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Field Study on Huawei Ascend Non-GPU AI Accelerators for Large-Model Inference
This study examines the engineering challenges of deploying large-model inference workloads on Huawei Ascend 910 non-GPU AI accelerators using CANN and vLLM-Ascend. It focuses on two workloads, including an LLM-based safety and alignment evaluation pipeline.
Understanding the practical costs and limitations of migrating large AI workloads beyond CUDA GPUs is crucial as non-GPU accelerators gain adoption. This insight informs decisions on hardware choices for large-model AI inference.
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