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Limits: 읽기 중심 평가이며 급격한 변화에서 제어 오버헤드와 안정성이 변수다.</property:Applicability>
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		<property:Context rdf:datatype="http://www.w3.org/2001/XMLSchema#string">Venue: FAST. Year: 2024.

고정 메모리 분할은 workload 변화와 두 캐시의 중복 때문에 비효율적이다.

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Canonical title: Symbiosis: The Art of Application and Kernel Cache Cooperation
Question: 애플리케이션 캐시와 커널 page cache의 중복·경쟁을 동적으로 조정할 수 있는가?
Context: 고정 메모리 분할은 workload 변화와 두 캐시의 중복 때문에 비효율적이다.
Method: Symbiosis는 애플리케이션과 커널 캐시 사이의 메모리 비율을 런타임에 조정한다.
Evaluation: workloads=LevelDB; WiredTiger; RocksDB; synthetic and real read-heavy workloads; baselines=static cache split; metrics=application performance; results=1.5× average and &gt;5× best-case improvement.
Interpretation: 캐시 계층을 독립 튜닝하지 말고 전체 hit·메모리 효율로 공동 제어해야 한다.
Reusable lesson: 중복 캐시는 정적 할당보다 피드백 기반 공동 할당이 낫다.
Applicability: 자체 캐시를 가진 DB와 OS page cache.
Limits: 읽기 중심 평가이며 급격한 변화에서 제어 오버헤드와 안정성이 변수다.</property:Evidence_note>
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Canonical title: Symbiosis: The Art of Application and Kernel Cache Cooperation
Question: 애플리케이션 캐시와 커널 page cache의 중복·경쟁을 동적으로 조정할 수 있는가?
Context: 고정 메모리 분할은 workload 변화와 두 캐시의 중복 때문에 비효율적이다.
Method: Symbiosis는 애플리케이션과 커널 캐시 사이의 메모리 비율을 런타임에 조정한다.
Evaluation: workloads=LevelDB; WiredTiger; RocksDB; synthetic and real read-heavy workloads; baselines=static cache split; metrics=application performance; results=1.5× average and &gt;5× best-case improvement.
Interpretation: 캐시 계층을 독립 튜닝하지 말고 전체 hit·메모리 효율로 공동 제어해야 한다.
Reusable lesson: 중복 캐시는 정적 할당보다 피드백 기반 공동 할당이 낫다.
Applicability: 자체 캐시를 가진 DB와 OS page cache.
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