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By Fajin Wang Bosah M Marcel Heimlich

LIRS: An Efficient Low Inter-reference Recency Set Replacement Policy to Improve Buffer Cache Performance Sensitivity/Overhead Analysis. By Fajin Wang Bosah M Marcel Heimlich. LIRS: An Efficient Low Inter-reference Recency Set Replacement Policy to Improve Buffer Cache Performance

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By Fajin Wang Bosah M Marcel Heimlich

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  1. LIRS: An Efficient Low Inter-reference Recency Set Replacement Policy to Improve Buffer Cache Performance Sensitivity/Overhead Analysis By Fajin Wang Bosah M Marcel Heimlich

  2. LIRS: An Efficient Low Inter-reference Recency Set Replacement Policy to Improve Buffer Cache Performance Sensitivity/Overhead Analysis By Fajin Wang Bosah M Marcel Heimlich

  3. Questions • Does the size of Lhirs affect the performance of LIRS? • Is there any effects of varying the thresholds for LIR/HIR switching on the performance of LIRS? • LRU is know for its simplicity and efficiency. • LIRS: time, space?

  4. Outline 1. Size Selection of Lhirs 2. Thresholds for LIR/HIR switching 3. Overhead Analysis

  5. Outline 1. Size Selection of Lhirs 2. Thresholds for LIR/HIR switching 3. Overhead Analysis

  6. Block Sets Physical Cache LIR block set (size is Llirs ) Llirs Lhirs HIR block set 1. Size Selection of Lhirs 1.1 Review Cache size L =Llirs + Lhirs

  7. 1. Size selection of Lhirs 1.2 Approach Optimal, LRU, LIRS

  8. 1. Size selection of Lhirs 1.3 Results • Not sensitive • Lowers – postgres • Improves – sprite

  9. 4. Sensitivity/Overhead Analysis 1. Size Selection of Lhirs 2. Thresholds for LIR/HIR switching 3. Overhead Analysis

  10. 5 0 1 3 2 2 3 1 6 4 5 9 4 6 7 8 2. Thresholds for LIR/HIR switching 2.2 Concepts 2.2.1 Rmax The Maximum recency of the LIR blocks 2.2.2 Easiness: HIR -> LIR Difficulty: LIR -> HIR

  11. 2. Thresholds for LIR/HIR switching 2.2 Experiments Optimal, LRU, LIRS

  12. 2. Thresholds for LIR/HIR switching • Not sensitive • Large threshold • close to LRU 2.3 Results

  13. 4. Sensitivity/Overhead Analysis 4.1 Size Selection of Lhirs 4.2 Thresholds for LIR/HIR switching 4.3 Overhead Analysis

  14. 4.3 Overhead analysis LIRS Efficiency: O(1) 4.3.1 Time IRR HIR (New IRR of the HIR block) Rmax (Maximum Recency of LIR blocks) This efficiency is achieved by the LIRS stack. LRU stack + LIR block with Rmax recency in its bottom ==> LIRS stack.

  15. 4.3 Overhead analysis 4.3.1 Space • LRU stack + LIR block with Rmax recency in its bottom ==> LIRS stack. • overhead: the extended portion of the LIRS stack • LIRS stack size/LRU stack size • Stack size limit

  16. 4.3 Overhead analysis LIRS stack size/LRU stack size 4.3.2 Space Ratio = 1: strong locality

  17. 4.3 Overhead analysis Limited LIRS stack size 4.3.2 Space Sensitive: moderatly extending the LRU stack size makes a large difference on its performance

  18. 4.3 Overhead analysis • Size of Lhirs • Not sensitive • Thresholds for LIR/HIR switching • Not sensitive • -Stack size • Sensitive • Critical point? 4.3.2 Analysis summary

  19. Conclusions LIRS • Effectively use deeper access history without explicit regularity detection and high cost operations. • Outperform exiting replacement policies. • Its implementation as simple as LRU. • Applicable to virtual memory and database buffer management.

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