Content by yuvmaz (1)

yuvmaz breaks down the MegaTrain paper’s approach to training 100B+ parameter LLMs on a single GPU by treating GPU memory as a cache and streaming layers from host memory/NVMe. The post connects the technique to Azure NC-series VM choices, storage throughput, PCIe constraints, and cost/performance trade-offs.