vllm
https://github.com/vllm-project/vllm
Python
A high-throughput and memory-efficient inference and serving engine for LLMs
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- Issues
- [ROCm] Fused Triton W8A16 fp8 GEMM for gfx90a + aiter arch-gate error message fix
- [Bug]: Block-FP8 tensor-parallel shards smaller than a quantization block fail to load
- [ROCm][Perf] Replace aceorch.einsum with batched_gemm_bf16 for Tâ¤32
- [Bug]: NemotronParseForConditionalGeneration does not tie lm_head.weight to decoder.embed_tokens.weight, produces garbage output
- [Performance][Model] Fuse GLM indexer attention projections
- [Bug][Spec Decode] All-NaN logits row is laundered into an out-of-vocab token id by the rejection sampler (device assert far from origin); NaN-metric blind spot on the verify path; uninit-scratch audit
- DFlash speculator `capture()` logs "Capturing model ..." even when nothing is captured â makes drafter-capture state unobservable
- [Bug]: In a Python environment, when requesting a model deployed with vLLM and the output mode is streaming, there is a low probability that the connection is established but the model does not receive the request.
- [Attention][Spec Decode] Enable varlen Mamba2 decode for adaptive verification
- [Discussion] Tiered SWA/Mamba checkpointing (HBM tail + store periodic) + recompute backfill for divergent hybrid prefix hits
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