Merge branch 'main' into fix_ada_fp8_groupgemm

Author: inocsin

.github/workflows/blossom-ci.yml

@@ -40,8 +40,298 @@ jobs:
         startsWith(github.event.comment.body, '/bot skip --comment') ||
         startsWith(github.event.comment.body, '/bot reuse-pipeline') ||
         startsWith(github.event.comment.body, '/bot kill')) && contains(
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-        github.actor)
+        fromJson('[
+        "2ez4bz",
+        "a-mccarthy",
+        "aalanwyr",
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+        "amirkl94",
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+        "amukkara",
+        "anish-shanbhag",
+        "arekay",
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+        "davidmlw",
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+        "dc3671",
+        "dcampora",
+        "dcaox",
+        "dhansen-nvidia",
+        "Dido0o0",
+        "djns99",
+        "DomBrown",
+        "dominicshanshan",
+        "dongfengy",
+        "dongjiyingdjy",
+        "dongxuy04",
+        "DylanChen-NV",
+        "ebarilanM",
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+        "EmmaQiaoCh",
+        "eopXD",
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+        "farazkh80",
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+        "hchings",
+        "hello-11",
+        "heyuhhh",
+        "hijkzzz",
+        "hlu1",
+        "HuiGao-NV",
+        "hvagadia",
+        "hypdeb",
+        "hyukn",
+        "inocsin",
+        "ISEEKYAN",
+        "ixlmar",
+        "IzzyPutterman",
+        "Jackch-NV",
+        "JadoTu",
+        "jaedeok-nvidia",
+        "jdemouth-nvidia",
+        "JennyLiu-nv",
+        "jershi425",
+        "jgangani",
+        "jhaotingc",
+        "jiaganc",
+        "jiahanc",
+        "Jie-Fang",
+        "jiefangz-nv",
+        "jieli-matrix",
+        "jinyangyuan-nvidia",
+        "jinzh-nvidia",
+        "jmydurant",
+        "johncalesp",
+        "joyang-nv",
+        "jthomson04",
+        "juney-nvidia",
+        "JunyiXu-nv",
+        "JyChang012",
+        "kaiyux",
+        "kanghui0204",
+        "karljang",
+        "katec846",
+        "Kefeng-Duan",
+        "KingsleyLiu-NV",
+        "kris1025",
+        "kunlunl",
+        "kxdc",
+        "kyleliang-nv",
+        "laikhtewari",
+        "lancelly",
+        "LarryXFly",
+        "latency1024",
+        "leslie-fang25",
+        "lfr-0531",
+        "liji-nv",
+        "limin2021",
+        "linda-stadter",
+        "lingjiew",
+        "LinPoly",
+        "litaotju",
+        "longlee0622",
+        "lowsfer",
+        "lucaslie",
+        "lucifer1004",
+        "MartinMarciniszyn",
+        "MatthiasKohl",
+        "mayani-nv",
+        "meenchen",
+        "mikeiovine",
+        "milesial",
+        "MinaHuai",
+        "ming-wei",
+        "mk-nvidia",
+        "mlefeb01",
+        "moraxu",
+        "MrGeva",
+        "Naveassaf",
+        "nekorobov",
+        "netanel-haber",
+        "niukuo",
+        "Njuapp",
+        "nv-guomingz",
+        "nv-yilinf",
+        "nvamyt",
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+        "nvchenghaoz",
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+        "nvjullin",
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+        "NVShreyas",
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+        "nvzhou",
+        "nzmora-nvidia",
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+        "pamelap-nvidia",
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+        "pengbowang-nv",
+        "PerkzZheng",
+        "poweiw",
+        "qiangxu1996",
+        "qiaoxj07",
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+        "qsang-nv",
+        "raayandhar",
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+        "rosenrodt",
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+        "ruoqianguo",
+        "rzilberstein-nvidia",
+        "samuellees",
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+        "shyeh25",
+        "SimengLiu-nv",
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+        "sugunav14",
+        "sunnyqgg",
+        "Superjomn",
+        "suyoggupta",
+        "sychen52",
+        "symphonylyh",
+        "syuoni",
+        "Tabrizian",
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+        "xuanzic",
+        "xueweilnvidia",
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+        "xxi-nv",
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+        "yibinl-nvidia",
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+        "yilin-void",
+        "yingcanw",
+        "yiqingy0",
+        "yizhang-nv",
+        "yuanjings-nvda",
+        "yuanjingx87",
+        "yuantailing",
+        "Yuening-wa",
+        "yufeiwu-nv",
+        "yuhengxnv",
+        "yuhsuan-t",
+        "yuki-666",
+        "yumin066",
+        "yunruis",
+        "yuxianq",
+        "yweng0828",
+        "zackyoray",
+        "zbpatel",
+        "zeroepoch",
+        "zerollzeng",
+        "zhanga5",
+        "zhangcl",
+        "ZhanruiSunCh",
+        "zhengd-nv",
+        "zhenhuaw-me",
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+        "zhhuang-nv",
+        "zhou-yuxin",
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+        "zihaok",
+        "ziyixiong-nv",
+        "zongfeijing"
+        ]'), github.actor)
     steps:
       - name: Check if comment is issued by authorized person
         run: blossom-ci

README.md

@@ -10,51 +10,51 @@ state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs.<
 [![python](https://img.shields.io/badge/python-3.10-green)](https://www.python.org/downloads/release/python-31012/)
 [![cuda](https://img.shields.io/badge/cuda-13.0.0-green)](https://developer.nvidia.com/cuda-downloads)
 [![trt](https://img.shields.io/badge/TRT-10.13.2-green)](https://developer.nvidia.com/tensorrt)
-[![version](https://img.shields.io/badge/release-1.2.0rc2-green)](./tensorrt_llm/version.py)
-[![license](https://img.shields.io/badge/license-Apache%202-blue)](./LICENSE)
+[![version](https://img.shields.io/badge/release-1.2.0rc3-green)](https://github.com/NVIDIA/TensorRT-LLM/blob/main/tensorrt_llm/version.py)
+[![license](https://img.shields.io/badge/license-Apache%202-blue)](https://github.com/NVIDIA/TensorRT-LLM/blob/main/LICENSE)
 
-[Architecture](./docs/source/torch/arch_overview.md)&nbsp;&nbsp;&nbsp;|&nbsp;&nbsp;&nbsp;[Performance](./docs/source/performance/perf-overview.md)&nbsp;&nbsp;&nbsp;|&nbsp;&nbsp;&nbsp;[Examples](https://nvidia.github.io/TensorRT-LLM/quick-start-guide.html)&nbsp;&nbsp;&nbsp;|&nbsp;&nbsp;&nbsp;[Documentation](https://nvidia.github.io/TensorRT-LLM/)&nbsp;&nbsp;&nbsp;|&nbsp;&nbsp;&nbsp;[Roadmap](https://github.com/NVIDIA/TensorRT-LLM/issues?q=is%3Aissue%20state%3Aopen%20label%3Aroadmap)
+[Architecture](https://nvidia.github.io/TensorRT-LLM/developer-guide/overview.html)&nbsp;&nbsp;&nbsp;|&nbsp;&nbsp;&nbsp;[Performance](https://nvidia.github.io/TensorRT-LLM/developer-guide/perf-overview.html)&nbsp;&nbsp;&nbsp;|&nbsp;&nbsp;&nbsp;[Examples](https://nvidia.github.io/TensorRT-LLM/quick-start-guide.html)&nbsp;&nbsp;&nbsp;|&nbsp;&nbsp;&nbsp;[Documentation](https://nvidia.github.io/TensorRT-LLM/)&nbsp;&nbsp;&nbsp;|&nbsp;&nbsp;&nbsp;[Roadmap](https://github.com/NVIDIA/TensorRT-LLM/issues?q=is%3Aissue%20state%3Aopen%20label%3Aroadmap)
 
 ---
 <div align="left">
 
 ## Tech Blogs
 
 * [10/13] Scaling Expert Parallelism in TensorRT LLM (Part 3: Pushing the Performance Boundary)
-✨ [➡️ link](./docs/source/blogs/tech_blog/blog14_Scaling_Expert_Parallelism_in_TensorRT-LLM_part3.md)
+✨ [➡️ link](https://nvidia.github.io/TensorRT-LLM/blogs/tech_blog/blog14_Scaling_Expert_Parallelism_in_TensorRT-LLM_part3.html)
 
 * [09/26] Inference Time Compute Implementation in TensorRT LLM
-✨ [➡️ link](./docs/source/blogs/tech_blog/blog13_Inference_Time_Compute_Implementation_in_TensorRT-LLM.md)
+✨ [➡️ link](https://nvidia.github.io/TensorRT-LLM/blogs/tech_blog/blog13_Inference_Time_Compute_Implementation_in_TensorRT-LLM.html)
 
 * [09/19] Combining Guided Decoding and Speculative Decoding: Making CPU and GPU Cooperate Seamlessly
-✨ [➡️ link](./docs/source/blogs/tech_blog/blog12_Combining_Guided_Decoding_and_Speculative_Decoding.md)
+✨ [➡️ link](https://nvidia.github.io/TensorRT-LLM/blogs/tech_blog/blog12_Combining_Guided_Decoding_and_Speculative_Decoding.html)
 
 * [08/29] ADP Balance Strategy
-✨ [➡️ link](./docs/source/blogs/tech_blog/blog10_ADP_Balance_Strategy.md)
+✨ [➡️ link](https://nvidia.github.io/TensorRT-LLM/blogs/tech_blog/blog10_ADP_Balance_Strategy.html)
 
 * [08/05] Running a High-Performance GPT-OSS-120B Inference Server with TensorRT LLM
-✨ [➡️ link](./docs/source/blogs/tech_blog/blog9_Deploying_GPT_OSS_on_TRTLLM.md)
+✨ [➡️ link](https://nvidia.github.io/TensorRT-LLM/blogs/tech_blog/blog9_Deploying_GPT_OSS_on_TRTLLM.html)
 
 * [08/01] Scaling Expert Parallelism in TensorRT LLM (Part 2: Performance Status and Optimization)
-✨ [➡️ link](./docs/source/blogs/tech_blog/blog8_Scaling_Expert_Parallelism_in_TensorRT-LLM_part2.md)
+✨ [➡️ link](https://nvidia.github.io/TensorRT-LLM/blogs/tech_blog/blog8_Scaling_Expert_Parallelism_in_TensorRT-LLM_part2.html)
 
 * [07/26] N-Gram Speculative Decoding in TensorRT LLM
-✨ [➡️ link](./docs/source/blogs/tech_blog/blog7_NGram_performance_Analysis_And_Auto_Enablement.md)
+✨ [➡️ link](https://nvidia.github.io/TensorRT-LLM/blogs/tech_blog/blog7_NGram_performance_Analysis_And_Auto_Enablement.html)
 
 * [06/19] Disaggregated Serving in TensorRT LLM
-✨ [➡️ link](./docs/source/blogs/tech_blog/blog5_Disaggregated_Serving_in_TensorRT-LLM.md)
+✨ [➡️ link](https://nvidia.github.io/TensorRT-LLM/blogs/tech_blog/blog5_Disaggregated_Serving_in_TensorRT-LLM.html)
 
 * [06/05] Scaling Expert Parallelism in TensorRT LLM (Part 1: Design and Implementation of Large-scale EP)
-✨ [➡️ link](./docs/source/blogs/tech_blog/blog4_Scaling_Expert_Parallelism_in_TensorRT-LLM.md)
+✨ [➡️ link](https://nvidia.github.io/TensorRT-LLM/blogs/tech_blog/blog4_Scaling_Expert_Parallelism_in_TensorRT-LLM.html)
 
 * [05/30] Optimizing DeepSeek R1 Throughput on NVIDIA Blackwell GPUs: A Deep Dive for Developers
-✨ [➡️ link](./docs/source/blogs/tech_blog/blog3_Optimizing_DeepSeek_R1_Throughput_on_NVIDIA_Blackwell_GPUs.md)
+✨ [➡️ link](https://nvidia.github.io/TensorRT-LLM/blogs/tech_blog/blog3_Optimizing_DeepSeek_R1_Throughput_on_NVIDIA_Blackwell_GPUs.html)
 
 * [05/23] DeepSeek R1 MTP Implementation and Optimization
-✨ [➡️ link](./docs/source/blogs/tech_blog/blog2_DeepSeek_R1_MTP_Implementation_and_Optimization.md)
+✨ [➡️ link](https://nvidia.github.io/TensorRT-LLM/blogs/tech_blog/blog2_DeepSeek_R1_MTP_Implementation_and_Optimization.html)
 
 * [05/16] Pushing Latency Boundaries: Optimizing DeepSeek-R1 Performance on NVIDIA B200 GPUs
-✨ [➡️ link](./docs/source/blogs/tech_blog/blog1_Pushing_Latency_Boundaries_Optimizing_DeepSeek-R1_Performance_on_NVIDIA_B200_GPUs.md)
+✨ [➡️ link](https://nvidia.github.io/TensorRT-LLM/blogs/tech_blog/blog1_Pushing_Latency_Boundaries_Optimizing_DeepSeek-R1_Performance_on_NVIDIA_B200_GPUs.html)
 
 ## Latest News
 * [08/05] 🌟 TensorRT LLM delivers Day-0 support for OpenAI's latest open-weights models: GPT-OSS-120B [➡️ link](https://huggingface.co/openai/gpt-oss-120b) and GPT-OSS-20B [➡️ link](https://huggingface.co/openai/gpt-oss-20b)
@@ -63,11 +63,11 @@ state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs.<
 * [05/22] Blackwell Breaks the 1,000 TPS/User Barrier With Meta’s Llama 4 Maverick
 ✨ [➡️ link](https://developer.nvidia.com/blog/blackwell-breaks-the-1000-tps-user-barrier-with-metas-llama-4-maverick/)
 * [04/10] TensorRT LLM DeepSeek R1 performance benchmarking best practices now published.
-✨ [➡️ link](./docs/source/blogs/Best_perf_practice_on_DeepSeek-R1_in_TensorRT-LLM.md)
+✨ [➡️ link](https://nvidia.github.io/TensorRT-LLM/blogs/Best_perf_practice_on_DeepSeek-R1_in_TensorRT-LLM.html)
 
 * [04/05] TensorRT LLM can run Llama 4 at over 40,000 tokens per second on B200 GPUs!
 
-![L4_perf](./docs/source/media/l4_launch_perf.png)
+![L4_perf](https://raw.githubusercontent.com/NVIDIA/TensorRT-LLM/main/docs/source/media/l4_launch_perf.png)
 
 
 * [03/22] TensorRT LLM is now fully open-source, with developments moved to GitHub!