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Page Replacement Policies in Virtual Memory Systems

Explore optimal, FIFO, random, and least-recently-used page replacement policies in virtual memory systems along with their impact on hit rates and performance. Learn about approximation algorithms, implementation, and strategies to prevent thrashing.

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Page Replacement Policies in Virtual Memory Systems

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  1. Beyond Physical Memory: Policies Ansu Na(asna@archi.snu.ac.kr) School of Computer Science and Engineering Seoul National University

  2. Introduction • Introduction • Page Replacement Policies • Optimal Replacement Policy • FIFO Policy • Random Policy • Least-Recently-Used Policy • Approximation : Clock Algorithm • Other Kinds of Policies for Virtual Machine • Page Selection Policy • Cleaning Policy

  3. Optimal Replacement Policy Impossible To Implement Page Access 0 1 2 0 1 3 0 3 1 2 1 Miss Miss Miss Hit Hit Miss Hit Hit Hit Miss Hit Memory 0 1 3 0 1 2 0 0 1 0 1 2 0 1 2 0 1 3 0 1 3 0 1 2 0 1 3 0 1 2 Compulsory Misses Hit Rate with compulsory misses : 54.6% Hit Rate without compulsory misses : 85.7% • Leads to the fewest number of misses • Replaces the page accessed furthest in the future • Can be used as a comparison point

  4. FIFO Policy Page Access 0 1 2 0 1 3 0 3 1 2 1 Miss Miss Miss Hit Hit Miss Miss Hit Miss Miss Hit Memory First-in Page 2 3 0 0 1 2 0 0 1 0 1 2 0 1 2 1 2 3 2 3 0 3 0 1 0 1 2 0 1 2 Compulsory Misses Hit Rate with compulsory misses : 36.4% Hit Rate without compulsory misses : 57.1% • Is simple to implement • Replaces the first-in page

  5. Random Policy (%) Page Access 0 1 2 0 1 3 0 3 1 2 1 Miss Miss Miss Hit Hit Miss Miss Hit Miss Hit Hit Memory 3 0 2 0 1 2 0 0 1 0 1 2 3 1 2 0 1 2 3 0 2 1 0 2 0 1 2 0 1 2 Compulsory Misses • Is simple to implement • Replaces the randomly selected page

  6. Least Recently Used(LRU) Policy Page Access 0 1 2 0 1 3 0 3 1 2 1 Miss Miss Miss Hit Hit Miss Hit Hit Hit Miss Hit Memory Least Recently Accessed Page 1 3 0 3 1 2 0 0 1 0 1 2 0 1 3 2 0 1 1 0 3 0 3 1 3 2 1 1 2 0 Compulsory Misses • Tries to guess the future accesses • Utilizes the locality • Replaces the least recently accessed page

  7. Implementing LRU Policy Logical page numbers Time stamps 4GB Memory Physical page numbers OS Access 0 1 2 0 3 Scan all 100 4KB Page Current Time 0 1 3 2 98 80 92 112 112 100 1 million entries HW • Hardware updates the time stamp on every memory reference • OS selects the victim on replacement by scanning all entries • The cost is very expensive

  8. Approximation of LRU : Clock Algorithm Page Access 0 1 2 0 1 3 0 3 1 2 1 Miss Miss Miss Hit Hit Miss Hit Hit Hit Miss Hit 0 0 - 1 2 0 1 0 : Reference bit - 3 2 - 1 1 • Uses the reference bit for checking recent access • Page access : HW sets the reference bit • Page fault : OS starts to find the unreferenced page clearing the reference bit • Does not scan through

  9. Dirty Bit 0 0 1 : Reference bit : Dirty bit 2 1 1 1 0 0 Unreferenced & Clean! • Represents that the page is modified or not • Prefer to evict clean page • Page replacement of dirty page is expensive

  10. Workload : No-Locality • Page access pattern is random • Number of pages : 100 • Number of accesses : 10000 • Optimal policy provides much better hit ratio • All of realistic policies provide similar hit ratio

  11. Workload : 80-20 Hot Cold 20% 80% # of pages # of accesses 80% 20% AMAT with 40 blocks 82% 77% • There is difference on access hotness of pages • LRU provides higher hit ratio than FIFO & Random • Improvement is dependent on miss penalty

  12. Workload : Looping Sequential Random policy does not have corner case 49 • 50 Pages are accessed in looping sequential manner • Access pattern : 0, 1, 2, 3, … 48, 49, 0, 1, 2, 3, … • Database system shows similar access patterns • Hit rates of LRU and FIFO are miserable

  13. Other Policies for Virtual Machine • Page selection policy • Demand paging • Bring the page when it is accessed • Prefetching • Bring some pages speculatively • Writing to disk Policy • One at a time • Immediately write out to disk • Clustering • Collect some writes and then write them together

  14. Thrashing • Paging constantly and rapidly • If working sets exceed physical memory • And if workload locality cannot held well Physical Memory Process A Process B Process C

  15. Thrashing • Paging constantly and rapidly • If working sets exceed physical memory • And if workload locality cannot held well Physical Memory Process A Process B Process C

  16. Thrashing • Paging constantly and rapidly • If working sets exceed physical memory • And if workload locality cannot held well Physical Memory Process A Process B Process C

  17. Thrashing Physical Memory Pending Process A Process B Process C Physical Memory KILL! Process A Process B Process C • Thrashing solutions • Admission control • Keeps working set smaller than physical memory • Imposes some overhead • Out-of-memory killer • Kills the memory intensive process • Can be problematic

  18. Thrashing Physical Memory Pending Process A Process B Process C Physical Memory Process A Process B Process C • Thrashing solutions • Admission control • Keeps working set smaller than physical memory • Imposes some overhead • Out-of-memory killer • Kills the memory intensive process • Can be problematic

  19. Summary Source : http://www.fusionio.com/load/-media-/302wu5/docsLibrary/PX600_DS_Final_v3.pdf (Retrieved on 2015.05.11) • Page replacement policy • It is critical for performance • Approximation is realistic approach • LRU & Clock algorithm • Scan-resistance is important • The best solution of author • Buy more memory • Page fault penalty is too expensive • Disk is too slow • The new trends • Storages are getting faster • Need to revisit the policies

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