Although Evo 2 supports the processing of very long DNA sequences, the following points should be noted for optimal performance:
Hardware Configuration:
- Recommended 40B parametric model (requires multi-GPU support)
- Graphics memory needs to be large enough, recommended to be no less than 40GB per GPU
Optimization Strategies:
- chunking: Split the sequence into multiple blocks to be processed sequentially
- teacher prompting: Using teacher prompting technology to improve efficiency
- Lower the temperature: Reduce computational burden and produce more stable results
Performance Monitoring:
- utilization
nvidia-smiMonitoring GPU Usage - Checking the Multi-GPU Allocation Status of the Vortex Framework
Please note that long sequence forward propagation is currently time-consuming, and it is recommended to test it in a non-production environment before performing large-scale computation.
This answer comes from the articleEvo2: An Open Source BioAI Tool to Support Genome Modeling and DesignThe
May not be reproduced without permission:AI productivity tools " What do I need to be aware of when Evo 2 processes sequences up to 1 million bases long?
