Add paper summary: Efficient Memory Management for Large Language Model Serving with PagedAttention (arXiv:2309.06180)

[claude]

Objective

Automatically summarize arXiv paper from Issue #552.

Effect

• Paper: Efficient Memory Management for Large Language Model Serving with PagedAttention
• Summary file: machine-learning/2023/efficient-memory-management-for-large-language-model-serving-with-pagedattention.md
• Issue: Closes Efficient Memory Management for Large Language Model Serving with PagedAttention #552

This PR includes a comprehensive summary following the project's DoD requirements:

• Concrete, detailed explanations (not vague statements)
• Clear input/output specifications with tensor dimensions
• Algorithm descriptions with mathematical formulations
• Datasets explicitly listed
• Comparisons with similar/related methods (FasterTransformer, Orca, FlashAttention)

Test

• Review the summary for completeness and accuracy
• Verify all mathematical formulations have proper dimensions
• Check that DoD requirements are met (see checklist below)
• Confirm the paper URL matches the issue

Note

Automatically generated via the auto-summarize-papers workflow.

Closes #552

---

Definition of Done Checklist

Common

• Describe the concrete sentences to support understanding (not just writing "I understand ...")
• Describe the condition which can be applied (who, when, where)
• Include information about licenses and copyrights

Computer Science / Machine Learning

• Clear Input and Output
• Describe Algorithms with pseudocode
• Explain datasets used
• Clear calculation order
• Describe the difference between similar algorithms