Memory Management
(Ch 14)

It is a 800-pages topic, but here
we want to do it in one/two class!
Dynamic memory allocation
Language systems provide an important hidden player:
Runtime memory manager
–
–
–
–
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Activation records
Objects
Explicit allocations: new, malloc, etc.
Implicit allocations: strings, file buffers, arrays with
dynamically varying size, etc.
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Memory Model
Yes! It’s OS’s job!!
For now, assume that the OS grants each
running program one or more fixed-size
regions of memory for dynamic allocation
 We will model these regions as an array

–
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Our textbook shows an examples of memory
management code in Java
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Stacks Of Activation Records
A simple memory management problem
Activation records must be allocated
dynamically
 Allocate on call and de-allocate on return
 Stack of activation records: push and pop

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A Stack Illustration
top: 8
An empty stack of 8
words.
7:
reg.
6:
5:
4:
3:
grow
2:
1:
0:
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Some program P needs 3 words
The manager
program calls
m.push(3).
top: 4
7:
first activation
record
6:
P gets this
pointer
5:
4:
8
3:
2:
1:
0:
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Some other program Q needs 2 words
The manager
program calls
m.push(2).
top: 1
7:
first activation
record
6:
P gets this
pointer
5:
4:
3:
Q gets this
pointer
2:
1:
8
second
activation record
4
0:
wasted
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Heap

Stack is easy to do, but
Allocations and deallocations may come in any
order?

A heap is a pool of blocks of memory
At the beginning there is only one block
(but not always the case)
There are many approaches for doing this…
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A pool of free blocks are linked, initially containing one big
free block, then fragmented into small blocks
How to deal blocks to the requests?
The easiest approach: First Fit for request
–
–
–
Search the free list for first adequate block
If there is extra space in the block, return the unused
portion to front of the free list
Allocate requested portion (at the lower end)
To free a block, just add to the front of the free list
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Heap implementation
in an array
9:
8:
7:
6:
5:
4:
3:
2:
freeStart: 0
1:
-1
0:
10
Pointer to
next block,
-1 means no
next block.
Size of this block
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9:
8:
7:
Some program P
requests 4 words
P gets this
pointer
6:
-1
5:
5
Size of this free block
4:
3:
first allocated
block
2:
1:
freeStart: 5
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0:
5
Size of this block for P
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Some program Q
requests 2 words
Q gets this
pointer
9:
-1
8:
2
7:
Size of this block
6:
second allocated
block
5:
3
4:
3:
first allocated
block
2:
1:
freeStart: 8
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5
11
9:
8:
7:
-1
2
6:
second allocated
block
5:
3
2
6:
second allocated
block
5:
3
3:
first allocated
block
2:
2:
P is done
1:
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8:
4:
3:
0:
-1
7:
4:
freeStart: 8
9:
5
freeStart: 0
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1:
8
0:
5
12
9:
-1
8:
2
7:
Some program R
requests 1 word
6:
second allocated
block
5:
3
4:
R gets this
pointer
3:
8
2:
3
third allocated
block
1:
freeStart: 2
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2
13
top
A Problem

Consider this sequence:
1. p1=m.allocate(4);
2. p2=m.allocate(4);
p2
-1
5
top
5
p2
5
0
5
-1
5
-1
5
top
3. m.deallocate(p1);
4. m.deallocate(p2);
5. p3=m.allocate(7);

The manager needs to
coalesce adjacent free
blocks.
How?
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p1
5
p1
5
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Improvement strategy

Quick lists, a separate list, same sized blocks
Keep separate free lists for
popular (small) block sizes
 Delayed coalescing
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Another problem:
Fragmentation
p1=m.allocate(4);
p2=m.allocate(1);
m.deallocate(p1);
p3=m.allocate(5);
The final allocation will fail because
of fragmentation.
9:
8:
-1
7:
3
6:
second allocated
block
5:
2
4:
3:
2:
DeFragmentation
freeStart: 0
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7
0:
5
16
Heap Mechanisms
(to manage heaps.)
Many variety and different refinements

Three major issues:
–
–
–
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Placement—where to allocate a block
Splitting—when and how to split large blocks
Coalescing—when and how to recombine
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Placement: Where to allocate a block
(FF) First Fit from a stack (FIFO) of free list
 (BF) Best Fit …
 (NF) Next Fit …

Some mechanisms use a more scalable data
structure like a Balanced Binary Tree
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Splitting: When and how to split large blocks

Split to requested size

Sometimes, less splitting gives better results
e.g., allocate more than requested or
rounding up allocation size to some
multiple, for example 2n
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Coalescing: When and how to recombine
adjacent free blocks

Several varieties:
–
–
–
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No coalescing
Eager coalescing
Delayed coalescing
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Current Heap Links


Some systems track current heap links
A current heap link is a memory
a
address (location in the heap)
where the running program
b
may use
What if
a = new X(i);
b = new X(j);
a = b;
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Tracing Current Heap Links
start:
a:
b: 2
c: 1
1
(an IntList)
free
(activation record
for main)
head: 2
tail: null
3
free
2
(a ConsCell)
free
head: 1
tail:
(a ConsCell)
IntList a =
new IntList(null);
int b = 2;
int c = 1;
a = a.cons(b);
a = a.cons(c);
Where are the current
heap links in this
picture?
1 2 3
free
the stack
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the heap
free
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To Find Current Heap Links

Start with the root set: memory locations outside
of the heap with links into the heap
We have to check:
– Active activation records (if on the stack)
– Static variables, etc.
{a b c }
They are not in the active activation record.


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For each memory location in the set, look at the
allocated block it points to, and add all the
memory locations in that block
Repeat until no new locations are found
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Possible Errors In Current Heap Links
1. Exclusion errors: a memory location that actually is a current heap
link is left out. (This type of error is not allowed)
Heap
Current heap links
Static
variables
s
456
x:123
a
y:100
b
p, r, a
c
d
2000
Current
Activation
Record
p
3000
z:200
r[3]
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4000
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Possible Errors In Current Heap Links
2. Unused inclusion errors: a memory location is included, but the
program never actually uses the value stored there
Heap
Current heap links
Static
variables
s
456
x:123
a
y:100
b
s, p, r, a, c, d
c
d
How do I know this is
the case?
2000
Current
Activation
Record
p
3000
z:200
r[3]
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4000
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Possible Errors In Current Heap Links
3. Used inclusion errors (mistaken): a memory location is included, but the
program uses the value stored there as something other than a heap
address (e.g. int)
Heap
Current heap links
Static
variables
s
456
x:123
a
y:100
b
s, p, r, a, c, y, z
c
d
How do I know this is
the case?
2000
Current
Activation
Record
p
3000
z:200
r[3]
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4000
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Errors Are Unavoidable

For heap manager purposes, exclusion errors are
unacceptable
Therefore, we must include a location if it might be
used as a heap link, and
 This makes unused inclusion errors unavoidable
 Depending on the language, used inclusions errors
(mistaken) may also be unavoidable
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An application for current heap links:
Heap Compaction/Defragmentation


P
Manager can re-allocate
blocks:
– Copy the block to a new
location
– Update all links to (or
into) that block
P
Q
S
R
Q
T
R
S
So it can compact the heap,
moving all allocated blocks
to one end, leaving one big
free block and no
fragmentation
T
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
There are so many errors caused by improper deallocation
(e.g., Bad or without class destructors in C/C++)

It is a burden on the programmer …
Therefore, let the language system do the job
automatically --- Garbage Collection
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Garbage Collection
Three Major Approaches
1.
2.
3.
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Mark and sweep
Copying
Reference counting
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Mark And Sweep
uses current heap links in a two-stage process:
–
Mark: find the live heap links and mark all the heap
blocks pointed by them
–
Sweep: make a pass over the heap and return unmarked
blocks to the free pool
- both kinds of inclusion errors are tolerated,
- blocks are not moved, fragmentation may remain
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Mark And Sweep
Mark: live heap
links (in red)
blocks are not moved / fragmentations may remain
P
P
Free blocks
Free blocks
R
S
R
S
T
T
Sweep: return
unmarked blocks
to the free pool
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Copying Collection




divide memory in half, and uses only one half at a
time
When one half becomes full, find live heap links,
and copy live blocks to the other half
Fragmentation is eliminated
Moves blocks
Cannot tolerate used inclusion errors. Why?
Because that used variable will be mistaken
as a link and hence modified
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Moves blocks: cannot tolerate used
inclusion errors (mistake)
X=100
X=700
P
P
Q
Copying
Collection

S
R
Q
T
R
S
T
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Reference Counting
Each block has a counter of heap links to it
 Incremented when a heap link is copied,
decremented when a heap link is discarded
 When counter goes to zero, block is garbage
and can be freed
 Does not use current heap links

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Reference Counting
circle:
2
link:
(activation record)
free
1
link:
free
free
link:
1
free
the stack
the heap
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Garbage cycles can’t
be identified
Reference Counting Problem
circle: null
1
link:
(activation record)
free
1
link:
free
But all blocks are
garbage.
free
1
link:
the stack
Reference counters
are not zero
free
the heap
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Reference Counting
Problem 1: cycles of garbage
 Problem 2: overhead of updating reference
counters is high


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One advantage: more uniform. I.e., cost is
incremental, no big pause while collecting
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Garbage Collecting Refinements

Generational collectors
–
–

Incremental collectors
–
–
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Divide block into generations according to age
Garbage collect in younger generations more
often (using previous methods)
Collect garbage a little at a time
Avoid the uneven performance like mark-andsweep and copying collectors
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Languages with Garbage Collectors
Required: Java, ML
 encouraged: Ada
 difficult to have: C, C++

–
–
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But not impossible, even for C and C++
There are libraries that replace the usual
malloc/free with a garbage-collecting
manager
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Conclusion
Memory management is an important
hidden player in language systems
 Performance and reliability are critical
 Different techniques are difficult to
compare, since every run of every program
makes different memory demands
 Still an active area of language systems
research and experimentation

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