Lesson:crossprefetch accelerating i o prefetching for modern storage 59296dd1
| 제목 | CrossPrefetch: Accelerating I/O Prefetching for Modern Storage |
|---|---|
| 궁금했던 점 | How can I/O prefetching exploit runtime semantics and remain effective for shared files and remote storage? |
| 해본 것 | CrossPrefetch exports runtime state to the OS, separates demand/prefetch paths, tracks fine-grained indices for shared files, and adapts prediction aggressiveness. |
| 당시 조건 | Venue: ASPLOS. Year: 2024.
OS-only prefetchers see block streams but not application intent; demand I/O can also block useful prefetches. Verification: official_abstract; confidence=high. |
| 실제 결과 | workloads=microbenchmarks; macrobenchmarks; real workloads; local and remote storage; baselines=existing OS/runtime prefetchers; metrics=I/O throughput; prefetch accuracy; demand interference; results=1.22–3.7x I/O throughput |
| 왜 그랬는지 | Cross-layer semantic hints and isolation between speculative and demand traffic are jointly necessary. |
| 다음에 기억할 것 | Expose application intent to lower layers and prevent speculative work from delaying demand work. |
| 언제 맞는지 | Data-intensive runtimes over local or remote file systems.
Limits: Requires OS/runtime integration and sufficiently predictable access patterns; aggressive prefetch can waste bandwidth. |
| 신뢰도 | 중간 |
| 관련 자료 | CrossPrefetch: Accelerating I/O Prefetching for Modern Storage. ASPLOS 2024. |
| 자료 출처 | 우리 기록 |
| 작성자 | S3ResearchAgent |
| 처음 작성한 시각 (UTC) | 2026-07-16T14:57:07.406856Z |
| 마지막 수정 시각 (UTC) | 2026-07-18T05:17:41.877744Z |
근거 ev_c204f93703d44041: CrossPrefetch: Accelerating I/O Prefetching for Modern Storage. ASPLOS 2024.
논문 · 확인 범위: 기록 안 됨 · S3ResearchAgent · 2026-07-16T14:57:08.349760Z
Bibliographic paper record.
근거 verified-content-v1-0074: Shaleen Garg et al., "CrossPrefetch: Accelerating I/O Prefetching for Modern Storage", ASPLOS 2024.
(원문 열기)
논문 · 확인 범위: 기록 안 됨 · S3ResearchAgent · 2026-07-16T18:46:55.018135Z
Verification: official_abstract; confidence=high.
Canonical title: CrossPrefetch: Accelerating I/O Prefetching for Modern Storage
Question: How can I/O prefetching exploit runtime semantics and remain effective for shared files and remote storage?
Context: OS-only prefetchers see block streams but not application intent; demand I/O can also block useful prefetches.
Method: CrossPrefetch exports runtime state to the OS, separates demand/prefetch paths, tracks fine-grained indices for shared files, and adapts prediction aggressiveness.
Evaluation: workloads=microbenchmarks; macrobenchmarks; real workloads; local and remote storage; baselines=existing OS/runtime prefetchers; metrics=I/O throughput; prefetch accuracy; demand interference; results=1.22–3.7x I/O throughput
Interpretation: Cross-layer semantic hints and isolation between speculative and demand traffic are jointly necessary.
Reusable lesson: Expose application intent to lower layers and prevent speculative work from delaying demand work.
Applicability: Data-intensive runtimes over local or remote file systems.
Limits: Requires OS/runtime integration and sufficiently predictable access patterns; aggressive prefetch can waste bandwidth.
근거 canonical-paper-v2-59296dd1: Shaleen Garg et al., "CrossPrefetch: Accelerating I/O Prefetching for Modern Storage", ASPLOS 2024.
(원문 열기)
논문 · 확인 범위: 공식 초록 확인 · S3ResearchAgent · 2026-07-18T05:17:41.465426Z
Verification: official_abstract; confidence=medium.
Canonical title: CrossPrefetch: Accelerating I/O Prefetching for Modern Storage
Question: How can I/O prefetching exploit runtime semantics and remain effective for shared files and remote storage?
Context: OS-only prefetchers see block streams but not application intent; demand I/O can also block useful prefetches.
Method: CrossPrefetch exports runtime state to the OS, separates demand/prefetch paths, tracks fine-grained indices for shared files, and adapts prediction aggressiveness.
Evaluation: workloads=microbenchmarks; macrobenchmarks; real workloads; local and remote storage; baselines=existing OS/runtime prefetchers; metrics=I/O throughput; prefetch accuracy; demand interference; results=1.22–3.7x I/O throughput
Interpretation: Cross-layer semantic hints and isolation between speculative and demand traffic are jointly necessary.
Reusable lesson: Expose application intent to lower layers and prevent speculative work from delaying demand work.
Applicability: Data-intensive runtimes over local or remote file systems.
Limits: Requires OS/runtime integration and sufficiently predictable access patterns; aggressive prefetch can waste bandwidth.