Virtual Memory & Address Translation Vivek Pai Princeton University
Oct 10, Memory Gedanken For a given system, estimate the following –# of processes –Amount of memory Are all portions of a program likely to be used? What fraction might be unused? What does this imply about memory bookkeeping?
Oct 10, Some Numbers Bubba: desktop machine –63 processes –128MB memory + 12MB swap used –About 2 MB per process Oakley: CS shared machine –188 processes –2GB memory + 624MB swap –About 13 MB per process Arizona: undergrad shared machine –818 processes –8GB memory, but only 2GB used –About 2MB per process
Oct 10, Quiz 1 Answers Microkernel – small privileged kernel with most kernel services running as user-space process Speed? Lots of context switches, memory copying for communications Memory layout:
Oct 10, Quiz 1 Breakdown 4.0 – – – – – – – 3
Oct 10, General Memory Problem We have a limited (expensive) physical resource: main memory We want to use it as efficiently as possible We have an abundant, slower resource: disk
Oct 10, Lots of Variants Many programs, total size less than memory –Technically possible to pack them together –Will programs know about each other’s existence? One program, using lots of memory –Can you only keep part of the program in memory? Lots of programs, total size exceeds memory –What programs are in memory, and how to decide?
Oct 10, History Versus Present History –Each variant had its own solution –Solutions have different hardware requirements –Some solutions software/programmer visible Present – general-purpose microprocessors –One mechanism used for all of these cases Present – less capable microprocessors –May still use “historical” approaches
Oct 10, Many Programs, Small Total Size Observation: we can pack them into memory Requirements by segments –Text: maybe contiguous –Data: keep contiguous, “relocate” at start –Stack: assume contiguous, fixed size Just set pointer at start, reserve space –Heap: no need to make it contiguous Text 1 Data 1 Stack 1 Data 2 Text 2 Stack 2
Oct 10, Many Programs, Small Total Size Software approach –Just find appropriate space for data & code segments –Adjust any pointers to globals/functions in the code –Heap, stack “automatically” adjustable Hardware approach –Pointer to data segment –All accesses to globals indirected
Oct 10, One Program, Lots of Memory Observations: locality –Instructions in a function generally related –Stack accesses generally in current stack frame –Not all data used all the time Goal: keep recently-used portions in memory –Explicit: programmer/compiler reserves, controls part of memory space – “ overlays ” –Note: limited resource may be address space Data Stack Text Active Heap Other Heap(s)
Oct 10, Many Programs, Lots of Memory Software approach –Keep only subset of programs in memory –When loading a program, evict any programs that use the same memory regions –“Swap” programs in/out as needed Hardware approach –Don’t permanently associate any address of any program to any part of physical memory Note: doesn’t address problem of too few address bits
Oct 10, Why Virtual Memory? Use secondary storage($) –Extend DRAM($$$) with reasonable performance Protection –Programs do not step over each other –Communications require explicit IPC operations Convenience –Flat address space –Programs have the same view of the world
Oct 10, How To Translate Must have some “mapping” mechanism Mapping must have some granularity –Granularity determines flexibility –Finer granularity requires more mapping info Extremes: –Any byte to any byte: mapping equals program size –Map whole segments: larger segments problematic
Oct 10, Translation Options Granularity –Small # of big fixed/flexible regions – segments –Large # of fixed regions – pages Visibility –Translation mechanism integral to instruction set – segments –Mechanism partly visible, external to processor – obsolete –Mechanism part of processor, visible to OS – pages
Oct 10, Translation Overview Actual translation is in hardware (MMU) Controlled in software CPU view –what program sees, virtual memory Memory view –physical memory Translation (MMU) CPU virtual address Physical memory physical address I/O device
Oct 10, Goals of Translation Implicit translation for each memory reference A hit should be very fast Trigger an exception on a miss Protected from user’s faults Registers Cache(s) DRAM Disk 10x 100x 10Mx paging
Oct 10, Base and Bound Built in Cray-1 A program can only access physical memory in [base, base+bound] On a context switch: save/restore base, bound registers Pros: Simple Cons: fragmentation, hard to share, and difficult to use disks virtual address base bound error + > physical address
Oct 10, Segmentation Have a table of (seg, size) Protection: each entry has –(nil, read, write, exec) On a context switch: save/restore the table or a pointer to the table in kernel memory Pros: Efficient, easy to share Cons: Complex management and fragmentation within a segment physical address + segmentoffset Virtual address segsize > error
Oct 10, Paging Use a page table to translate Various bits in each entry Context switch: similar to the segmentation scheme What should be the page size? Pros: simple allocation, easy to share Cons: big table & cannot deal with holes easily VPage #offset Virtual address > error PPage#... PPage#... PPage #offset Physical address Page table page table size
Oct 10, How Many PTEs Do We Need? Assume 4KB page –Equals “low order” 12 bits Worst case for 32-bit address machine –# of processes 2 20 What about 64-bit address machine? –# of processes 2 52
Oct 10, Segmentation with Paging VPage #offset Virtual address > PPage#... PPage#... PPage #offset Physical address Page table segsize Vseg # error
Oct 10, Stretch Time: Getting A Line First try: fflush (stdout) scanf(“%s”, line) 2nd try: scanf(“%c”, firstChar) if (firstChar != ‘\n’) scanf(“%s”, rest) Final: back to first principles while (…) getc( )
Oct 10, Multiple-Level Page Tables Directory pte dirtableoffset Virtual address What does this buy us? Sparse address spaces and easier paging
Oct 10, Inverted Page Tables Main idea –One PTE for each physical page frame –Hash (Vpage, pid) to Ppage# Pros –Small page table for large address space Cons –Lookup is difficult –Overhead of managing hash chains, etc pidvpageoffset pidvpage 0 k n-1 koffset Virtual address Physical address Inverted page table
Oct 10, Virtual-To-Physical Lookups Programs only know virtual addresses Each virtual address must be translated –May involve walking hierarchical page table –Page table stored in memory –So, each program memory access requires several actual memory accesses Solution: cache “active” part of page table
Oct 10, Translation Look-aside Buffer (TLB) offset Virtual address PPage#... PPage#... PPage#... PPage #offset Physical address VPage # TLB Hit Miss Real page table VPage#
Oct 10, Bits in a TLB Entry Common (necessary) bits –Virtual page number: match with the virtual address –Physical page number: translated address –Valid –Access bits: kernel and user (nil, read, write) Optional (useful) bits –Process tag –Reference –Modify –Cacheable
Oct 10, Hardware-Controlled TLB On a TLB miss –Hardware loads the PTE into the TLB Need to write back if there is no free entry –Generate a fault if the page containing the PTE is invalid –VM software performs fault handling –Restart the CPU On a TLB hit, hardware checks the valid bit –If valid, pointer to page frame in memory –If invalid, the hardware generates a page fault Perform page fault handling Restart the faulting instruction
Oct 10, Software-Controlled TLB On a miss in TLB –Write back if there is no free entry –Check if the page containing the PTE is in memory –If no, perform page fault handling –Load the PTE into the TLB –Restart the faulting instruction On a hit in TLB, the hardware checks valid bit –If valid, pointer to page frame in memory –If invalid, the hardware generates a page fault Perform page fault handling Restart the faulting instruction
Oct 10, Hardware vs. Software Controlled Hardware approach –Efficient –Inflexible –Need more space for page table Software approach –Flexible –Software can do mappings by hashing PP# (Pid, VP#) (Pid, VP#) PP# –Can deal with large virtual address space
Oct 10, Cache vs. TLBs Similarities –Both cache a portion of memory –Both write back on a miss Combine L1 cache with TLB –Virtually addressed cache –Why wouldn’t everyone use virtually addressed caches? Differences –Associativity TLB is usually fully set- associative Cache can be direct- mapped –Consistency TLB does not deal with consistency with memory TLB can be controlled by software
Oct 10, Caches vs. TLBs Similarities Both cache a portion of memory Both read from memory on misses Differences Associativity –TLBs generally fully associative –Caches can be direct-mapped Consistency –No TLB/memory consistency –Some TLBs software-controlled Combining L1 caches with TLBs Virtually addressed caches Not always used – what are their drawbacks?
Oct 10, Issues What TLB entry to be replaced? –Random –Pseudo LRU What happens on a context switch? –Process tag: change TLB registers and process register –No process tag: Invalidate the entire TLB contents What happens when changing a page table entry? –Change the entry in memory –Invalidate the TLB entry
Oct 10, Consistency Issues “Snoopy” cache protocols can maintain consistency with DRAM, even when DMA happens No hardware maintains consistency between DRAM and TLBs: you need to flush related TLBs whenever changing a page table entry in memory On multiprocessors, when you modify a page table entry, you need to do “TLB shoot-down” to flush all related TLB entries on all processors
Oct 10, Issues to Ponder Everyone’s moving to hardware TLB management – why? Segmentation was/is a way of maintaining backward compatibility – how? For the hardware-inclined – what kind of hardware support is needed for everything we discussed today?