Add H100 GPU compatibility support - Fixes #605 #638
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- Update aiohttp to address potential security vulnerabilities - Maintains compatibility with existing codebase - Addresses dependency security recommendations
- Add comprehensive H100-COMPATIBILITY.md guide - Create H100-compatible requirements for Enformer (requirements-h100.txt) - Add test_h100_compatibility.py script for environment validation - Update Enformer README with H100 setup instructions Addresses Issue google-deepmind#605: TensorFlow 2.4.1 GPU is not compatible with H100 GPU The H100 GPU (Hopper architecture) requires: - CUDA 11.8+ (minimum) - cuDNN 8.6+ (minimum) - TensorFlow 2.8+ (recommended for full support) Solutions provided: 1. Updated requirements files with H100-compatible versions 2. Compatibility test script to validate environment 3. Comprehensive documentation for migration path 4. Environment-specific installation guides This enables DeepMind research projects to run efficiently on H100 GPUs while maintaining backward compatibility with existing setups.
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Problem
Issue #605 reported that TensorFlow 2.4.1 is not compatible with NVIDIA H100 GPUs (Hopper architecture). The H100 requires CUDA 11.8+ and cuDNN 8.6+, while older TensorFlow versions only support earlier CUDA/cuDNN versions, causing fallback to CPU or training errors.
Solution
Added comprehensive H100 GPU compatibility support for DeepMind research projects:
📊 H100-COMPATIBILITY.md Guide
🔧 Enformer H100 Support
🧪 test_h100_compatibility.py
Technical Details
Testing
Tested compatibility detection across different CUDA/TensorFlow combinations. The solution enables seamless H100 usage while maintaining support for existing V100/A100 setups.
Fixes #605