Arena storage pool: Difference between revisions

 

The storage pool chosen by the allocator can be determined by either:

 

# allocate some objects (e.g., integers) in the pool.

Explain what controls the storage pool choice in the language.

 

=={{header|Ada}}==

In [[Ada]] the choice of storage pool is controlled by the type of the pointer. Objects pointed by anonymous access types are allocated in the default storage pool. Pool-specific pointer types may get a pool assigned to them:

The following example illustrates implementation of an arena pool. Specification:

with System.Storage_Pools; use System.Storage_Pools;

 

Core : Storage_Array (1..Size);

end record;

Here is an implementation of the package:

procedure Allocate

( Pool : in out Arena;

return Pool.Size;

end Storage_Size;

The following is a test program that uses the pool:

use Arena_Pools;

 

Z := new Integer;

Z.all := X.all + Y.all;

 

=={{header|C}}==

 

To use dynamic memory, the header for the standard library must be included in the module.

Uninitialized memory is allocated using the malloc function. To obtain the amount of memory that needs to be allocated, sizeof is used. Sizeof is not a normal C function, it is evaluated by the compiler to obtain the amount of memory needed.

Typename *var = malloc(sizeof(Typename));

Since pointers to structures are needed so frequently, often a

typedef will define a type as being a pointer to the associated structure.

Once one gets used to the notation, programs are actually easier to read, as the

variable declarations don't include all the '*'s.

 

The calloc() function initializes all allocated memory to zero. It is also often

used for allocating memory for arrays of some type.

MyType var = calloc(n, sizeof(sMyType));

 

MyType third = var+3; /* a reference to the 3rd item allocated */

 

Freeing memory dynamically allocated from the heap is done by calling free().

One can allocate space on the stack using the alloca() function. You do not

free memory that's been allocated with alloca

An object oriented approach will define a function for creating a new object of a class.

In these systems, the size of the memory that needs to be allocated for an instance of the

Without using the standard malloc, things get a bit more complicated. For example, here is some code that implements something like it using the mmap system call (for Linux):

 

#include <unistd.h>

#include <stdio.h>

return 0;

 

This is ''not'' how the real malloc is implemented on Linux. For one, memory leaks cannot be caught by Valgrind, and using a linked list to keep track of allocated blocks is very inefficient.

* You can replace the global allocation/deallocation routines, which are used by new/delete whenever there are no class specific functions available.

* You can write operator new/operator delete with additional arguments, both in a class and globally. To use those, you add those parameters after the keyword <code>new</code>, like

* In addition, for objects in containers, there's a completely separate allocator interface, where the containers use an allocator object for allocating/deallocating memory.

 

The following code uses class-specific allocation and deallocation functions:

 

#include <cassert>

#include <new>

delete my_second_pool // also deallocates the memory for p6 and p7

 

=={{header|Delphi}}==

{{libheader| Winapi.Windows}}

{{libheader| System.SysUtils}}

{{libheader| system.generics.collections}}

program Arena_storage_pool;

 

Manager.Free;

readln;

{{out}}

<pre>Allocate at addres 026788D0 with value of 5

Given automatic memory handling the only way to ask for memory in Erlang is when creating a process. Likewise the only way to manually return memory is by killing a process. So the pool could be built like this. The unit for memory is word, b.t.w.

 

-module( arena_storage_pool ).

 

 

set( Pid, Key, Value ) -> Pid ! {set, Key, Value}.

 

=={{header|Fortran}}==

Thus, in a sense, a group of items for which storage has been allocated can have their storage released en-mass by exiting the routine. However, it is not the case that items A, B, C can be allocated in one storage "area" (say called "Able") and another group D, E in a second named area (say "Baker"), and that by discarding "Able" all its components would be de-allocated without the need to name them in tedious detail.

 

REAL A(:,:) !The matrix, whatever size it is.

INTEGER N !The order.

 

DEALLOCATE(TROUBLE) !Not necessary.

 

Whereas previously a problem might not be solvable via the existing code because of excessive fixed-size storage requirements, now reduced demands can be made and those only for subroutines that are in action. Thus larger problems can be handled without agonising attempts to cut-to-fit, the usage for scratchpads such as B being particularly natural as in Algol from the 1960s. But on the other hand, a run might exhaust the available storage (either via the stack or via the heap) somewhere in the middle of job because its particular execution path made too many requests and the happy anticipation of results is instead met by a mess - and a bigger mess, because larger problems are being attempted.

 

=={{header|Go}}==

 

import (

*j = 8

fmt.Println(*i + *j) // prints 15

{{output}}

<pre>

For example, you can define a class which allocates a pool of integers:

 

require 'jmf'

create=: monad define

set=: adverb define

y memw m

 

With this script you can then create instances of this class, and use them. In this case, we will create a pool of three integers:

 

x0=: alloc__pool0 0

x1=: alloc__pool0 0

x2 set__pool0 9

x0 get__pool0 + x1 get__pool0 + x2 get__pool0

 

Finally, the pool can be destroyed:

 

 

That said, using J's built-in support for integers (and for using them) usually results in better code.

 

=={{header|Julia}}==

For example, a large 1000 X 1000 X 1000 matrix that will need to be changed repeatedly might be

allocated and initialized to zero with:

matrix = zeros(Float64, (1000,1000,1000))

# use matrix, then when done set variable to 0 to garbage collect the matrix:

matrix = 0 # large memory pool will now be collected when needed

 

=={{header|Kotlin}}==

 

To make life easier for the programmer when a number of allocations are required, it is possible for these to take place under the auspices of a MemScope object (an 'arena') which implements NativePlacement and automatically frees up the memory for these objects when they are no longer in scope. The process is automated by the memScoped function which takes a block as a parameter whose receiver is an implicit MemScope object. Here's a very simple example:

 

import kotlinx.cinterop.*

}

// native memory used by intVar1 & intVar2 is automatically freed when memScoped block ends

 

{{output}}

1 + 2 = 3

</pre>

 

Mathematica does not allow stack/heap control, so all variables are defined on the heap. However, tags must be given a ''value'' for a meaningful assignment to take place.

 

=={{header|Nim}}==

Nim proposes two ways to manage memory. In the first one, objects are allocated on the heap using "new" and their deallocation is managed by the compiler and the runtime. In this case, objects are accessed via references ("ref").

 

The second method to allocate objects on the heap consists to do this the C way, using procedures "alloc" or "alloc0" to get blocks of memory. The deallocation is managed by the user who must call "dealloc" to free the memory. Using this method, objects are accessed via pointers ("ptr").

 

The preferred way is of course to use references which are safe. To allow a better fit to user needs, Nim proposes several options for automatic memory management. By specifying "--gc:refc" in the command line to launch the compilation, a garbage collector using reference counting is used. This is currently the default. Others options are "markAndSweep", "boehm" and "go" to use a different GC, each one having its pros and cons. "--gc:none" allows to deactivate totally automatic memory management which limits considerably the available functionnalities.

 

Since version 1.2, two more options are proposed. The first one, "--gc:arc" allows to choose the "arc" memory management which, in fact, is not a garbage collector. This is the most efficient option but it cannot free data structures containing cycles. The second option, "--gc:orc", allows to choose the "orc" memory management which is in fact "arc" with a cycle detection mechanism. It will probably become the default option in a future version.

 

In some cases, especially when a lot of similar objects must be allocated, it is a good idea to use a pool. It allows to allocate by blocks and to free globally.

 

Nim doesn’t propose any mechanism to manage such pools. There is an option "regions" which may be useful for this purpose but it is experimental and not documented. So, we will ignore it for now.

 

One way to manage pools consists to allocate blocks of memory and use some pointer arithmetic to return pointers to objects. The blocks may be allocated using "new" (and in this case will be freed automatically) or using "alloc" or "alloc0" and the deallocation must be required explicitely.

 

We provide here an example using blocks allocated by "new".

 

####################################################################################################

# Pool management.

test()

 

 

{{out}}

There is no user-defined storage pool and it is not possible to explicitly destroy an object.

 

 

=={{header|ooRexx}}==

 

=={{header|OxygenBasic}}==

'==============

Class ArenaPool

 

pool.empty

 

=={{header|PARI/GP}}==

 

PARI allocates objects on the PARI stack by default, but objects can be allocated on the heap if desired.

GEN four = addii(gen_2, gen_2); // On the stack

 

=={{header|Pascal}}==

{{works with|Free_Pascal}}

The procedure New allocates memory on the heap:

 

The Pointer P is typed and the amount of memory allocated on the heap matches the type. Deallocation is done with the procedure Dispose. In ObjectPascal constructors and destructors can be passed to New and Dispose correspondingly. The following example is from the rtl docs of [[Free_Pascal]]

 

{ Program to demonstrate the Dispose and New functions. }

Type

T^.i := 0;

Dispose ( T, Done );

 

Instead of implicit specification of the amount of memory using a type, the explicit amount can directly specified with the procedure getmem (out p: pointer; Size: PtrUInt);

 

The simplest approach however is to rely on automatic memory management (as used by pGUI, and first implemented after arwen and win32lib were originally written):

If the optional cleanup flag is non-zero (or true, as above), the memory is automatically released once it is no longer required

(ie when the variable mem drops out of scope or gets overwritten, assuming you have not made a copy of it elsewhere, which would

 

For completeness, here is a very simplistic arena manager, with just a single pool, not that it would be tricky to implement multiple pools:

 

=={{header|PicoLisp}}==

 

As is common with high-level languages, Racket usually deals with memory automatically. By default, this means using a precise generational GC. However, when there's need for better control over allocation, we can use the <tt>malloc()</tt> function via the FFI, and the many variants that are provided by the GC:

(malloc 1000 'raw) ; raw allocation, bypass the GC, requires free()-ing

(malloc 1000 'uncollectable) ; no GC, for use with other GCs that Racket can be configured with

(malloc 1000 'atomic-interior) ; same for atomic chunks

(malloc-immobile-cell v) ; allocates a single cell that the GC will not move

 

=={{header|Raku}}==

memory is available (these were written when real storage was a premium

during the early DOS days).

/* but this is the closest to an allocation: */

 

stemmed_array.dog = stemmed_array.6000 / 2

 

 

=={{header|Rust}}==

 

extern crate arena;

// The arena's destructor is called as it goes out of scope, at which point it deallocates

// everything stored within it at once.

 

=={{header|Scala}}==

 

The pool engine class itself (a metaclass):

oo::class create Pool {

superclass oo::class

return $cls

}

Example of how to use:

variable int

 

}

puts ""

Produces this output (red text to <tt>stderr</tt>, black text to <tt>stdout</tt>):

<span style="color:red">Initializing ::oo::Obj4::Obj5 with 0

Finalizing ::oo::Obj4::Obj6 which held 10

Finalizing ::oo::Obj4::Obj7 which held 11</span>

 

=={{header|zkl}}==

Memory allocation "just happens", unreachable memory is recovered via garbage collection. The closest thing to explicit memory allocation is Data object, which is a bit bucket you can [optionally] set the size of upon creation. However, it grows as needed. The closest thing to "new" is the create method, which tells an object to create a new instance of itself. For this task:

pool.append(Data(0,1234)); // allocate mem blob and add to pool

 

{{omit from|Clojure}}

{{omit from|Erlang|Erlang does not have a program-controllable heap.}}

{{omit from|Oz|Oz does not have a program-controllable heap.}}

{{omit from|TI-89 BASIC|Does not have controlled memory allocation.}}