mirage-project/mirage

• highreadme#1

  Add a clear disclaimer to avoid confusion with MirageOS

  Why:

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  Add this sentence prominently near the top of your README: 'Note: This project, Mirage Persistent Kernel (MPK), is distinct from the MirageOS unikernel project.'

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• hightopics#2

  Add relevant topics for better categorization

  Why:

  CURRENT

  (none)

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  llm, inference, gpu, megakernel, compiler, deep-learning, machine-learning, triton, flashinfer, pytorch

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• mediumreadme#3

  Strengthen the README's opening to highlight core differentiation

  Why:

  CURRENT

  Mirage Persistent Kernel (MPK) is a compiler and runtime system that automatically transforms LLM inference into a single megakernel—a fused GPU kernel that performs all necessary computation and communication within a single kernel launch. This end-to-end GPU fusion approach reduces LLM inference latency by 1.2× to 6.7×, all while requiring minimal developer effort.

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  Mirage Persistent Kernel (MPK) is a novel compiler and runtime system specifically designed to automatically transform multi-GPU LLM inference into a single, highly optimized megakernel. Unlike general-purpose compilers or individual kernel libraries, MPK achieves end-to-end GPU fusion, significantly reducing LLM inference latency by 1.2× to 6.7× with minimal developer effort, making it a unique solution for high-performance LLM deployment.

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Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

• CATEGORY QUERY

  How to reduce LLM inference latency for multi-GPU deployments effectively?

  you: not recommended
  AI recommended (in order):

  1. vLLM
  2. NVIDIA TensorRT-LLM
  3. TGI (Text Generation Inference) by Hugging Face
  4. DeepSpeed-MII (Microsoft Inference Interface)
  5. OpenVINO (Intel)
  6. Ray Serve
  7. TorchServe

  AI recommended 7 alternatives but never named mirage-project/mirage. This is the gap to close.

  Show full AI answer
• CATEGORY QUERY

  Tools to compile large language models into a single fused GPU kernel?

  you: not recommended
  AI recommended (in order):

  1. TensorRT
  2. OpenVINO
  3. Apache TVM
  4. XLA
  5. TorchDynamo
  6. Triton

  AI recommended 6 alternatives but never named mirage-project/mirage. This is the gap to close.

  Show full AI answer

• Metadata completeness

  warn

  Suggestion:

• README presence

  pass

• Compared to common alternatives in this category, what is the core differentiator of mirage-project/mirage?

  pass
  ⚠AI did not name mirage-project/mirage — likely talking about a different project

  AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

• If a team adopts mirage-project/mirage in production, what risks or prerequisites should they evaluate first?

  pass
  ⚠AI did not name mirage-project/mirage — likely talking about a different project

  AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

• In one sentence, what problem does the repo mirage-project/mirage solve, and who is the primary audience?

  pass
  ⚠AI did not name mirage-project/mirage — likely talking about a different project

  AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?