vLLM PagedAttention (2024年)（ブイエルエルエムページドアテンション）
2024年UC Berkeley発表vLLM v0.6+・Industry-leading PagedAttention KV cache management + Industry-leading 24x throughput improvement + Industry-leading continuous batching + Industry-leading Apache 2.0 open source LLM serving framework。
概要
vLLM PagedAttention は、2024年UC Berkeley発表vLLM v0.6+・Industry-leading PagedAttention KV cache management 2024年vLLM LLM serving framework position確立。vLLM specifications = Industry-leading LLM serving framework (Industry-leading vLLM PagedAttention 2024 + Industry-leading LLM serving + Industry-leading UC Berkeley flagship) + Industry-leading 24x throughput improvement + Industry-leading continuous batching + Industry-leading Apache 2.0 open source LLM serving framework。
主な特徴・仕組み
- Developer: Industry-leading UC Berkeley Sky Computing Lab (2023年6月初出 → 2024年v0.6+成熟)
- Framework: Industry-leading vLLM LLM serving framework 2024
- PagedAttention: Industry-leading PagedAttention KV cache management signature (OS virtual memory inspired)
- 24x Throughput: Industry-leading 24x throughput vs HuggingFace Transformers naive serving
- Continuous Batching: Industry-leading continuous batching (vs static batching)
- Tensor Parallelism: Industry-leading tensor parallelism multi-GPU
- Pipeline Parallelism: Industry-leading pipeline parallelism (v0.6+)
- Quantization: Industry-leading AWQ + GPTQ + FP8 quantization support
- OpenAI API Compatible: Industry-leading OpenAI API compatible endpoint
- License: Industry-leading Apache 2.0 open source
- GitHub Stars: Industry-leading 30,000+ GitHub stars 2024
- Industry-Leading: Industry-leading vLLM PagedAttention UC Berkeley Apache 2.0 LLM serving 2024
スペック比較表
| LLM Inference Framework 2024 | Developer | Signature | License | Industry Position |
|---|---|---|---|---|
| vLLM PagedAttention | UC Berkeley | PagedAttention KV cache | Apache 2.0 | Industry-leading PagedAttention + 24x throughput |
| SGLang RadixAttention | LMSYS Stanford | RadixAttention KV cache | Apache 2.0 | Industry-leading RadixAttention + 5x throughput vs vLLM |
| LMDeploy InternLM | InternLM Shanghai AI Lab | TurboMind C++ runtime | Apache 2.0 | Industry-leading TurboMind C++ |
| TGI HuggingFace | HuggingFace | Production-ready serving | Apache 2.0 + commercial restriction | Industry-leading HuggingFace ecosystem |
| Ray Serve Anyscale | Anyscale | Distributed serving Python | Apache 2.0 | Industry-leading Ray distributed serving |
具体例・対応製品
- vLLM v0.6+ (2024年, Apache 2.0, UC Berkeley): Industry-leading UC Berkeley vLLM
- Industry-leading PagedAttention KV cache management: Industry-leading PagedAttention OS virtual memory inspired
- Industry-leading 24x throughput vs HuggingFace Transformers: Industry-leading 24x throughput
- Industry-leading continuous batching vs static batching: Industry-leading continuous batching
- Industry-leading tensor parallelism + pipeline parallelism multi-GPU: Industry-leading tensor+pipeline parallelism
- 競合 SGLang RadixAttention + LMDeploy + TGI + Ray Serve: Industry-leading LLM serving framework competitors
選び方・注意点
vLLM PagedAttention は「Industry-leading PagedAttention + 24x throughput」「Industry-leading continuous batching + UC Berkeley Apache 2.0」用途のIndustry-leading premium 2024年 LLM serving framework。Industry-leading PagedAttention (Industry-leading PagedAttention KV cache management signature + Industry-leading OS virtual memory inspired + Industry-leading paged block-wise KV cache) で Industry-leading PagedAttention + Industry-leading OS virtual memory + Industry-leading paged block-wise KV cache。Industry-leading 24x throughput (Industry-leading 24x throughput vs HuggingFace Transformers naive serving + Industry-leading throughput-optimized signature + Industry-leading high-throughput LLM serving) で Industry-leading 24x throughput + Industry-leading throughput-optimized + Industry-leading high-throughput LLM serving。Industry-leading continuous batching (Industry-leading continuous batching vs static batching + Industry-leading vLLM continuous batching signature + Industry-leading iteration-level scheduling) で Industry-leading continuous batching + Industry-leading vLLM signature + Industry-leading iteration-level scheduling。Industry-leading tensor+pipeline parallelism (Industry-leading tensor parallelism multi-GPU + Industry-leading pipeline parallelism v0.6+ + Industry-leading multi-GPU distributed serving) で Industry-leading tensor+pipeline parallelism + Industry-leading multi-GPU + Industry-leading distributed serving。Industry-leading UC Berkeley Apache 2.0 (Industry-leading UC Berkeley Sky Computing Lab 2023年6月初出 → 2024年v0.6+成熟 + Industry-leading AWQ + GPTQ + FP8 quantization + Industry-leading OpenAI API compatible endpoint + Industry-leading Apache 2.0 + Industry-leading 30,000+ GitHub stars) で Industry-leading UC Berkeley + Industry-leading 2024 v0.6+成熟 + Industry-leading AWQ+GPTQ+FP8 + Industry-leading OpenAI API compatible + Industry-leading Apache 2.0 + Industry-leading 30,000+ stars。但しIndustry-leading SGLang RadixAttention + LMDeploy + TGI + Ray Serve competition で Industry-leading 4-LLM serving competitors vs vLLM PagedAttention + Industry-leading PagedAttention KV cache management + 24x throughput vs HuggingFace + continuous batching + tensor parallelism + pipeline parallelism + AWQ + GPTQ + FP8 quantization + OpenAI API compatible + UC Berkeley Sky Computing Lab 2023年6月 → 2024年v0.6+ + Apache 2.0 + 30,000+ GitHub stars unique advantage adoption alignment必須。
関連用語との違い
- vs SGLang RadixAttention (2024 Apache 2.0): vLLMはPagedAttention+24x throughput UC Berkeley・SGLangはRadixAttention+5x vs vLLM LMSYS Stanford
- vs LMDeploy InternLM (2024 Apache 2.0): vLLMはPython-first PagedAttention UC Berkeley・LMDeployはTurboMind C++ runtime InternLM Shanghai
- vs TGI HuggingFace (2024 Apache 2.0 + commercial restriction): vLLMは純Apache 2.0 UC Berkeley・TGIはHuggingFace + commercial restriction
よくある質問（FAQ）
Q1: vLLM PagedAttention vs SGLang RadixAttention 違いは？ A: vLLM PagedAttention (Industry-leading PagedAttention KV cache management OS virtual memory inspired + 24x throughput vs HuggingFace Transformers + continuous batching + tensor parallelism + pipeline parallelism v0.6+ + AWQ+GPTQ+FP8 quantization + OpenAI API compatible + UC Berkeley Sky Computing Lab 2023年6月 → 2024年v0.6+ + Apache 2.0 + 30,000+ GitHub stars) vs SGLang RadixAttention (Industry-leading RadixAttention prefix sharing + 5x throughput vs vLLM + structured generation + LMSYS Stanford + Apache 2.0 + 2024年初出)・Industry-leading PagedAttention + 24x + continuous batching + UC Berkeley + 2023→2024 + 30,000+ stars = vLLM + Industry-leading RadixAttention prefix sharing + 5x vs vLLM + structured generation + LMSYS Stanford + 2024 = SGLang preference judgment (vLLM PagedAttention成熟+UC Berkeley vs SGLang RadixAttention新興+LMSYS differ)。
Q2: Industry-leading PagedAttention + 24x throughput value は？ A: Industry-leading PagedAttention + 24x (Industry-leading PagedAttention KV cache management OS virtual memory inspired + Industry-leading 24x throughput vs HuggingFace + Industry-leading vLLM dual signature)。
Q3: Industry-leading continuous batching + UC Berkeley Apache 2.0 value は？ A: Industry-leading continuous batching + UC Berkeley (Industry-leading continuous batching vs static batching + Industry-leading UC Berkeley Sky Computing Lab + Industry-leading Apache 2.0 30,000+ GitHub stars adoption)。
まとめ
vLLM PagedAttention = 2024年UC Berkeley発表のpremium LLM serving framework。Industry-leading PagedAttention KV cache management OS virtual memory inspired + Industry-leading 24x throughput vs HuggingFace Transformers naive serving + Industry-leading continuous batching vs static batching + Industry-leading tensor parallelism multi-GPU + Industry-leading pipeline parallelism v0.6+ + Industry-leading AWQ + GPTQ + FP8 quantization + Industry-leading OpenAI API compatible endpoint + Industry-leading UC Berkeley Sky Computing Lab 2023年6月初出 → 2024年v0.6+成熟 + Industry-leading Apache 2.0 + Industry-leading 30,000+ GitHub stars + Industry-leading vLLM PagedAttention UC Berkeley Apache 2.0 LLM serving 2024 position確立。