Os8 2

Operating Systems Principles Memory Management Lecture 8: Virtual Memory 主講人：虞台文

Content Principles of Virtual Memory Implementations of Virtual Memory Paging Segmentation Paging With Segmentation Paging of System Tables Translation Look-Aside Buffers Memory Allocation in Paged Systems Global Page Replacement Algorithms Local Page Replacement Algorithms Load Control and Thrashing Evaluation of Paging

Operating Systems Principles Memory Management Lecture 8: Virtual Memory Principles of Virtual Memory

The Virtual Memory Virtual memory is a technique that allows processes that may not be entirely in the memory to execute by means of automatic storage allocation upon request. The term virtual memory refers to the abstraction of separating LOGICAL memory  memory as seen by the process  from PHYSICAL memory  memory as seen by the processor . The programmer needs to be aware of only the logical memory space while the operating system maintains two or more levels of physical memory space.

Principles of Virtual Memory 00000000 00000000 FFFFFFFF FFFFFFFF 00000000 3FFFFFF 4 G 4 G Virtual Memory Virtual Memory Physical Memory 64 M . . . . . . . . .

Principles of Virtual Memory 00000000 00000000 FFFFFFFF FFFFFFFF 00000000 3FFFFFF 4 G 4 G Virtual Memory Virtual Memory Physical Memory 64 M Address Map Address Map . . . . . . . . .

Principles of Virtual Memory For each process, the system creates the illusion of large contiguous memory space(s) Relevant portions of Virtual Memory (VM) are loaded automatically and transparently Address Map translates Virtual Addresses to Physical Addresses 00000000 00000000 FFFFFFFF FFFFFFFF 00000000 3FFFFFF 4 G 4 G Virtual Memory Virtual Memory Physical Memory 64 M Address Map Address Map . . . . . . . . .

Approaches Single-segment Virtual Memory: One area of 0… n  1 words Divided into fix-size pages Multiple-Segment Virtual Memory: Multiple areas of up to 0… n  1 (words) Each holds a logical segment (e.g., function, data structure) Each is contiguous or divided into pages . . . . . . . . . . . .

Main Issues in VM Design Address mapping How to translate virtual addresses to physical addresses? Placement Where to place a portion of VM needed by process? Replacement Which portion of VM to remove when space is needed? Load control How many process could be activated at any one time? Sharing How can processes share portions of their VMs?

Operating Systems Principles Memory Management Lecture 8: Virtual Memory Implementations of Virtual Memory

Implementations of VM Paging Segmentation Paging With Segmentation Paging of System Tables Translation Look-aside Buffers

Paged Virtual Memory Page No. 0 1 2 p P  1 0 w 2 n  1 1 2 Page size 2 n Virtual Memory Offset Virtual Address ( p , w )

Physical Memory Frame No. 0 1 2 f F  1 0 w 2 n  1 1 2 Frame size 2 n Physical Memory Offset Physical Address ( f , w ) The size of physical memory is usually much smaller than the size of virtual memory .

Virtual & Physical Addresses The size of physical memory is usually much smaller than the size of virtual memory . va pa Memory Size Address Page number p Offset w Frame number f Offset w | p | bits | w | bits | f | bits | w | bits

Address Mapping Address Map Given ( p , w ) , how to determine f from p ? Page No. 0 1 2 p P  1 Virtual Memory Frame No. 0 1 2 f F  1 Physical Memory ( p , w ) ( f , w )

Address Mapping Address Map Each process (pid = id ) has its own virtual memory. Given ( id , p , w ) , how to determine f from ( id , p ) ? Page No. 0 1 2 p P  1 Virtual Memory Frame No. 0 1 2 f F  1 Physical Memory ( id , p , w ) ( f , w )

Frame Tables frame f  1 frame f frame f +1 Physical Memory ID p f pid page Each process (pid = id ) has its own virtual memory. Given ( id , p , w ) , how to determine f from ( id , p ) ? ID p w ID p Frame Table FT 0 1 f F  1 w

Address Translation via Frame Table address_map(id,p,w){ pa = UNDEFINED; for( f =0; f <F; f++) if( FT [ f ].pid==id && FT [ f ].page==p) pa = f +w; return pa ; } Each process (pid = id ) has its own virtual memory. Given ( id , p , w ) , how to determine f from ( id , p ) ?

Disadvantages Inefficient : mapping must be performed for every memory reference . Costly : Search must be done in parallel in hardware (i.e., associative memory). Sharing of pages difficult or not possible.

Associative Memories as Translation Look-Aside Buffers When memory size is large , frame tables tend to be quite large and cannot be kept in associative memory entirely. To alleviate this, associative memories are used as translation look-aside buffers . To be detailed shortly.

Page Tables f Page Tables frame f  1 frame f frame f +1 PTR Page Table Register Physical Memory p w p w

Page Tables A page table keeps track of current locations of all pages belonging to a given process. PTR points at PT of the current process at run time by OS. Drawback: An extra memory accesses needed for any read/write operations. Solution: Translation Look-Aside Buffer address_map(p, w) { pa = *( PTR +p)+w; return pa ; }

Demand Paging Pure Paging All pages of VM are loaded initially Simple, but maximum size of VM = size of PM Demand Paging Pages are loaded as needed: “on demand ” Additional bit in PT indicates a page’s presence/absence in memory “ Page fault ” occurs when page is absent

Demand Paging Pure Paging All pages of VM can be loaded initially Simple, but maximum size of VM = size of PM Demand Paging Pages a loaded as needed: “on demand ” Additional bit in PT indicates a page’s presence/absence in memory “ Page fault ” occurs when page is absent resident( m ) True : the m th page is in memory. False : the m th page is missing. address_map(p, w) { if (resident(*( PTR +p))) { pa = *( PTR +p)+w; return pa; } else page_fault ; }

Segmentation Multiple contiguous spaces (“segments”) More natural match to program/data structure Easier sharing (Chapter 9) va = ( s , w ) mapped to pa (but no frames) Where / how are segments placed in PM? Contiguous versus paged application

Contiguous Allocation Per Segment Segment Tables Segment x Segment s Segment y Physical Memory STR Segment Table Register s w s w

Contiguous Allocation Per Segment Each segment is contiguous in PM Segment Table (ST) tracks starting locations STR points to ST Address translation: Drawback: External fragmentation address_map(s, w) { if (resident(*( STR +s))) { pa = *( STR +s)+w; return pa ; } else segment_fault ; }

Paging with segmentation Each segment is divided into fix-size pages va = ( s , p , w ) | s | determines # of segments (size of ST) | p | determines # of pages per segment (size of PT) | w | determines page size Address Translation: Drawback: 2 extra memory references address_map(s, p, w) { pa = *(*( STR +s)+p)+w; return pa ; }

Paging of System Tables ST or PT may be too large to keep in PM Divide ST or PT into pages Keep track by additional page table Paging of ST ST divided into pages Segment directory keeps track of ST pages Address Translation: Drawback: 3 extra memory references. address_map(s1, s2, p, w) { pa = *(*(*( STR +s1)+s2)+p)+w; return pa ; }

Translation Look-Aside Buffers (TLB) Advantage of VM Users view memory in logical sense. Disadvantage of VM Extra memory accesses needed. Solution T ranslation L ook-aside B uffers (TLB) A special high-speed memory Basic idea of TLB Keep the most recent translation of virtual to physical addresses readily available for possible future use. An associative memory is employed as a buffer.

Translation Look-Aside Buffers (TLB)

Translation Look-Aside Buffers (TLB) When the search of ( s , p ) fails, the complete address translation is needed. Replacement strategy: LRU .

Translation Look-Aside Buffers (TLB) The buffer is searched associatively (in parallel )

Operating Systems Principles Memory Management Lecture 8: Virtual Memory Memory Allocation in Paged Systems

Memory Allocation with Paging Placement policy  where to allocate the memory on request? Any free frame is OK (no external fragmentation) Keep track of available space is sufficient both for statically and dynamically allocated memory systems Replacement policy  which page(s) to be replaced on page fault? Goal: Minimize the number of page faults and/or the total number pages loaded .

Global/Local Replacement Policies Global replacement: Consider all resident pages (regardless of owner). Local replacement Consider only pages of faulting process , i.e., the working set of the process.

Criteria for Performance Comparison Tool: Reference String (RS) r 0 r 1 ... r t ... r T r t : the page number referenced at time t Criteria: The number of page faults The total number of pages loaded

Criteria for Performance Comparison Tool: Reference String (RS) r 0 r 1 ... r t ... r T r t : the page number referenced at time t Criteria: The number of page faults The total number of pages loaded Equivalent To be used in the following discussions. =1

Global Page Replacement Algorithms Optimal Replacement Algorithm (MIN) Accurate prediction needed Unrealizable Random Replacement Algorithm Playing roulette wheel FIFO Replacement Algorithm Simple and efficient Suffer from Belady’s anormaly Least Recently Used Algorithm ( LRU ) Doesn’t suffer from Belady’s anormaly, but high overhead Second-Chance Replacement Algorithm Economical version of LRU Third-Chance Replacement Algorithm Economical version of LRU Considering dirty pages

Optimal Replacement Algorithm (MIN) Replace page that will not be referenced for the longest time in the future . Problem: Reference String not known in advance.

Example: Optimal Replacement Algorithm (MIN) RS = c a d b e b a b c d Replace page that will not be referenced for the longest time in the future . c a d b e b a b c d Problem: Reference String not known in advance. 2 page faults Time t RS Frame 0 Frame 1 Frame 2 Frame 3 IN t OUT t 0 1 2 3 4 5 6 7 8 9 10 a b c d a b c d a b c d a b c d a b c d a b c e d b c e e d a b c e a b c e a b c e a b c e d a

Random Replacement Program reference string are never know in advance. Without any prior knowledge, random replacement strategy can be applied. Is there any prior knowledge available for common programs? Yes , the locality of reference . Random replacement is simple but without considering such a property.

The Principle of Locality Most instructions are sequential Except for branch instruction Most loops are short for -loop while -loop Many data structures are accessed sequentially Arrays files of records

FIFO Replacement Algorithm FIFO: Replace oldest page Assume that pages residing the longest in memory are least likely to be referenced in the future. Easy but may exhibit Belady’s anormaly , i.e., Increasing the available memory can result in more page faults .

Example: FIFO Replacement Algorithm RS = c a d b e b a b c d c a d b e b a b c d Replace oldest page.            5 page faults Time t RS Frame 0 Frame 1 Frame 2 Frame 3 IN t OUT t 0 1 2 3 4 5 6 7 8 9 10 a b c d a b c d a b c d a b c d a b c d e b c d d a b c e a e b c d e a c d e a b d e a b c d e a b b c c d

Example: Belady’s Anormaly RS = dcbadcedcbaecdcbae 17 page faults 14 page faults Time t RS Frame 0 Frame 1 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 0 8 d c b a d c e d c b a e c d c b a e d d c b c b a d a d c e c e d c d c b a b e b c b c d c d b d b a e a Time t RS Frame 0 Frame 1 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 0 8 Frame 2 d c b a d c e d c b a e c d c b a e d d c d c a c a d b b b a d c e d c e d c e d c e b c e b a e b a e c a e d a c d a c b a c b a c e a

Example: Belady’s Anormaly 14 page faults 15 page faults Time t RS Frame 0 Frame 1 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 0 8 Frame 2 d c b a d c e d c b a e c d c b a e d d c d c a c a d b b b a d c e d c e d c e d c e b c e b a e b a e c a e d a c d a c b a c b a c e a d c b a d c e d c b a e c d c b a e d d c d c d c b b a d c b a d c b a e c b a e d b a e d c a e d c b a d c b a e c b a e c b a e d b a e d c b e d c b a d c b a e c Time t RS Frame 0 Frame 1 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 0 8 Frame 2 Frame 3

Least Recently Used Replacement (LRU) Replace Least Recently Used page Remove the page which has not been referenced for the longest time. Comply with the principle of locality Doesn’t suffer from Belady’s anormaly

Example: Least Recently Used Replacement (LRU) RS = c a d b e b a b c d Replace Least Recently Used page. 3 page faults c a d b e b a b c d Time t RS Frame 0 Frame 1 Frame 2 Frame 3 IN t OUT t 0 1 2 3 4 5 6 7 8 9 10 Queue end Queue head a b c d a b c d a b c d a b c d a b c d a b e d a b d c e c a b e d a b e d a b e d a b e c d e c d d c b a c d b a a c d b d a c b b d a c e b d a b e d a a b e d b a e d c b a e d c b a

LRU Implementation Software queue: too expensive Time-stamping Stamp each referenced page with current time Replace page with oldest stamp Hardware capacitor with each frame Charge at reference Replace page with smallest charge n -bit aging register with each frame Set left-most bit of referenced page to 1 Shift all registers to right at every reference or periodically Replace page with smallest value R = R n  1 R n  2 … R 1 R 0

Second-Chance Algorithm Approximates LRU Implement use-bit u with each frame Set u =1 when page referenced To select a page: If u ==0 , select page Else, set u =0 and consider next frame Used page gets a second chance to stay in PM Also called clock algorithm since search cycles through page frames .

Example: Second-Chance Algorithm To select a page: If u ==0 , select page Else, set u =0 and consider next frame cycle through page frames RS = c a d b e b a b c d 4 page faults c a d b e b a b c d            Time t RS Frame 0 Frame 1 Frame 2 Frame 3 IN t OUT t 0 1 2 3 4 5 6 7 8 9 10 a /1 b /1 c /1 d /1 a /1 b /1 c /1 d /1 a /1 b /1 c /1 d /1 a /1 b /1 c /1 d /1 a /1 b /1 c /1 d /1 e /1 b /0 c /0 d /0 e a e /1 b /1 c /0 d /0 e /1 b /0 a /1 d /0 a c e /1 b /1 a /1 d /0 e /1 b /1 a /1 c /1 c d d /1 b /0 a /0 c /0 d e

Third-Chance Algorithm Second chance algorithm does not distinguish between read and write access Write access more expensive Give modified pages a third chance: u -bit set at every reference ( read and write ) w -bit set at write reference to select a page, cycle through frames, resetting bits, until uw ==00 : uw  uw 1 1 0 1 1 0 0 0 0 1 0 0 * (remember modification) 0 0 select Can be implemented by an additional bit.

Example: Third-Chance Algorithm RS = c a w d b w e b a w b c d 3 page faults uw  uw 1 1 0 1 1 0 0 0 0 1 0 0 * 0 0 select c a w d b w e b a w b c d            Time t RS Frame 0 Frame 1 Frame 2 Frame 3 IN t OUT t 0 1 2 3 4 5 6 7 8 9 10 a /00 * d /10 e /00 c /00 a /10 b /10 c /10 d /10 a /10 b /10 c /10 d /10 a /11 b /10 c /10 d /10 a /11 b /10 c /10 d /10 a /11 b /11 c /10 d /10 a /00 * b /00 * e /10 d /00 e c a /00 * b /10 * e /10 d /00 a /11 b /10 * e /10 d /00 a /11 b /10 * e /10 d /00 a /11 b /10 * e /10 c /10 c d d b

Local Page Replacement Algorithms Measurements indicate that Every program needs a “ minimum ” set of pages If too few , thrashing occurs If too many , page frames are wasted The “ minimum ” varies over time How to determine and implement this “ minimum ”? Depending only on the behavior of the process itself.

Local Page Replacement Algorithms Optimal Page Replacement Algorithm (VMIN) The Working Set Model (WS) Page Fault Frequency Replacement Algorithm (PFF)

Optimal Page Replacement Algorithm (VMIN) The method Define a sliding window ( t , t +  )  width  + 1  is a parameter (a system constant) At any time t , maintain as resident all pages visible in window Guaranteed to generate smallest number of page faults corresponding to a given window width.

Example: Optimal Page Replacement Algorithm (VMIN) RS = c c d b c e c e a d 5 page faults  = 3 Time t RS Page a IN t OUT t 0 1 2 3 4 5 6 7 8 9 10 c c d b c e c e a d Page b Page c Page d Page e                                                        c b d b c e e a a d d

Example: Optimal Page Replacement Algorithm (VMIN) By increasing  , the number of page faults can arbitrarily be reduced , of course at the expense of using more page frames. VMIN is unrealizable since the reference string is unavailable. RS = c c d b c e c e a d 5 page faults  = 3 Time t RS Page a IN t OUT t 0 1 2 3 4 5 6 7 8 9 10 c c d b c e c e a d Page b Page c Page d Page e                                                        c b d b c e e a a d d

Working Set Model Use trailing window (instead of future window) Working set W ( t ,  ) is all pages referenced during the interval ( t –  , t ) (instead of ( t , t +  ) ) At time t : Remove all pages not in W ( t ,  ) Process may run only if entire W ( t ,  ) is resident

Example: Working Set Model RS = e d a c c d b c e c e a d 5 page faults  = 3 Time t RS Page a IN t OUT t 0 1 2 3 4 5 6 7 8 9 10 c c d b c e c e a d Page b Page c Page d Page e                                                        c b a b e a d a e d

Approximate Working Set Model Drawback: costly to implement Approximations: 1. Each page frame with an aging register Set left-most bit to 1 whenever referenced Periodically shift right all aging registers Remove pages which reach zero from working set. 2. Each page frame with a use bit and a time stamp Use bit is turned on by hardware whenever referenced Periodically do following for each page frame: Turn off use-bit if it is on and set current time as its time stamp Compute turn-off time t off of the page frame Remove the page from the working set if t off > t max

Page Fault Frequency (PFF) Replacement Main objective: Keep page fault rate low Basic principle: If the time btw the current ( t c ) and the previous ( t c  1 ) page faults exceeds a critical value  , all pages not referenced during that time interval are removed from memory. The algorithm of PFF: If time between page faults   grow resident set by adding new page to resident set If time between page faults >  shrink resident set by adding new page and removing all pages not referenced since last page fault

Example: Page Fault Frequency (PFF) Replacement RS = c c d b c e c e a d 5 page faults  = 2 Time t RS Page a IN t OUT t 0 1 2 3 4 5 6 7 8 9 10 c c d b c e c e a d Page b Page c Page d Page e                                                        c b a , e e a d a e b , d

Load Control and Thrashing Main issues: How to choose the degree of multiprogramming ? Decrease ? Increase ? When level decreased , which process should be deactivated ? When a process created or a suspended one reactivated , which of its pages should be loaded ? One or many ? Load Control Policy to set the number & type of concurrent processes Thrashing Most system’s effort pays on moving pages between main and secondary memory, i.e., low CPU utilization .

Load control  Choosing Degree of Multiprogramming Local replacement: Each process has a well-defined resident set , e.g., Working set model & PFF replacement This automatically imposes a limit , i.e., up to the point where total memory is allocated. Global replacement No working set concept Use CPU utilization as a criterion With too many processes , thrashing occurs

Load control  Choosing Degree of Multiprogramming Local replacement: Each process has a well-defined resident set , e.g., Working set model & PFF replacement This automatically imposes a limit , i.e., up to the point where total memory is allocated. Global replacement No working set concept Use CPU utilization as a criterion With too many processes , thrashing occurs L = mean time between faults S = mean page fault service time

Load control  Choosing Degree of Multiprogramming Local replacement: Each process has a well-defined resident set , e.g., Working set model & PFF replacement This automatically imposes a limit , i.e., up to the point where total memory is allocated. Global replacement No working set concept Use CPU utilization as a criterion With too many processes , thrashing occurs L = mean time between faults S = mean page fault service time How to determine the optimum, i.e., N max Thrashing

Load control  Choosing Degree of Multiprogramming L = S criterion: Page fault service S needs to keep up with mean time between faults L . 50% criterion: CPU utilization is highest when paging disk 50% busy (found experimentally). Clock load control Scan the list of page frames to find replaced page . If the pointer advance rate is too low, increase multiprogramming level. How to determine N max ?

Load control  Choosing the Process to Deactivate Lowest priority process Consistent with scheduling policy Faulting process Eliminate the process that would be blocked Last process activated Most recently activated process is considered least important . Smallest process Least expensive to swap in and out Largest process Free up the largest number of frames

Load control  Prepaging Which pages to load when process activated Prepage last resident set

Evaluation of Paging Advantages of paging Simple placement strategy No external fragmentation Parameters affecting the dynamic behavior of paged systems Page size Available memory

Evaluation of Paging A process requires a certain percentages of its pages within the short time period after activation . Prepaging is important.

Evaluation of Paging Smaller page size is beneficial. Another advantage with a small page size: Reduce memory waste due to internal fragmentation . However, small pages require lager page tables .

Evaluation of Paging W : Minimum amount of memory to avoid thrashing . Load control is important.

Os8 2

Recommended

More Related Content

What's hot (11)

Viewers also liked (20)

Similar to Os8 2 (20)

More from issbp (19)

Os8 2