A high-throughput and memory-efficient inference and serving engine for LLMs
Mirrored from https://github.com/tduncan-lum/Nvidia-Optimization-Stack---VLLM.git
Synced Nov 7, 19:00 UTC
Add @MatthewBonanni to CODEOWNERS (#35207)
Signed-off-by: Matthew Bonanni <mbonanni@redhat.com>
Matthew Bonanni committed
Feb 24, 2026 at 12:45 UTC
a9e15e040de12f2aaa97c6c71d7b1540cbe2561f
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.github/CODEOWNERS
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@@ -5,14 +5,14 @@
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/vllm/compilation @zou3519 @youkaichao @ProExpertProg
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/vllm/distributed/kv_transfer @NickLucche @ApostaC @orozery
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/vllm/lora @jeejeelee
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-/vllm/model_executor/layers/attention @LucasWilkinson
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+/vllm/model_executor/layers/attention @LucasWilkinson @MatthewBonanni
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/vllm/model_executor/layers/fused_moe @mgoin @pavanimajety
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/vllm/model_executor/layers/quantization @mgoin @robertgshaw2-redhat @tlrmchlsmth @yewentao256 @pavanimajety
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/vllm/model_executor/layers/mamba @tdoublep
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/vllm/model_executor/model_loader @22quinn
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/vllm/model_executor/layers/batch_invariant.py @yewentao256
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/vllm/multimodal @DarkLight1337 @ywang96 @NickLucche @tjtanaa
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-/vllm/vllm_flash_attn @LucasWilkinson
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+/vllm/vllm_flash_attn @LucasWilkinson @MatthewBonanni
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CMakeLists.txt @tlrmchlsmth @LucasWilkinson
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# Any change to the VllmConfig changes can have a large user-facing impact,
@@ -43,14 +43,14 @@ CMakeLists.txt @tlrmchlsmth @LucasWilkinson
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/vllm/tool_parsers @aarnphm @chaunceyjiang
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# vLLM V1
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-/vllm/v1/attention @LucasWilkinson
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+/vllm/v1/attention @LucasWilkinson @MatthewBonanni
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/vllm/v1/attention/backend.py @WoosukKwon @zhuohan123 @youkaichao @alexm-redhat @njhill
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/vllm/v1/attention/backends/mla @pavanimajety
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/vllm/v1/attention/backends/flashinfer.py @mgoin @pavanimajety
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/vllm/v1/attention/backends/triton_attn.py @tdoublep
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/vllm/v1/core @WoosukKwon @robertgshaw2-redhat @njhill @ywang96 @alexm-redhat @heheda12345 @ApostaC @orozery
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/vllm/v1/sample @22quinn @houseroad @njhill
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-/vllm/v1/spec_decode @benchislett @luccafong
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+/vllm/v1/spec_decode @benchislett @luccafong @MatthewBonanni
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/vllm/v1/structured_output @mgoin @russellb @aarnphm @benchislett
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/vllm/v1/kv_cache_interface.py @heheda12345
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/vllm/v1/kv_offload @ApostaC @orozery