NVIDIA NIM for OpenFold3

OpenFold3

• Overview
  • Key Features
  • Tooling
  • Advantages of NIMs
• Release Notes for NVIDIA NIM for OpenFold3
  • Release 1.1.0
    • Summary
    • New Features
      • Structural Template Support
      • Additional GPU Support
      • Telemetry Control
    • Supported Features
  • Release 1.0.0
    • Summary
    • Supported Features
      • Entity Types
      • Multiple Entities and Complexes
      • Multiple Sequence Alignment (MSA) Support
      • Inference Parameters
      • Structure Templates
      • Output Formats
• Prerequisites
  • Known issues
  • Installing NVIDIA Drivers
    • Option 1: Interactive Installation (Local Machine)
    • Option 2: Command Line Installation (Remote Machine/SSH)
    • Troubleshooting Driver Installation
  • Verifying GPU Access
  • NGC (NVIDIA GPU Cloud) Account
  • NGC CLI Tool
• Supported Hardware
  • GPU
  • Storage
  • CPU and System Memory
• Getting Started
  • Pull and run the NIM
  • Submit Health-Check Requests to the NIM as it Starts Up
  • Run Inference
• Example Requests
  • Using the OpenFold3 NIM
    • Predict Structure
      • Request Structure
      • Molecule Specification
      • MSA Structure
      • Recommended Workflow
      • Response Structure
  • Additional Examples
    • Protein-Only Structure Prediction
    • Protein-DNA Complex
    • Protein-Ligand with SMILES
    • Protein with Structural Templates
  • Field Reference
    • Request-Level Fields
    • Input-Level Fields
    • Molecule Fields
    • AlignmentFileRecord Fields
    • StructuralTemplate Fields
    • Important Validation Rules
  • MSA Format Requirements
• Template Processing
  • Overview
  • How Template Processing Works
    • Chain Extraction
    • Sequence Alignment
    • Chain Scoring
    • Template Selection
    • Structure Guidance
  • Best Practices
    • When to Use Templates
    • Template Selection
    • Multi-Chain CIF Files
  • Template Requirements
  • Configuration
  • Related Documentation
• Performance in OpenFold3 NIM
  • NIM Accuracy
  • Factors Affecting NIM Performance
    • Hardware Factors
    • Input Complexity
    • Model Configuration
  • Performance Characteristics
    • Typical Runtimes
  • Performance Results on H100 (NVIDIA H100 80GB)
    • Structure Prediction Performance
    • Performance Analysis
    • Configuration
  • Performance Optimization Tips
    • Backend Selection
    • General Optimization Tips
  • Reproducing Performance Benchmarks
    • Overview
    • Prerequisites
      • Install the OpenStructure Docker Image
      • Download Reference Structures
    • Preparing Input JSON Files
      • Example Input JSON Structure
      • Create Input JSON Files
    • Benchmarking Script
    • Understanding lDDT Metric
    • Running Benchmarks for Performance Table
      • Step 1: Prepare the scripts
      • Step 2: Run the complete benchmark workflow
      • Quick Summary:
    • Expected Output Format
  • Troubleshooting
    • General Performance Issues
    • Backend-Specific Issues
    • Benchmarking Issues
• Configuration Alternatives at Runtime
  • Start the OpenFold3 NIM
  • Using an Alternative Port for OpenFold3 NIM Requests
  • Backend Optimization Options
    • Running with PyTorch+cuEquivariance
    • Running with PyTorch+DeepSpeed
  • Template Configuration Options
    • Configuring Template Chain Selection Threshold
• Observability
  • About Observability
  • Health Check Endpoints
    • Readiness Check
    • Liveness Check
  • Metrics
    • Available Metrics Summary
  • Collecting Metrics with OpenTelemetry Collector
    • Prerequisites
    • OpenTelemetry Collector Configuration
    • Running the Collector
  • Related Information
• API Reference
  • OpenAPI Schema
    • Reference
• EULA