Unverified85% confidenceFactTime unknown
Dynamo提供分布式KV Cache管理、请求级别的动态路由、GPU资源的细粒度调度等能力
1
Sources
85%
Confidence
Long-term
Relevance
6/1/2026
First Seen
Sources
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Related Claims
UnverifiedThe key states saved in a Dynamo Snapshot include the layout of model weights in GPU memory, the inference engine runtime context, pre-allocated memory pools and buffers, and compiled CUDA kernels and optimized graphs.74% similarUnverifiedvLLM 支持多 GPU 分布式推理，主要采用张量并行策略，底层集成 Megatron-LM 的并行算子并利用 NCCL 库实现 GPU 间通信70% similarUnverifiedIn llama.cpp, the -ngl (number of GPU layers) parameter controls how many layers are placed on the GPU, used to balance speed and model size.68% similarVerifiedllama.cpp supports hybrid CPU and GPU inference (layer offloading), allowing partial model layers to be loaded into GPU VRAM while the remaining layers are kept in memory67% similarVerifiedMainstream quantization solutions include GPTQ (post-training quantization), AWQ (activation-aware weight quantization), and the GGUF format (used by llama.cpp, suitable for CPU inference).66% similar
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