An amateur ML researcher is seeking advice on optimizing GPU costs for a personal drug repurposing project. The researcher is using Google Vertex AI with A100 GPUs for training NBFnets on biomedical graphs, but is encountering high costs and memory limitations that force smaller batch sizes than reported in a key paper. They are asking the machine learning community for guidance on determining sufficient training duration, cost-effective alternatives to on-demand cloud GPUs, and potential memory optimization techniques. AI
IMPACT N/A
RANK_REASON User is asking for advice on a personal project, not reporting a new development.
AI-generated summary · Google Gemini · from 1 sources. How we write summaries →