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Limits: 특정 가속기/CXL 프로토타입과 모델 보정에 의존한다.</property:Applicability>
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		<property:Context rdf:datatype="http://www.w3.org/2001/XMLSchema#string">Venue: FAST. Year: 2024.

가속기 근처 캐시는 빠르지만 작고, 호스트 캐시는 크지만 데이터 이동 비용이 있다.

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Canonical title: OmniCache: Collaborative Caching for Near-storage Accelerators
Question: near-storage 가속기의 작은 로컬 캐시와 호스트 캐시를 협업시킬 수 있는가?
Context: 가속기 근처 캐시는 빠르지만 작고, 호스트 캐시는 크지만 데이터 이동 비용이 있다.
Method: 호스트·장치 캐시를 공동 관리하고 모델 기반으로 캐시·연산 오프로딩을 결정하며 CXL로 확장한다.
Evaluation: workloads=I/O and data-processing workloads on near-storage accelerators; baselines=non-collaborative caching designs; metrics=I/O performance; data-processing performance; results=Up to 3.24× I/O and 3.06× processing performance.
Interpretation: 근접 캐시를 독립 계층이 아니라 전체 캐시 계층의 일부로 최적화해야 한다.
Reusable lesson: 캐시 배치와 연산 오프로딩 결정을 함께 내려라.
Applicability: CSD·near-storage accelerator·CXL 시스템.
Limits: 특정 가속기/CXL 프로토타입과 모델 보정에 의존한다.</property:Evidence_note>
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Canonical title: OmniCache: Collaborative Caching for Near-storage Accelerators
Question: near-storage 가속기의 작은 로컬 캐시와 호스트 캐시를 협업시킬 수 있는가?
Context: 가속기 근처 캐시는 빠르지만 작고, 호스트 캐시는 크지만 데이터 이동 비용이 있다.
Method: 호스트·장치 캐시를 공동 관리하고 모델 기반으로 캐시·연산 오프로딩을 결정하며 CXL로 확장한다.
Evaluation: workloads=I/O and data-processing workloads on near-storage accelerators; baselines=non-collaborative caching designs; metrics=I/O performance; data-processing performance; results=Up to 3.24× I/O and 3.06× processing performance.
Interpretation: 근접 캐시를 독립 계층이 아니라 전체 캐시 계층의 일부로 최적화해야 한다.
Reusable lesson: 캐시 배치와 연산 오프로딩 결정을 함께 내려라.
Applicability: CSD·near-storage accelerator·CXL 시스템.
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