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Lisp does its own memory management. The garbage collector is part of the memory management system. It disposes of objects that are no longer needed, freeing up the space that they occupied. While the garbage collector is working, no other work can be done. Therefore, we have made the garbage collector as fast and unobtrusive as possible.

Allegro CL uses a version of the generation-scavenging method of garbage collection. Because optimal performance of generation-scavenging garbage collection depends on the application, you have a great deal of control over how the garbage collector works. In this section, we will describe the user interface to the garbage collector, and suggest how to tune its performance for an application.

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In what follows, the generation-scavenging garbage collection system will be abbreviated gsgc , and the act of garbage collecting will be abbreviated gc.

Symbols naming gc-related functionality are generally in the :excl package or the :system package. The Allegro CL garbage collector is a two-space, generation-scavenging system.

The two spaces are called newspace and oldspace. Note that, as we describe below, newspace is divided into two pieces, called areas, and oldspace may be divided into a number of pieces, also called areas.

Generally, when we say newspace, we mean both newspace areas and when we say oldspace, we mean all oldspace areas. Usually, the context should make this clear. Scavenges eliminate all garbage in newspace and may retain live objects in newspace or move them to oldspace. Scavenges are typically very fast and reasonably frequent.

They are not under user control, but rather triggered automatically when necessary. The section Section 1. The features described in this section were added in release Note this feature is not implemented in Sparc Solaris Lisps. When extra cores are available, this can have a significant effect on global gc time, since the gc worker threads can run concurrently.

The function sys:gc-parameters returns or prints information about aspects of the gc setup. The related sys:gc-parameter returns information about specific parameters and sys:gc-switch returns information about gc switches. Where appropriate, they can be used with setf to reset values.

There is always one gc thread, so helper threads are in addition to that thread. Users might vary :helper-threads-requested to see what effect it has on pause times. There is no reason to make :helper-threads-requested larger than the number of cores available minus 1.

The number of cores available is the actual number of cores less any that are dedicated to other purposes, such as managing video. See Section 5.

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Some Lisp values exist on the stack. However, some values on the stack may not be real. When a variable is placed on the stack or when the stack pointer is moved so the stack is larger, values are not initialized since doing so would slow down execution time noticeably. During a gc scavenge or global , the stack is scanned and pointers are evaluated. Some do not point to Lisp values. Those are leftovers and can be ignored. But some point to valid Lisp objects.

A conservative approach treats any valid object pointed to from the stack as live.

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A precise approach determines by other means which pointers should be considered and follows only those to objects, which it marks as live. Other pointers are ignored and so do not themselves keep objects alive.

Allegro CL uses a hybrid approach: precise where possible and conservative where precision is not possible. The conservative approach is used when the system considers it likely the function is being debugged because it has stopped at an unexpected place , or when information on the frame is insufficient to tell whether pointers in it should be considered, or when determining whether the frame should be considered will itself take too much time.

The precise approach is used whenever possible and is the typical approach used. The benefit of the conservative approach is that it is easy to implement, which is why it is what was implemented for many releases. A more serious consequence is weak vectors are prevented from being cleared and finalizations are delayed see Section This code snippet happens to work in 9. But the value is in fact returned from that let form, thus making a lie out of that dynamic-extent declaration.

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  • If any other dynamic-extent allocations are performed in the body, or if a tail-call is performed, the array which is now dead will be overwritten. The reason why this technique works in 9.

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    This allows the fudging of dynamic-extent declarations shown above, but it also creates potentially huge wastes of space in the stack, forcing the conservative-gc to scan and validate more slots which increases the risk of dead slots being unnecessarily forwarded.

    Now dynamic extent objects on the stack are put in a single, Last In, First Out lifo area and objects can be freed when logically they are outside the scope of the dynamic extent declarations. That means in our example, sarray may be overwritten before it is in fact truly garbage. Care must be excercise to ensure dynamic extent declarations are proper.

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    The more compact representation of stack-allocated objects in The process known as reward assessment during a global gc estimates how much space will be saved by the adjustment and compactification phases of a global gc. If the estimate is less than the value of the :minimum-recovery-bytes parameter, those phases are skipped. This can result in a significant time saving. Adjustment and compatification moves objects in oldspace.

    When an object is moved, all pointers to that object must be found and updated. Skipping adjustment and compactification means that pointers to live objects in oldspace are automatically valid and do not have to be found or updated.

    Note dead objects in oldspace are discarded regardless of whether adjustment and compactification is performed or not. See the sys:gc-parameter function.

    When called with :minimum-recovery-bytes as its required argument, it returns the value of the parameter:. The two pieces of newspace are managed as a stop-and-copy garbage collector system.

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    The two areas are the same size. At any one time, one area is active and the other is not. A newspace area is filled from one end to the other. Imagine, for example, a book shelf.

    Existing books are packed together on the right side. Each new book is placed just to the left of the leftmost book. It may happen that books already placed are removed, leaving gaps, but these gaps are ignored, with each new book still being placed to the left of the location of the last new book.

    When the shelf fills up, the other shelf newspace area is used. First, all books remaining are moved to the other shelf, packed tight to one side, and new books are placed in the next free location. So with Lisp objects in newspace areas. All existing objects are packed together on one side of the area and new objects are placed in the free space next to the existing objects, with gaps left by objects which are no longer alive being ignored.

    When the area fills up, Lisp stops and copies all live objects to the other area, packing them tight. Then the process is repeated.

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    The process of copying objects from one newspace area to the other is called a scavenge. We will discuss the speed of scavenges below, but scavenges are supposed to be so fast that humans usually barely notice them.

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    The first listed cause is under user-control. The second and third causes are under system control and the resulting scavenge cannot be prevented if the system determines it must occur. The system keeps track of the age of objects in newspace by counting the number of scavenges that the object has survived. The number of scavenges survived is called the generation of an object.

    When objects are created, they have generation 1, and the generation is increased by 1 at each scavenge. Of course, many objects become garbage as time passes.

    An object is garbage when there are no pointers to it from any other live object.

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    If there are no pointers to an object, nothing can reference or access it and so it is guaranteed never to be looked at again. Thus, it is garbage. The theory of a generation scavenging garbage collector is that most objects that will ever become garbage will do so relatively quickly and so will not survive many scavenges.

    The problem with a stop-and-copy system is that objects that survive have to be moved and moving objects takes time. If an object is going to be around for a while or for the entire Lisp session , it should be moved out of newspace to some place where it does not have to be moved or is moved much less often. This is where the other half of the generation scavenging algorithm comes into play. Once an object has survived enough scavenges, it is assumed to be long-lived and is moved to oldspace.

    Oldspace is not touched during scavenges and so objects in oldspace are not moved during scavenges, thus saving considerable time over a pure stop-and-copy system. Part of a scavenge is checking the age generation of surviving objects and moving those that are old enough to oldspace.

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  • The remaining objects are moved to the other newspace area. The age at which objects are tenured is user-settable. Its initial value is 4 and that seems to work for many applications. We will discuss below how changing that and many other settings can affect gc performance.