1. Container Marking : Combining Data Placement, Garbage Collection and Wear Leveling for Flash MASCOTS '11 Xiao-Yu Hu, Robert Haas, and Eleftheriou Evangelos From IBM Reserarch, Zurich, Switzerland 2011. 08. 23 (Tue) Kwangwoon univ. SystemSoftware Lab. HoSeok Seo 1

2. Introduction  Garbage Collection  Reclaim blocks that include invalid page to reuse it as free blocks  Wear Leveling  Use blocks evenly to extends overall SSD endurance life  But, Wear Leveling makes  Unnecessary invalid pages  Unnecessary Writes ( for relocation of valid pages )  In this paper  Proposes Container Marking Scheme to solve these problems 2

3. Background  Garbage Collection  Greedy -Select victims that have less valid pages  Cost-benefit(FIFO) -Consider two parameters time after last updated block Number of valid pages -Select victims that have the biggest value 3

4. Motivation  Why are active and inactive pages distinguished? 4

5. Scheme Principle  If a block has the same active level pages, it has high chance to have invalid pages a lot.  Marker  Blocks have a marker indicating block’s endurance life.  Pages have a marker indicating page’s active level  Data placement  One block has the same active level pages.  More active pages is located more younger blocks 5

6. Container-marking based data placement  Block marker range : 1 ~ 2L  Low marker : older blocks  High marker : younger blocks  The free block pool is organized by a priority queue in term of the remaining life count of the blocks.  The priority queue can be logically divided into 2L segments.  Once a free block has been filled up with data, it is removed from the free block pool and goes into one of 2L lists of occupied blocks depending on its marker 6

7. Container-marking based data placement 7

8. Modified greedy selection  Victim selection policy for garbage collection.  Prevent relatively younger blocks from being locked by inactive data.  To select j-th block, 8 V : the number of valid page in a block E : remaining life count

9. Page marker estimation  Basic  At high utilization, pages on average have a higher chance to be relocated than to be updated.  In this case, the markers gradually decrease and converge to lower values. 9 TypeEstimation NewM = L UpdatedM = m’ + 1 RelocatedM = m’ - 1

10. Page marker estimation with probabilistic marker 10

11. Implementation  Java-based Simulator  Map Policy : page-level mapping  Container-marking meta data (32bits)  Remaining life count (20bit)  The number of valid pages within the block (8bits)  Container marker (4bits) 11

12. Result 12

13. Result 13