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A new technical paper titled “MLP-Offload: Multi-Level, Multi-Path Offloading for LLM Pre-training to Break the GPU Memory Wall” was published by researchers at Argonne National Laboratory and ...

Together, Pliops and the vLLM Production Stack are delivering unparalleled performance and efficiency for LLM inference. Pliops contributes its expertise in shared storage and efficient vLLM cache ...

As LLMs continue to grow in size and sophistication, their demands for computational power and energy also increase significantly. This growth introduces challenges, such as longer processing times, ...

Forged in collaboration with founding contributors CoreWeave, Google Cloud, IBM Research and NVIDIA and joined by industry leaders AMD, Cisco, Hugging Face, Intel, Lambda and Mistral AI and university ...