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Automatic Storage Management Patrick Earl Simon Leonard Jack Newton.

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1 Automatic Storage Management Patrick Earl Simon Leonard Jack Newton

2 CMPUT 425/525: Automatic Storage Management 2 Overview Terminology Why use Automatic Storage Management? Comparing garbage collection algorithms The “Classic” algorithms Copying garbage collection Incremental Tracing garbage collection Generational garbage collection Conclusions

3 CMPUT 425/525: Automatic Storage Management 3 Terminology Stack: a memory area where activation records or frames are pushed onto when a procedure is called and popped off when it returns Heap: a memory area where data structures can be allocated and deallocated in any order.

4 CMPUT 425/525: Automatic Storage Management 4 Terminology (Continued) Roots: values that a program can manipulate directly (i.e. values held in registers, on the program stack, and global variables.) Node/Cell/Object: an individually allocated piece of data in the heap. Children Nodes: the list of pointers that a given node contains. Live Node: a node whose address is held in a root or is the child of a live node.

5 CMPUT 425/525: Automatic Storage Management 5 Terminology (Continued) Garbage: nodes that are not live, but are not free either. Garbage collection: the task of recovering (freeing) garbage nodes. Mutator: The program running alongside the garbage collection system.

6 CMPUT 425/525: Automatic Storage Management 6 Why Garbage Collect? Language requirements – In some situations it may be impossible to know when a shared data structure is no longer in use.

7 CMPUT 425/525: Automatic Storage Management 7 Why Garbage Collect? (Continued) Software Engineering – Garbage collection increases abstraction level of software development. – Simplified interfaces and decreases coupling of modules. – Studies have shown a significant amount of development time is spent on memory management bugs [Rovner, 1985].

8 CMPUT 425/525: Automatic Storage Management 8 Comparing Garbage Collection Algorithms Directly comparing garbage collection algorithms is difficult – there are many factors to consider. Some factors to consider: – Cost of reclaiming cells – Cost of allocating cells – Storage overhead – How does the algorithm scale with residency? – Will user program be suspended during garbage collection? – Does an upper bound exist on the pause time? – Is locality of data structures maintained (or maybe even improved?)

9 CMPUT 425/525: Automatic Storage Management 9 Classes of Garbage Collection Algorithms Direct Garbage Collectors: a record is associated with each node in the heap. The record for node N indicates how many other nodes or roots point to N. Indirect/Tracing Garbage Collectors: usually invoked when a user’s request for memory fails because the free list is exhausted. The garbage collector visits all live nodes, and returns all other memory to the free list. If sufficient memory has been recovered from this process, the user’s request for memory is satisfied.

10 CMPUT 425/525: Automatic Storage Management 10 Quick Review: Reference Counting Every cell has an additional field: the reference count. This field represents the number of pointers to that cell from roots or heap cells. Initially, all cells in the heap are placed in a pool of free cells, the free list.

11 CMPUT 425/525: Automatic Storage Management 11 Reference Counting (Continued) When a cell is allocated from the free list, its reference count is set to one. When a pointer is set to reference a cell, the cell’s reference count is incremented by 1; if a pointer is to the cell is deleted, its reference count is decremented by 1. When a cell’s reference count reaches 0, its pointers to its children are deleted and it is returned to the free list.

12 CMPUT 425/525: Automatic Storage Management Reference Counting Example

13 CMPUT 425/525: Automatic Storage Management Reference Counting Example (Continued) 0 1

14 CMPUT 425/525: Automatic Storage Management Reference Counting Example (Continued)

15 CMPUT 425/525: Automatic Storage Management Reference Counting Example (Continued) Returned to free list

16 CMPUT 425/525: Automatic Storage Management 16 Reference Counting: Advantages and Disadvantages Advantages: – Garbage collection overhead is distributed. – Locality of reference is no worse than mutator. – Free memory is returned to free list quickly.

17 CMPUT 425/525: Automatic Storage Management 17 Reference Counting: Advantages and Disadvantages (Continued) Disadvantages: – High time cost (every time a pointer is changed, reference counts must be updated). – Storage overhead for reference counter can be high. – Unable to reclaim cyclic data structures. – If the reference counter overflows, the object becomes permanent.

18 CMPUT 425/525: Automatic Storage Management 18 Reference Counting: Cyclic Data Structure - Before

19 CMPUT 425/525: Automatic Storage Management 19 Reference Counting: Cyclic Data Structure – After

20 CMPUT 425/525: Automatic Storage Management 20 Deferred Reference Counting Optimisation – Cost can be improved by special treatment of local variables. – Only update reference counters of objects on the stack at fixed intervals. – Reference counts are still affected from pointers from one heap object to another.

21 CMPUT 425/525: Automatic Storage Management 21 Quick Review: Mark-Sweep The first tracing garbage collection algorithm Garbage cells are allowed to build up until heap space is exhausted (i.e. a user program requests a memory allocation, but there is insufficient free space on the heap to satisfy the request.) At this point, the mark-sweep algorithm is invoked, and garbage cells are returned to the free list.

22 CMPUT 425/525: Automatic Storage Management 22 Mark-Sweep (Continued) Performed in two phases: – Mark phase: identifies all live cells by setting a mark bit. Live cells are cells reachable from a root. – Sweep phase: returns garbage cells to the free list.

23 CMPUT 425/525: Automatic Storage Management 23 Mark-Sweep Example Returned to free list

24 CMPUT 425/525: Automatic Storage Management 24 Mark-Sweep: Advantages and Disadvantages Advantages: – Cyclic data structures can be recovered. – Tends to be faster than reference counting.

25 CMPUT 425/525: Automatic Storage Management 25 Mark-Sweep: Advantages and Disadvantages (Continued) Disadvantages: – Computation must be halted while garbage collection is being performed – Every live cell must be visited in the mark phase, and every cell in the heap must be visited in the sweep phase. – Garbage collection becomes more frequent as residency of a program increases. – May fragment memory.

26 CMPUT 425/525: Automatic Storage Management 26 Mark-Sweep: Advantages and Disadvantages (Continued) Disadvantages: – Has negative implications for locality of reference. Old objects get surrounded by new ones (not suited for virtual memory applications). However, if objects tend to survive in clusters in memory, as they apparently often do, this can greatly reduce the cost of the sweep phase.

27 CMPUT 425/525: Automatic Storage Management 27 Mark-Compact Collection Remedy the fragmentation and allocation problems of mark-sweep collectors. Two phases: – Mark phase: identical to mark sweep. – Compaction phase: marked objects are compacted, moving most of the live objects until all the live objects are contiguous.

28 CMPUT 425/525: Automatic Storage Management 28 Mark-Compact: Advantages and Disadvantages (Continued) Advantages: – The contiguous free area eliminates fragmentation problem. Allocating objects of various sizes is simple. – The garbage space is "squeezed out", without disturbing the original ordering of objects. This ameliorate locality.

29 CMPUT 425/525: Automatic Storage Management 29 Mark-Compact: Advantages and Disadvantages (Continued) Disadvantages: – Requires several passes over the data are required. "Sliding compactors" takes two, three or more passes over the live objects. One pass computes the new location Subsequent passes update the pointers to refer to new locations, and actually move the objects

30 CMPUT 425/525: Automatic Storage Management 30 Copying Garbage Collection Like mark-compact, copying garbage collection does not really "collect" garbage. Rather it moves all the live objects into one area and the rest of the heap is know to be available. Copying collectors integrate the traversal and the copying process, so that objects need only be traversed once. The work needed is proportional to the amount of live date (all of which must be copied).

31 CMPUT 425/525: Automatic Storage Management 31 Semispace Collector Using the Cheney Algorithm The heap is subdivided into two contiguous subspaces (FromSpace and ToSpace). During normal program execution, only one of these semispaces is in use. When the garbage collector is called, all the live data are copied from the current semispace (FromSpace) to the other semispace (ToSpace).

32 CMPUT 425/525: Automatic Storage Management 32 Semispace Collector Using the Cheney Algorithm A BC D FromSpaceToSpace

33 CMPUT 425/525: Automatic Storage Management 33 Semispace Collector Using the Cheney Algorithm FromSpaceToSpace A B C D A BC D

34 CMPUT 425/525: Automatic Storage Management 34 Semispace Collector Using the Cheney Algorithm (Continued) Once the copying is completed, the ToSpace is made the "current" semispace. A simple form of copying traversal is the Cheney algorithm. The immediately reachable objects from the initial queue of objects for a breadth-first traversal. A scan pointer is advanced through the first object location by location. Each time a pointer into FromSpace is encountered, the referred-to-object is transported to the end of the queue and the pointer to the object is updated.

35 CMPUT 425/525: Automatic Storage Management 35 Cheney Algorithm: Example Root Nodes A B F E D C A A A B B B C C C D D E A BCD E F B A scan free

36 CMPUT 425/525: Automatic Storage Management 36 Semispace Collector Using the Cheney Algorithm (Continued) Multiple paths must not be copied to tospace multiple times. When an object is transported to tospace, a forwarding pointer is installed in the old version of the object. The forwarding pointer signifies that the old object is obsolete and indicates where to find the new copy.

37 CMPUT 425/525: Automatic Storage Management 37 Copying Garbage Collection: Advantages and Disadvantages Advantages: – Allocation is extremely cheap. – Excellent asymptotic complexity. – Fragmentation is eliminated. – Only one pass through the data is required.

38 CMPUT 425/525: Automatic Storage Management 38 Copying Garbage Collection: Advantages and Disadvantages (Continued) Disadvantages: – The use of two semi-spaces doubles memory requirement needs – Poor locality. Using virtual memory will cause excessive paging.

39 CMPUT 425/525: Automatic Storage Management 39 Problems with Simple Tracing Collectors Difficult to achieve high efficiency in a simple garbage collector, because large amounts of memory are expensive. If virtual memory is used, the poor locality of the allocation/reclamation cycle will cause excessive paging. Even as main memory becomes steadily cheaper, locality within cache memory becomes increasingly important.

40 CMPUT 425/525: Automatic Storage Management 40 Problems with Simple Tracing Collectors (Continued) With a simple semispace copy collector, locality is likely to be worse than mark- sweep. The memory issue is not unique to copying collectors. Any efficient garbage collection involves a trade-off between space and time. The problem of locality is an indirect result of the use of garbage collection.

41 CMPUT 425/525: Automatic Storage Management 41 Incremental Tracing Collectors Overview Introduction to Incremental Collectors Coherence and Conservatism Tricolor Marking Write Barrier Algorithms Baker’s Read Barrier Algorithm

42 CMPUT 425/525: Automatic Storage Management 42 Incremental Tracing Collectors Program (Mutator) and Garbage Collector run concurrently. – Can think of system as similar to two threads. One performs collection, and the other represents the regular program in execution. Can be used in systems with real-time requirements. For example, process control systems.

43 CMPUT 425/525: Automatic Storage Management 43 Coherence & Conservatism Coherence: A proper state must be maintained between the mutator and the collector. Conservatism: How aggressive the garbage collector is at finding objects to be deallocated.

44 CMPUT 425/525: Automatic Storage Management 44 Tricoloring White – Not yet traversed. A candidate for collection. Black – Already traversed and found to be live. Will not be reclaimed. Grey – In traversal process. Defining characteristic is that it’s children have not necessarily been explored.

45 CMPUT 425/525: Automatic Storage Management 45 The Tricolor Abstraction

46 CMPUT 425/525: Automatic Storage Management 46 Tricoloring Invariant There must not be a pointer from a black object to a white object.

47 CMPUT 425/525: Automatic Storage Management 47 Violation of Coloring Invariant BeforeAfter A B C D A B C D

48 CMPUT 425/525: Automatic Storage Management 48 Steps in Violation Read a pointer to a white object Assign that pointer to a black object Original pointer must be destroyed without collection system noticing.

49 CMPUT 425/525: Automatic Storage Management 49 Read Barrier Barriers are essentially memory access detection systems. We detect when any pointers to any white objects are read. If a read to the pointer occurs, we conceptually color that object grey.

50 CMPUT 425/525: Automatic Storage Management 50 Write Barrier When a pointer is written to an object, we record the write somehow. The recorded write is dealt with at a later point. Read vs. Write efficiency considerations.

51 CMPUT 425/525: Automatic Storage Management 51 Write Barrier Algorithms Snapshot-at-beginning Incremental update

52 CMPUT 425/525: Automatic Storage Management 52 Snapshot-at-beginning Conceptually makes a copy-on-write duplication of the pointer graph. Can be implemented with a simple write barrier that records pointer writes and adds the old addresses to a stack to be traversed later.

53 CMPUT 425/525: Automatic Storage Management 53 Snapshot-at-beginning Example BeforeAfter A B C D A B C D Stack Pointer to D is now On stack

54 CMPUT 425/525: Automatic Storage Management 54 Comments on Snapshot-at- beginning Very conservative. All overwritten pointer values are saved and traversed. No objects can be freed while collection process is occurring.

55 CMPUT 425/525: Automatic Storage Management 55 Incremental Update Write- Barrier Algorithm No copy of tree is made. Catches overwrites of pointers that have been copied. – If a pointer is not copied before being written, it will be freed. The object with the overwritten pointer is colored grey and the algorithm must search that node again at the end.

56 CMPUT 425/525: Automatic Storage Management 56 Incremental Update Example BeforeAfter A B C D A B C D

57 CMPUT 425/525: Automatic Storage Management 57 Comments on Incremental Update Things that are freed during collection are far more likely to be collected than with the snapshot algorithm. (Less conservative) Although the collector restarts the traversal in some places, it is guaranteed to do a full search and will eventually terminate.

58 CMPUT 425/525: Automatic Storage Management 58 Baker’s Read Barrier Algorithms Incremental Copying Non-copying Algorithm (The Treadmill)

59 CMPUT 425/525: Automatic Storage Management 59 Incremental Copying Variation of Copying Collector “Garbage collection cycle begins with an atomic flip.” All objects directly pointed to by the root are copied into tospace.

60 CMPUT 425/525: Automatic Storage Management 60 Read Barrier in Incremental Copying Whenever an object is read that is not already in ToSpace, the read barrier catches that and copies the object over to ToSpace at that point. Normal “background scavenging” occurs simultaneously to ensure that all objects are traversed and reclamation can occur.

61 CMPUT 425/525: Automatic Storage Management 61 Incremental Copying Example A B C D FromSpaceToSpace Atomic Flip, then a read to D occurs… E DABC

62 CMPUT 425/525: Automatic Storage Management 62 Comments on Read Barrier If implemented in software can be quite slow due to numerous reads to heap. Specialized hardware is available on some unique machines that allow this type of tracing to be done quickly.

63 CMPUT 425/525: Automatic Storage Management 63 Baker’s Incremental Non- Copying Algorithm Doubly Linked Lists New area for allocations since started collection To/From spaces Free list New Free From To Allocation Scanning

64 CMPUT 425/525: Automatic Storage Management 64 Example - Allocation Take an object from the free list and move it to the new list. New Free From To Allocation Scanning

65 CMPUT 425/525: Automatic Storage Management 65 Example - Scanning Searching nodes in ToSpace for references to objects in FromSpace. When found, object is unlinked in FromSpace and is linked in ToSpace. New Free From To Allocation Scanning

66 CMPUT 425/525: Automatic Storage Management 66 Treadmill Workings When starting collection cycle: – New list is empty – From list contains all New and To objects from last cycle. Collection proceeds and scanning and allocation are performed. When finished: – From list is merged with Free list.

67 CMPUT 425/525: Automatic Storage Management 67 Comments on Treadmill As in Incremental Copying, the garbage found in the FromSpace is reclaimed in constant time. Conservative with new objects Conservative also in that reached objects will not be removed even if they become garbage before scan ends.

68 CMPUT 425/525: Automatic Storage Management 68 Incremental Collectors Summary Incremental Tracing Collectors Tricolor Marking and Invariant Read and Write Barriers Snapshot-at-beginning Incremental Update Baker’s Incremental Copying Baker’s Non-copying (Treadmill)

69 CMPUT 425/525: Automatic Storage Management 69 Generational Garbage Collection Attempts to address weaknesses of simple tracing collectors such as mark-sweep and copying collectors: – All active data must be marked or copied. – For copying collectors, each page of the heap is touched every two collection cycles, even though the user program is only using half the heap, leading to poor cache behavior and page faults. – Long-lived objects are handled inefficiently.

70 CMPUT 425/525: Automatic Storage Management 70 Generational Garbage Collection (Continued) Generational garbage collection is based on the generational hypothesis: Most objects die young. As such, concentrate garbage collection efforts on objects likely to be garbage: young objects.

71 CMPUT 425/525: Automatic Storage Management 71 Generational Garbage Collection: Object Lifetimes When we discuss object lifetimes, the amount of heap allocation that occurs between the object’s birth and death is used rather than the wall time. For example, an object created when 1Kb of heap was allocated and was no longer referenced when 4 Kb of heap data was allocated would have lived for 3Kb.

72 CMPUT 425/525: Automatic Storage Management 72 Generational Garbage Collection: Object Lifetimes (Continued) Typically, between 80 and 98 percent of all newly-allocated heap objects die before another megabyte has been allocated.

73 CMPUT 425/525: Automatic Storage Management 73 Generational Garbage Collection (Continued) Objects are segregated into different areas of memory based on their age. Areas containing newer objects are garbage collected more frequently. After an object has survived a given number of collections, it is promoted to a less frequently collected area.

74 CMPUT 425/525: Automatic Storage Management 74 Generational Garbage Collection: Example Old GenerationNew Generation Root Set S A B C Memory Usage

75 CMPUT 425/525: Automatic Storage Management 75 Generational Garbage Collection: Example (Continued) Old GenerationNew Generation Root Set S A B C Memory Usage R

76 CMPUT 425/525: Automatic Storage Management 76 Generational Garbage Collection: Example (Continued) Old GenerationNew Generation Root Set S A B C Memory Usage R D

77 CMPUT 425/525: Automatic Storage Management 77 Generational Garbage Collection: Example (Continued) This example demonstrates several interesting characteristics of generational garbage collection: – The young generation can be collected independently of the older generations (resulting in shorter pause times). – An intergenerational pointer was created from R to D. These pointers must be treated as part of the root set of the New Generation. – Garbage collection in the new generation result in S becoming unreachable, and thus garbage. Garbage in older generations (sometimes called tenured garbage) can not be reclaimed via garbage collections in younger generations.

78 CMPUT 425/525: Automatic Storage Management 78 Generational Garbage Collection: Implementation Usually implemented as a copying collector, where each generation has its own semispace: Old GenerationNew Generation FromSpace ToSpace

79 CMPUT 425/525: Automatic Storage Management 79 Generational Garbage Collection: Issues Choosing an appropriate number of generations: – If we benefit from dividing the heap into two generations, can we further benefit by using more than two generations? Choosing a promotion policy: – How many garbage collections should an object survive before being moved to an older generation?

80 CMPUT 425/525: Automatic Storage Management 80 Generational Garbage Collection: Issues (Continued) Tracking intergenerational pointers: – Inter-generational pointers need to be tracked, since they form part of the root set for younger generations. Collection Scheduling – Can we attempt to schedule garbage collection in such a way that we minimize disruptive pauses?

81 CMPUT 425/525: Automatic Storage Management 81 Generational Garbage Collection: Multiple Generations Generation 1Generation 2Generation 3Generation 4

82 CMPUT 425/525: Automatic Storage Management 82 Generational Garbage Collection: Multiple Generations (Continued) Advantages: – Keeps youngest generation’s size small. – Helps address mistakes made by the promotion policy by creating more intermediate generations that still get garbage collected fairly frequently. Disadvantages: – Collections for intermediate generations may be disruptive. – Tends to increase number of inter-generational pointers, increasing the size of the root set for younger generations. Most generational collectors are limited to just two or three generations.

83 CMPUT 425/525: Automatic Storage Management 83 Generational Garbage Collection: Promotion Policies A promotion policy determines how many garbage collections cycles (the cycle count) an object must survive before being advanced to the next generation. If the cycle count is too low, objects may be advanced too fast; if too high, the benefits of generational garbage collection are not realized.

84 CMPUT 425/525: Automatic Storage Management 84 Generational Garbage Collection: Promotion Policies (Continued) With a cycle count of just one, objects created just before the garbage collection will be advanced, even though the generational hypothesis states they are likely to die soon. Increasing the cycle count to two denies advancement to recently created objects. Under most conditions, it increasing the cycle count beyond two does not significantly reduce the amount of data advanced.

85 CMPUT 425/525: Automatic Storage Management 85 Generational Garbage Collection: Inter-generational Pointers Inter-generational pointers can be created in two ways: – When an object containing pointers is promoted to an older generation. – When a pointer to an object in a newer generation is stored in an object. The garbage collector can easily detect promotion- caused inter-generational pointers, but handling pointer stores is a more complicated task.

86 CMPUT 425/525: Automatic Storage Management 86 Generational Garbage Collection: Inter-generational Pointers Pointer stores can be tracked via the use of a write barrier: – Pointer stores must be accompanied by extra bookkeeping instructions that let the garbage collector know of pointers that have been updated. Often implemented at the compiler level.

87 CMPUT 425/525: Automatic Storage Management 87 Generational Garbage Collection: Inter-generational Pointers (Continued) However, write barriers only provide a conservative estimation of live intergenerational pointers: Old GenerationNew Generation Root Set

88 CMPUT 425/525: Automatic Storage Management 88 Generational Garbage Collection: Inter-generational Pointers (Continued) Tracking inter-generational pointers are often the largest cost of generational garbage collection. 1 percent of a typical Lisp program’s total instruction count are pointer stores. If a write barrier adds 10 instructions to a pointer store, overall performance will drop by 10 percent.

89 CMPUT 425/525: Automatic Storage Management 89 Generational Garbage Collection: Inter-generational Pointers (Continued) Entry Tables – Pointers from older generations point indirectly to younger generations via an entry table: Generation 2Generation 1Generation 3 Entry Table

90 CMPUT 425/525: Automatic Storage Management 90 Generational Garbage Collection: Inter-generational Pointers (Continued) Entry Table: Advantages – When a younger generation is collected, only the entry table for that generation needs to be scanned. Entry Table: Disadvantages – Entry table may contain several entries to the same object, making scans of the object table proportional to the number of pointer stores rather than to the number of inter-generational pointers. – High overhead because of extra level of indirection.

91 CMPUT 425/525: Automatic Storage Management 91 Generational Garbage Collection: Inter-generational Pointers (Continued) Remembered Sets – The write barrier checks to see if a pointer being stored in an old objects points to an object in a newer generation. If so, the address of the old object is added to the remembered set (if that object is not already in the set).

92 CMPUT 425/525: Automatic Storage Management 92 Generational Garbage Collection: Inter-generational Pointers (Continued) Remembered Sets (Continued) New GenerationOld Generation Remembered Set

93 CMPUT 425/525: Automatic Storage Management 93 Generational Garbage Collection: Inter-generational Pointers (Continued) Remembered Sets: Advantages – Scanning is proportional to the number of stored-into objects, not the number of store operations. Remembered Sets: Disadvantages – Pointer store checking can be expensive.

94 CMPUT 425/525: Automatic Storage Management 94 Generational Garbage Collection: Collection Scheduling Generational garbage collection aims to reduce pause times. When should these (hopefully short) pause times occur? Two strategies exist: – Hide collections when the user is least likely to notice a pause, or – Trigger efficient collections when there is likely to be lots of garbage to collect.

95 CMPUT 425/525: Automatic Storage Management 95 Generational Garbage Collection: Advantages In practice it has proven to be an effective garbage collection technique. Minor garbage collections are performed quickly. Good cache and virtual memory behavior.

96 CMPUT 425/525: Automatic Storage Management 96 Generational Garbage Collection: Disadvantages Performs poorly if any of the main assumptions are false: – That objects tend die young. – That there are relatively few pointers from old objects to young ones. Frequent pointer writes to older generations will increase the cost of the write barrier, and possibly increase the size of the root set for younger generations.

97 CMPUT 425/525: Automatic Storage Management 97 Garbage Collection: Summary MethodConservatismSpaceTimeFragmentationLocality Mark SweepMajorBasic1 traversal + heap scan YesFair Mark CompactMajorBasicMany passes of heap NoGood CopyingMajorTwo Semispaces 1 traversalNoPoor Reference Counting NoReference count field Constant per Assignment YesVery Good Deferred Reference Counting Only for stack variables Reference Count Field Constant per Assignment YesVery Good IncrementalVaries depending on algorithm VariesCan be Guaranteed Real-Time Varies GenerationalVariableSegregated Areas Varies with number of live objects in new generation Yes (Non- Copying) No (Copying) Good Tracing Incremental

98 CMPUT 425/525: Automatic Storage Management 98 Garbage Collection: Conclusions Relieves the burden of explicit memory allocation and deallocation. Software module coupling related to memory management issues is eliminated. An extremely dangerous class of bugs is eliminated.

99 CMPUT 425/525: Automatic Storage Management 99 Garbage Collection: Conclusions (Continued) Zorn’s study in 1989/93 compared garbage collection to explicit deallocation: – Non-generational Between 0% and 36% more CPU time. Between 40% and 280% more memory. – Generational garbage collection Between 5% to 20% more CPU time. Between 30 and 150% more memory. Wilson feels these numbers can be improved, and they are also out of date. A well implemented garbage collector will slow a program down by approximately 10 percent relative to explicit heap deallocation.

100 CMPUT 425/525: Automatic Storage Management 100 Garbage Collection: Conclusions (Continued) Despite this cost, garbage collection a feature in many widely used languages: – Lisp (1959) – Perl (1987) – Java (1995) – C# (2001) – Microsoft’s Common Language Runtime (2002)

101 CMPUT 425/525: Automatic Storage Management 101 Garbage Collection: Pointers Heap of fish applet (Mark and Sweep garbage collection example) Java HotSpot Garbage Collection Strategies The Memory Management Reference Uniprocessor Garbage Collection Techniques (Wilson) Garbage Collection: Algorithms for Automatic Dynamic Memory Management (Richard Jones and Rafael Lins)

102 CMPUT 425/525: Automatic Storage Management 102 Questions? If you have any questions, please feel free to one of us: Patrick Earl Simon Leonard Jack Newton


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