SlideDP: Scaling Host-Resident LLM Fine-Tuning Across Multiple GPUs
SlideDP scales host-resident multi-GPU LLM fine-tuning, beating offload baselines and nearing FSDP2 on Qwen3-14B.
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Stories tagged #multi-gpu
Scalability Analysis of Distributed Kolmogorov-Arnold Network Training on High-Performance Computing Systems
An empirical study shows distributed Kolmogorov-Arnold Network training reaches 74.7% parallel efficiency at 8 A100 GPUs, with overheads driven by All-Reduce choices.