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FRD: A Filtering based Buffer Cache Algorithm that Considers both Frequency and Reuse Distance

FRD: A Filtering based Buffer Cache Algorithm that Considers both Frequency and Reuse Distance. 33rd International Conference on Massive Storage Systems and Technology ( MSST 2017). OUTLINE. INTRODUCTION BACKGROUND & MOTIVATION PROPOSED FRD ALGORITHM EVALUATION CONCLUSION. OUTLINE.

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FRD: A Filtering based Buffer Cache Algorithm that Considers both Frequency and Reuse Distance

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  1. FRD: A Filtering based Buffer Cache Algorithm thatConsiders both Frequency and Reuse Distance 33rdInternational Conference on Massive StorageSystems and Technology (MSST 2017)

  2. OUTLINE • INTRODUCTION • BACKGROUND&MOTIVATION • PROPOSED FRDALGORITHM • EVALUATION • CONCLUSION

  3. OUTLINE • INTRODUCTION • BACKGROUND&MOTIVATION • PROPOSED FRDALGORITHM • EVALUATION • CONCLUSION

  4. INTRODUCTION(1/3) • Buffer cachealgorithms play a major role in building amemory hierarchy in a storage system. • Buffer cache is one of the key factors for improving performance. • Because of its simplicity and low overhead, a least-recently-used (LRU) algorithm is one of the most commonly used buffer cache algorithms.

  5. INTRODUCTION(2/3) • However, the LRU algorithm performs poorly forthe following workloads because of certain characteristics. • Scanning workload. • →meaningful blocks arepresent in the cache, the scanning workload evicts them. • Cyclic access (loop-like) workload in which loop lengthis greater than cache size. • →request sequence is1-2-3-4-1-2-3-4-1-2-3-4 2 1 4 3

  6. INTRODUCTION(3/3) • We propose a buffer cache algorithm, called frequency and reuse distance (FRD), that considers both frequency and reuse distance. • Through careful analysis on various real-world workloads, we find that infrequently accessed blocks are dominant in most cases and such blocks are the main source of cache pollution. • We concentrate on the manner in which to identify these infrequently accessed blocks and exclude them from the cache.

  7. OUTLINE • INTRODUCTION • BACKGROUND&MOTIVATION • PROPOSED FRDALGORITHM • EVALUATION • CONCLUSION

  8. BACKGROUND&MOTIVATION(1/6)

  9. BACKGROUND&MOTIVATION(2/6)

  10. BACKGROUND&MOTIVATION(3/6) • Observation #1. Approximately 50 to 90% of blocks are infrequently accessed in a real-world workload. • Most blocks are infrequently accessed and only a few blocks are frequently accessed. • If a cache algorithm performs in an LRU manner, blocks to be frequently accessed may be easily evicted from a cache because of infrequently accessed blocks. • Therefore, infrequently accessed blocks should be evicted prior to frequently accessed blocks, and frequently accessed blocks should be retained for a long time to make more cache hits.

  11. BACKGROUND&MOTIVATION(4/6)

  12. BACKGROUND&MOTIVATION(5/6) • Observation #2. Reuse distance for infrequently accessed blocks is either very short or very long. • Regarding cache size, most distribution is less than 10% or greater than 100% of cache size.

  13. BACKGROUND&MOTIVATION(6/6) • Type 1(Infrequently accessed with a long reuse distance)blocks generate pure cache pollution and this algorithm cannot be a cache hit as well. • The Type 2(Infrequently accessed with a short reuse distance)blocks might be a cache hit because it has a short reuse distance. • However, after a cache hit, it still produces cache pollution because it has infrequently accessed characteristics.

  14. OUTLINE • INTRODUCTION • BACKGROUND&MOTIVATION • PROPOSED FRDALGORITHM • EVALUATION • CONCLUSION

  15. PROPOSED FRDALGORITHM(1/11) • We propose a buffer cache algorithm that considers both access frequency and reuse distance, known as FRD. • The FRD effectively filters out cache polluting blocks using a filter stack and effectively maintains meaningful blocks using a reuse distance stack.

  16. PROPOSED FRDALGORITHM(2/11) • We have classified the infrequently accessed blocks by reuse distance (Type 1 and 2). • In this section, we expand the block classification into four Classification.

  17. PROPOSED FRDALGORITHM(3/11) • Cache pollution caused by Class IS or IL commonly occurs as a result of a scan-like workload in a LRU cache algorithm. • To avoid this cache pollution, we design our cache algorithm using two types of buffers: temporal and actual cache buffers. Temporal cache (Filter stack) Actual cache (Reuse distance stack)

  18. PROPOSED FRDALGORITHM(4/11) 5 actual block 8 7 8 5 5 7 5 history block MRU LRU HIT!!! 6 8 9 8 9 5 8 6 9 7 8 6 5 Temporal cache (Filter stack) LRU MRU 6 8 9 5 8 5 7 8 9 5 9 8 6 6 Actual cache (Reuse distance stack)

  19. PROPOSED FRDALGORITHM(5/11) HIT!!! 5 actual block 5 5 history block MRU LRU 6 8 9 8 9 5 8 6 9 7 8 6 5 Temporal cache (Filter stack) LRU MRU HIT!!! 6 8 9 5 8 5 7 8 7 8 9 6 5 9 5 9 8 6 6 Actual cache (Reuse distance stack)

  20. PROPOSED FRDALGORITHM(6/11) • When the two stacks are full, a total of four cases arepossible for a block request because of the history blockaccesses. • Case 1) Cache miss and history miss • Case 2) Cache miss but history hit • Case 3) Cache hit in the filter stack • Case 4) Cache hit in the reuse distance stack

  21. PROPOSED FRDALGORITHM(7/11) • Case 1) Cache miss and history miss: 12 12 MRU LRU 6 8 7 9 8 8 9 5 8 6 9 12 7 6 8 6 5 Temporal cache (Filter stack) LRU MRU 4 3 5 1 6 8 9 5 8 5 2 7 8 10 9 5 7 8 9 6 5 9 5 9 8 6 6 Actual cache (Reuse distance stack)

  22. PROPOSED FRDALGORITHM(8/11) • Case 2) Cache miss but history hit 10 MRU LRU 6 8 9 8 9 5 8 6 9 7 8 6 5 Temporal cache (Filter stack) LRU MRU HIT!!! 4 3 9 1 9 5 8 5 2 7 8 5 10 8 9 7 8 6 10 9 5 9 6 6 6 1 Actual cache (Reuse distance stack)

  23. PROPOSED FRDALGORITHM(9/11) • Case 3) Cache hit in the filter stack 6 MRU LRU HIT!!! 8 6 8 7 6 9 7 Temporal cache (Filter stack) LRU MRU 4 3 10 7 8 9 5 8 5 2 7 8 5 10 8 6 7 8 6 10 9 9 6 6 6 1 9 Actual cache (Reuse distance stack)

  24. PROPOSED FRDALGORITHM(10/11) • Case 4) Cache hit in the reuse distance stack 4 MRU LRU 6 8 9 7 Temporal cache (Filter stack) LRU MRU HIT!!! 4 3 3 9 2 4 2 10 10 7 8 7 8 9 6 1 6 1 Actual cache (Reuse distance stack)

  25. PROPOSED FRDALGORITHM(11/11) • The filter stack has two purposes. • Identify noise blocks (e.g., Class IS or IL) • Identify blocks with short reuse distance (e.g., Class IS or FS). • The reuse distance stack also has two purposes. • Maintain history block in reuse distance order. • Store frequently accessed blocks for later used (e.g., Class FL).

  26. OUTLINE • INTRODUCTION • BACKGROUND&MOTIVATION • PROPOSED FRDALGORITHM • EVALUATION • CONCLUSION

  27. EVALUATION(1/4)

  28. EVALUATION(2/4)

  29. EVALUATION(3/4) 37.8% 20%

  30. EVALUATION(4/4)

  31. OUTLINE • INTRODUCTION • BACKGROUND&MOTIVATION • PROPOSED FRDALGORITHM • EVALUATION • CONCLUSION

  32. CONCLUSION(1/1) • We proposed a buffer cache algorithm calledFRD that considers both frequency and reuse distance. • The primary purpose of the FRDis to exclude infrequently accessed blocks that may cause cache pollution and to maintain frequently accessed blocks based on reuse distance. • Experimental results showed that the FRD outperformed ARC or LIRS and that FRD’s hit ratio was stable for various cache sizes.

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