Download Chapter 14

Memory Management (a)
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Background
 Program must be brought into memory
and placed within a process for it to be run.
 Input queue – collection of processes on
the disk that are waiting to be brought into
memory to run the program.
 User programs go through several steps
before being run.
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Memory Management Requirements
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Relocation
 Users generally don’t know where they will be placed in main
memory
 May want to swap in at a different place (pointers???)
 Generally handled by hardware
Protection
 Prevent processes from interfering with the O.S. or other
processes
 Often integrated with relocation
Sharing
 Allow processes to share data/programs
Logical Organization
 Support modules, shared subroutines
Physical Organization
 Main memory verses secondary memory
 Overlaying
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von Neumann Model
 Instruction cycle
 CPU fetches instructions from memory
 Instruction is decoded
 Operands loaded from memory
 Instruction is executed
 Results are then stored back in memory
 Memory only sees a stream of addresses
 requests
 stores
 “von Neumann Bottleneck”
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Address Binding
 A process must be tied to a physical address
at some point (bound)
 Binding can take place at 3 times
 Compile time
 Always loaded to same memory address
 must recompile code if starting location changes
 Load time
 relocatable code
 stays in same spot once loaded
 Execution time
 Binding delayed until run time
 may be moved during execution
 special hardware needed
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Multistep Processing of a User Program
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Logical vs. Physical Address Space
 The concept of a logical address space that is
bound to a separate physical address space is
central to proper memory management.
 Logical address – generated by the CPU; also
referred to as virtual address.
 Physical address – address seen by the memory
unit.
 Logical and physical addresses are the same
in compile-time and load-time address-binding
schemes; logical (virtual) and physical
addresses differ in execution-time addressbinding scheme.
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Memory-Management Unit (MMU)
 Hardware device that maps virtual to physical
address.
 In MMU scheme, the value in the relocation
register is added to every address generated
by a user process at the time it is sent to
memory.
 The user program deals with logical
addresses; it never sees the real physical
addresses.
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Dynamic relocation using a relocation register
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Dynamic Loading
 Routine is not loaded until it is called
 Better memory-space utilization; unused
routine is never loaded.
 Useful when large amounts of code are
needed to handle infrequently occurring
cases,such as error routines.
 No special support from the operating
system is required implemented through
program design.
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Dynamic Linking
 Linking postponed until execution time.
 Small piece of code, stub, used to locate
the appropriate memory-resident library
routine.
 Stub replaces itself with the address of the
routine, and executes the routine.
 Operating system needed to check if
routine is in processes’ memory address.
 Dynamic linking is particularly useful for
libraries.
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Overlays
 Keep in memory only those instructions and
data that are needed at any given time.
 Needed when process is larger than amount
of memory allocated to it.
 Implemented by user, no special support
needed from operating system, programming
design of overlay structure is complex
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Overlays for a Two-Pass Assembler
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Swapping
 A process can be swapped temporarily out of memory
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to a backing store, and then brought back into memory
for continued execution.
Backing store – fast disk large enough to accommodate
copies of all memory images for all users; must provide
direct access to these memory images.
Roll out, roll in – swapping variant used for prioritybased scheduling algorithms; lower-priority process is
swapped out so higher-priority process can be loaded
and executed.
Major part of swap time is transfer time; total transfer
time is directly proportional to the amount of memory
swapped.
Modified versions of swapping are found on many
systems, i.e., UNIX, Linux, and Windows.
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Schematic View of Swapping
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Memory Management Techniques
 Fixed Partitioning
 Divide memory into partitions at boot time, partition
sizes may be equal or unequal but don’t change
 Simple but has internal fragmentation
 Dynamic Partitioning
 Create partitions as programs loaded
 Avoids internal fragmentation, but must deal with
external fragmentation
 Simple Paging
 Divide memory into equal-size pages, load program
into available pages
 No external fragmentation, small amount of internal
fragmentation
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Memory Management Techniques
 Simple Segmentation
 Divide program into segments
 No internal fragmentation, some external fragmentation
 Virtual-Memory Paging
 Paging, but not all pages need to be in memory at one
time
 Allows large virtual memory space
 More multiprogramming, overhead
 Virtual Memory Segmentation
 Like simple segmentation, but not all segments need to
be in memory at one time
 Easy to share modules
 More multiprogramming, overhead
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Fixed Partitioning
 Main memory divided into
static partitions
 Simple to implement
 Inefficient use of memory
Operating System
8M
8M
8M
Small programs use entire
partition
Maximum active processes fixed
Internal Fragmentation
8M
8M
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Fixed Partitioning
 Variable-sized partitions
 assign smaller programs to smaller
partitions
 lessens the problem, but still a
problem
 Placement
 Which partition do we use?
 Want to use smallest possible partition
 What if there are no large jobs waiting?
 Can have a queue for each partition
size, or one queue for all partitions
Operating System
8M
2M
4M
6M
8M
8M
12 M
 Used by IBM OS/MFT
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Placement Algorithm with Partitions
 Equal-size partitions
because all partitions are of equal size, it does
not matter which partition is used
 Unequal-size partitions
can assign each process to the smallest
partition within which it will fit
queue for each partition
processes are assigned in such a way as to
minimize wasted memory within a partition
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Dynamic Partitioning
 Partitions are of variable length and number
 Process is allocated exactly as much
memory as required
 Eventually get holes in the memory.
external fragmentation
 Must use compaction to shift processes so
they are contiguous and all free memory is
in one block
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Memory Management
400 K
OS
P5
P1
P1
900 K
1000 K
1700 K
Process Memory
P1
600
P2
1000
P3
300
P4
700
P5
500
P4
P2
P2
2000 K
2300 K
P3
2560 K
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Allocation Strategies
 First Fit
 Allocate the first spot in memory that is big enough to
satisfy the requirements.
 Best Fit
 Search through all the spots, allocate the spot in
memory that most closely matches requirements.
 Next Fit
 Scan memory from the location of the last placement
and choose the next available block that is large
enough.
 Worst Fit
 The largest free block of memory is used for bringing
in a process.
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Which Allocation Strategy?
 The first-fit algorithm is not only the simplest but usually
the best and the fastest as well.
 May litter the front end with small free partitions that must be
searched over on subsequent first-fit passes.
 The next-fit algorithm will more frequently lead to an
allocation from a free block at the end of memory.
 Results in fragmenting the largest block of free memory.
 Compaction may be required more frequently.
 Best-fit is usually the worst performer.
 Guarantees the fragment left behind is as small as possible.
 Main memory quickly littered by blocks too small to satisfy
memory allocation requests.
First-fit and best-fit better than worst-fit in
terms of speed and storage utilization.
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Dynamic Partitioning Placement
Algorithm
8K
8K
12K
12K
Allocate 18K
22K
Last
allocated
block (14K)
First Fit
18K
Next Fit
Best Fit
2K
8K
8K
6K
6K
14K
14K
36K
20K
Allocated block
Free block
6K
Before
After
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Fragmentation
 External Fragmentation – total memory space
exists to satisfy a request, but it is not contiguous.
 Internal Fragmentation – allocated memory may
be slightly larger than requested memory; this
size difference is memory internal to a partition,
but not being used.
 Reduce external fragmentation by compaction
 Shuffle memory contents to place all free memory
together in one large block.
 Compaction is possible only if relocation is
dynamic, and is done at execution time.
 I/O problem
 Latch job in memory while it is involved in I/O.
 Do I/O only into OS buffers.
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Memory Fragmentation
Solution of Fragmentation
 Statistical analysis shows that given N
allocated blocks, another 0.5 N blocks will
be lost due to fragmentation.
On average, 1/3 of memory is unusable
 (50-percent rule)
 Solution – Compaction.
Move allocated memory blocks so they are
contiguous
Run compaction algorithm periodically
 How often?
 When to schedule?
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Memory Fragmentation
Memory Compaction
400 K
700 K
1000 K
1400
1300 K
K
OS
P3
P1
P4
P3
Process Memory
P1
600
P2
1000
P3
300
P4
700
P5
500
Time
10
5
20
8
15
P2
P5
P4
1900 K
2000 K
2300 K
2500 K
2560 K
P3
P5
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Buddy System
Buddy System
 Tries to allow a variety of block sizes while avoiding
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excess fragmentation
Blocks generally are of size 2k, for a suitable range of k
Initially, all memory is one block
All sizes are rounded up to 2s
If a block of size 2s is available, allocate it
Else find a block of size 2s+1 and split it in half to create
two buddies
If two buddies are both free, combine them into a larger
block
Largely replaced by paging
 Seen in parallel systems and Unix kernel memory allocation
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Buddy System
Buddy System Example
1 Mbyte Block
1M
Request 100 Kb (A)
A
128K
256K
512K
Request 240 Kb (B)
A
128K
B
512K
Request 64 Kb (C)
A
C 64K
B
512K
Request 256 Kb (D)
A
C 64K
B
D
256K
Release B
A
C 64K
256K
D
256K
Release A
128K
C 64K
256K
D
256K
Request 75 Kb (E)
E
C 64K
256K
D
256K
Release C
E
128K
256K
D
256K
D
256K
Release E
Release D
256K
1M
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