Serving frontier MoE and multimodal models on Ascend 910 via vLLM-Ascend is feasible but dominated by engineering cost from incomplete operators, fragile parallelism, kernel faults, and weak observability.
Switch Transformers: Scaling to trillion parameter models with simple and efficient sparsity.Journal of Machine Learning Research, 23(120):1–39, 2022
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On the Limitations of Non-GPU AI Accelerators for Large-Model Inference: A Field Study of MoE and Multimodal Serving on Huawei Ascend
Serving frontier MoE and multimodal models on Ascend 910 via vLLM-Ascend is feasible but dominated by engineering cost from incomplete operators, fragile parallelism, kernel faults, and weak observability.