implementation detail · filed under inference & serving
Data-parallel vision encoding
Uses data parallelism for multimodal vision encoding.
Also called --mm-encoder-tp-mode data.
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Evidence
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For multimodal workloads, use --mm-encoder-tp-mode data for data-parallel vision encoding and --mm-processor-cache-type shm for shared-memory caching of preprocessed multimodal inputs.
usedinference servingin vLLMvLLM
Filed alongside
Other methods under inference & serving :: serving parallelism.
Attention data parallelismDeepEPPrefill-decode disaggregationEncoder-Prefill-Decode disaggregationTensor parallelism (degree 4)Tensor parallelism (degree 8)Topology-aware NVLink domain placementZero-copy fused token permutation and unpermutationExpert parallelismFused reduce-scatter/all-gather collectivesIdentical cache-layout pinning across prefill and decode poolsLow-precision MoE combineRound-robin routing for prefill-decode disaggregationTensor parallelism for MoE layersTensorRT-LLM all-reduce backendToken migration for balanced expert placement