Update readme (#15425)
This commit is contained in:
Lianmin Zheng
@@ -20,10 +20,10 @@
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| [**Slides**](https://github.com/sgl-project/sgl-learning-materials?tab=readme-ov-file#slides) |
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## News
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- [2025/12] SGLang provides day-0 support for latest open models ([MiNo-V2](https://lmsys.org/blog/2025-12-16-mimo-v2-flash/), [Nemotron 3 Nano](https://lmsys.org/blog/2025-12-15-run-nvidia-nemotron-3-nano/), [Mistral Large 3](https://github.com/sgl-project/sglang/pull/14213), [LLaDA 2.0 Diffusion LLM](https://x.com/lmsysorg/status/1999378073125552375?s=20), [MiniMax M2](https://lmsys.org/blog/2025-11-04-miminmax-m2/)).
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- [2025/11] 🔥 SGLang Diffusion accelerates video and image generation ([blog](https://lmsys.org/blog/2025-11-07-sglang-diffusion/)).
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- [2025/10] 🔥 SGLang now runs natively on TPU with the SGLang-Jax backend ([blog](https://lmsys.org/blog/2025-10-29-sglang-jax/)).
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- [2025/10] PyTorch Conference 2025 SGLang Talk ([slide](https://github.com/sgl-project/sgl-learning-materials/blob/main/slides/sglang_pytorch_2025.pdf)).
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- [2025/09] 🔥 Deploying DeepSeek on GB200 NVL72 with PD and Large Scale EP (Part II): 3.8x Prefill, 4.8x Decode Throughput ([blog](https://lmsys.org/blog/2025-09-25-gb200-part-2/)).
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- [2025/09] Deploying DeepSeek on GB200 NVL72 with PD and Large Scale EP (Part II): 3.8x Prefill, 4.8x Decode Throughput ([blog](https://lmsys.org/blog/2025-09-25-gb200-part-2/)).
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- [2025/09] SGLang Day 0 Support for DeepSeek-V3.2 with Sparse Attention ([blog](https://lmsys.org/blog/2025-09-29-deepseek-V32/)).
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- [2025/08] SGLang x AMD SF Meetup on 8/22: Hands-on GPU workshop, tech talks by AMD/xAI/SGLang, and networking ([Roadmap](https://github.com/sgl-project/sgl-learning-materials/blob/main/slides/amd_meetup_sglang_roadmap.pdf), [Large-scale EP](https://github.com/sgl-project/sgl-learning-materials/blob/main/slides/amd_meetup_sglang_ep.pdf), [Highlights](https://github.com/sgl-project/sgl-learning-materials/blob/main/slides/amd_meetup_highlights.pdf), [AITER/MoRI](https://github.com/sgl-project/sgl-learning-materials/blob/main/slides/amd_meetup_aiter_mori.pdf), [Wave](https://github.com/sgl-project/sgl-learning-materials/blob/main/slides/amd_meetup_wave.pdf)).
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- [2025/08] SGLang provides day-0 support for OpenAI gpt-oss model ([instructions](https://github.com/sgl-project/sglang/issues/8833))
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@@ -32,6 +32,7 @@
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<details>
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<summary>More</summary>
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- [2025/10] PyTorch Conference 2025 SGLang Talk ([slide](https://github.com/sgl-project/sgl-learning-materials/blob/main/slides/sglang_pytorch_2025.pdf)).
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- [2025/10] SGLang x Nvidia SF Meetup on 10/2 ([recap](https://x.com/lmsysorg/status/1975339501934510231)).
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- [2025/06] SGLang, the high-performance serving infrastructure powering trillions of tokens daily, has been awarded the third batch of the Open Source AI Grant by a16z ([a16z blog](https://a16z.com/advancing-open-source-ai-through-benchmarks-and-bold-experimentation/)).
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- [2025/06] Deploying DeepSeek on GB200 NVL72 with PD and Large Scale EP (Part I): 2.7x Higher Decoding Throughput ([blog](https://lmsys.org/blog/2025-06-16-gb200-part-1/)).
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@@ -292,13 +292,8 @@ class Scheduler(
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)
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)
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# Init model config
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self.model_config = ModelConfig.from_server_args(server_args)
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self.dllm_config = ( # For diffusion LLM
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DllmConfig.from_server_args(server_args)
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if server_args.dllm_algorithm is not None
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else None
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)
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# Init model configs
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self.init_model_config()
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# Init metrics stats
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self.init_metrics(tp_rank, pp_rank, dp_rank)
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@@ -306,7 +301,7 @@ class Scheduler(
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# Init inter-process communication
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self.init_sockets(server_args, port_args)
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# Init pdmux context
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# Init PD-multiplexing context
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if self.enable_pdmux:
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self.init_pdmux()
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@@ -316,10 +311,10 @@ class Scheduler(
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# Init moe config and GEMM config (FP8 GEMM, etc.)
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self.init_moe_gemm_config()
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# Launch a tensor parallel worker
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# Launch a model worker and draft model worker if using speculative decoding
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self.init_model_worker()
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# Init cache using the existing memory pool
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# Init cache and memory pool
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self.init_cache_with_memory_pool()
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# Init running status
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@@ -340,10 +335,10 @@ class Scheduler(
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# Init profiler
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self.init_profiler()
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# Init disaggregation
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# Init prefill-decodedisaggregation
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self.init_disaggregation()
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# Init overlap
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# Init overlap schedule
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self.init_overlap()
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# Init prefill kv split size when deterministic inference is enabled with various attention backends
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@@ -352,6 +347,14 @@ class Scheduler(
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# Init request dispatcher
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self.init_request_dispatcher()
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def init_model_config(self):
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self.model_config = ModelConfig.from_server_args(self.server_args)
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self.dllm_config = ( # For diffusion LLM
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DllmConfig.from_server_args(self.server_args)
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if self.server_args.dllm_algorithm is not None
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else None
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)
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def init_sockets(self, server_args: ServerArgs, port_args: PortArgs):
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context = zmq.Context(2)
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self.idle_sleeper = None
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