NVIDIA to diagnose errors and regressions faster, leading to quicker support response times and higher overall availability.

    • Informs smarter optimizations and future releases: Real-world, aggregated telemetry data helps guide the optimization of NIM runtimes, model packaging, and deployment workflows, ensuring updates target the scenarios that matter most to users.

    • Protects user privacy and data security: Collects only minimal, anonymous metadata, such as hardware type and NIM version. No user data, input sequences, or prediction results are collected.

    • Fully optional and configurable: Telemetry collection is disabled by default. You can toggle telemetry at any time using environment variables.

    Configuration:

    • Set NIM_TELEMETRY_MODE=0 to disable telemetry (default)

    • Set NIM_TELEMETRY_MODE=1 to enable telemetry

    For more information about data privacy, what is collected, and how to configure telemetry, refer to:

Release 2.0.0#

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-BioNeMo 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

Release 1.2.0#

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.

Release 1.1.0#

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

Release 1.0.0#

Summary#

This is the first release of NVIDIA NIM for OpenFold2.