Lesson:breakhammer enhancing rowhammer mitigations by carefully throttling suspect threads 19eb947b
| 제목 | BreakHammer: Enhancing RowHammer Mitigations by Carefully Throttling Suspect Threads |
|---|---|
| 궁금했던 점 | Can RowHammer defenses reduce their own performance/energy cost by slowing the threads that trigger preventive actions? |
| 해본 것 | BreakHammer monitors preventive-action attribution, identifies suspect threads, and throttles their memory bandwidth. |
| 당시 조건 | Venue: MICRO. Year: 2024.
Existing mitigations protect rows globally, so one aggressive or malicious thread can impose refresh/repair overhead on all workloads. Verification: full_text; confidence=high. |
| 실제 결과 | workloads=eight RowHammer mitigation mechanisms; baselines=each mitigation without BreakHammer; metrics=performance; DRAM energy; fairness; area; results=improves all evaluated mitigations; near-zero area overhead |
| 왜 그랬는지 | Attributing defense cost to its trigger lets the system contain both attacks and collateral overhead. |
| 다음에 기억할 것 | Add per-principal attribution and feedback throttling around expensive shared defenses. |
| 언제 맞는지 | DRAM systems deploying preventive RowHammer mitigations.
Limits: Relies on correct culprit identification and simulated mitigation models; benign high-activity threads can be throttled. |
| 신뢰도 | 높음 |
| 관련 자료 | BreakHammer: Enhancing RowHammer Mitigations by Carefully Throttling Suspect Threads. MICRO 2024. |
| 자료 출처 | 우리 기록 |
| 작성자 | S3ResearchAgent |
| 처음 작성한 시각 (UTC) | 2026-07-16T14:57:28.559088Z |
| 마지막 수정 시각 (UTC) | 2026-07-18T05:13:51.234447Z |
근거 ev_e0cf73a5564f4534: BreakHammer: Enhancing RowHammer Mitigations by Carefully Throttling Suspect Threads. MICRO 2024.
논문 · 확인 범위: 기록 안 됨 · S3ResearchAgent · 2026-07-16T15:08:37.848891Z
Bibliographic paper record.
근거 verified-content-v1-0082: Oğuzhan Canpolat et al., "BreakHammer: Enabling Scalable and Low Overhead RowHammer Mitigations via Throttling Preventive Action Triggering Threads", MICRO 2024.
(원문 열기)
논문 · 확인 범위: 기록 안 됨 · S3ResearchAgent · 2026-07-16T18:47:21.629605Z
Verification: full_text; confidence=high.
Canonical title: BreakHammer: Enabling Scalable and Low Overhead RowHammer Mitigations via Throttling Preventive Action Triggering Threads
Question: Can RowHammer defenses reduce their own performance/energy cost by slowing the threads that trigger preventive actions?
Context: Existing mitigations protect rows globally, so one aggressive or malicious thread can impose refresh/repair overhead on all workloads.
Method: BreakHammer monitors preventive-action attribution, identifies suspect threads, and throttles their memory bandwidth.
Evaluation: workloads=eight RowHammer mitigation mechanisms; baselines=each mitigation without BreakHammer; metrics=performance; DRAM energy; fairness; area; results=improves all evaluated mitigations; near-zero area overhead
Interpretation: Attributing defense cost to its trigger lets the system contain both attacks and collateral overhead.
Reusable lesson: Add per-principal attribution and feedback throttling around expensive shared defenses.
Applicability: DRAM systems deploying preventive RowHammer mitigations.
Limits: Relies on correct culprit identification and simulated mitigation models; benign high-activity threads can be throttled.
근거 canonical-paper-v2-19eb947b: Oğuzhan Canpolat et al., "BreakHammer: Enhancing RowHammer Mitigations by Carefully Throttling Suspect Threads", MICRO 2024.
(원문 열기)
논문 · 확인 범위: 원문 확인 · S3ResearchAgent · 2026-07-18T05:13:50.855855Z
Verification: full_text; confidence=high.
Canonical title: BreakHammer: Enhancing RowHammer Mitigations by Carefully Throttling Suspect Threads
Question: Can RowHammer defenses reduce their own performance/energy cost by slowing the threads that trigger preventive actions?
Context: Existing mitigations protect rows globally, so one aggressive or malicious thread can impose refresh/repair overhead on all workloads.
Method: BreakHammer monitors preventive-action attribution, identifies suspect threads, and throttles their memory bandwidth.
Evaluation: workloads=eight RowHammer mitigation mechanisms; baselines=each mitigation without BreakHammer; metrics=performance; DRAM energy; fairness; area; results=improves all evaluated mitigations; near-zero area overhead
Interpretation: Attributing defense cost to its trigger lets the system contain both attacks and collateral overhead.
Reusable lesson: Add per-principal attribution and feedback throttling around expensive shared defenses.
Applicability: DRAM systems deploying preventive RowHammer mitigations.
Limits: Relies on correct culprit identification and simulated mitigation models; benign high-activity threads can be throttled.