I saw this question:
Fortran dynamic objects
and the accepted answer made me question if I wrote the following function safely (without allowing a memory leak)
function getValues3D(this) result(vals3D)
implicit none
type(allBCs),intent(in) :: this
real(dpn),dimension(:,:,:),pointer :: vals3D
integer,dimension(3) :: s
if (this%TF3D) then
s = shape(this%vals3D)
if (associated(this%vals3D)) then
stop "possible memory leak - p was associated"
endif
allocate(vals3D(s(1),s(2),s(3)))
vals3D = this%vals3D
else; call propertyNotAssigned('vals3D','getValues3D')
endif
end function
This warning shows up when I run my code, but shouldn't my this%vals3D be associated if it was previously (to this function) set? I'm currently running into memory errors, and they started showing up when I introduced a new module with this function in it.
Any help is greatly appreciated.
I think I wasn't specific enough. I would like to make the following class, and know how to implement the class, safely in terms of memory. That is:
module vectorField_mod
use constants_mod
implicit none
type vecField1D
private
real(dpn),dimension(:),pointer :: x
logical :: TFx = .false.
end type
contains
subroutine setX(this,x)
implicit none
type(vecField1D),intent(inout) :: this
real(dpn),dimension(:),target :: x
allocate(this%x(size(x)))
this%x = x
this%TFx = .true.
end subroutine
function getX(this) result(res)
implicit none
real(dpn),dimension(:),pointer :: res
type(vecField1D),intent(in) :: this
nullify(res)
allocate(res(size(this%x)))
if (this%TFx) then
res = this%x
endif
end function
end module
Where the following code tests this module
program testVectorField
use constants_mod
use vectorField_mod
implicit none
integer,parameter :: Nx = 150
real(dpn),parameter :: x_0 = 0.0
real(dpn),parameter :: x_N = 1.0
real(dpn),parameter :: dx = (x_N - x_0)/dble(Nx-1)
real(dpn),dimension(Nx) :: x = (/(x_0+dble(i)*dx,i=0,Nx-1)/)
real(dpn),dimension(Nx) :: f
real(dpn),dimension(:),pointer :: fp
type(vecField1D) :: f1
integer :: i
do i=1,Nx
f(i) = sin(x(i))
enddo
do i=1,10**5
call setX(f1,f) !
f = getX(f1) ! Should I use this?
fp = getX(f1) ! Or this?
fp => getX(f1) ! Or even this?
enddo
end program
Currently, I'm running on windows. When I CTR-ALT-DLT, and view performance, the "physical memory usage histery" increases with every loop iteration. This is why I assume that I have a memory leak.
So I would like to repose my question: Is this a memory leak? (The memory increases with every one of the above cases). If so, is there a way I avoid the memory leak while still using pointers? If not, then what is happening, should I be concerned and is there a way to reduce the severity of this behavior?
Sorry for the initial vague question. I hope this is more to the point.
Are you really restricted to Fortran 90? In Fortran 2003 you would use an allocatable function result for this. This is much safer. Using pointer function results, whether you have a memory leak with this code or not depends on how you reference the function, which you don't show. If you must return a pointer from a procedure, it is much safer to return it via a subroutine argument.
BUT...
This function is pointless. There's no point testing the association status of this%vals3D` after you've referenced it as the argument to SHAPE in the previous line. If the pointer component is disassocated (or has undefined pointer association status), then you are not permitted to reference it.
Further, if the pointer component is associated, all you do is call stop!
Perhaps you have transcribed the code to the question incorrectly?
If you simply delete the entire if construct starting with if (associated(this%vals3D))... then your code may make sense.
BUT...
if this%TF3D is true, then this%vals3D must be associated.
when you reference the function, you must use pointer assignment
array_ptr => getValues3D(foo)
! ^
! |
! + this little character is very important.
Forget that little character and you are using normal assignment. Syntactically valid, difficult to pick the difference when reading code and, in this case, potentially a source of memory corruption or leaks that might go undetected until the worst possible moment, in addition to the usual pitfalls of using pointers (e.g. you need to DEALLOCATE array_ptr before you reuse it or it goes out of scope). This is why functions returning pointer results are considered risky.
Your complete code shows several memory leaks. Every time you allocate something that is a POINTER - you need to pretty much guarantee that there will be a matching DEALLOCATE.
You have a loop in your test code. ALLOCATE gets called a lot - in both the setter and the getter. Where are the matching DEALLOCATE statements?
Every time setX is called, any previously allocated memory for the x component of your type will be leaked. Since you call the function 10^5 times, you will waste 100000-1 copies. If you know that the size of this%x will never change, simply check to see if a previous call had already allocated the memory by checking to see if ASSOCIATED(this%x) is true. If it is, skip the allocation and move directly to the assignment statement. If the size does change, then you will first have to deallocate the old copy before allocating new space.
Two other minor comments on setX: The TARGET attribute of the dummy argument x appears superfluous since you never take a pointer of that argument. Second, the TFx component of your type also seems superfluous since you can instead check if x is allocated.
For the function getX, why not skip the allocation completely, and merely set res => this%x? Admittedly, this will return a direct reference to the underlying data, which maybe you want to avoid.
In your loop,
do i=1,10**5
call setX(f1,f) !
f = getX(f1) ! Should I use this?
fp = getX(f1) ! Or this?
fp => getX(f1) ! Or even this?
enddo
fp => getX(f1) will allow you to obtain a pointer to the underlying x component of your type (if you adopt my change above). The other two use assignment operators and will copy data from the result of getX into either f, or (if it is previously allocated) fp. If fp is not allocated, the code will crash.
If you do not want to grant direct access to the underlying data, then I suggest that the return value of getX should be defined as an automatic array with the size determined by this%x. That is, you can write the function as
function getX(this) result(res)
implicit none
type(vecField1D),intent(in) :: this
real(dpn),dimension(size(this%x,1)) :: res
res = this%x
end function
Related
Usually the multiple dispatch in julia is straightforward if one of the parameters in a function changes data type, for example Float64 vs Complex{Float64}. How can I implement multiple dispatch if the parameter is an integer, and I want two functions, one for even and other for odd values?
You may be able to solve this with a #generated function: https://docs.julialang.org/en/v1/manual/metaprogramming/#Generated-functions-1
But the simplest solution is to use an ordinary branch in your code:
function foo(x::MyType{N}) where {N}
if isodd(N)
return _oddfoo(x)
else
return _evenfoo(x)
end
end
This may seem as a defeat for the type system, but if N is known at compile-time, the compiler will actually select only the correct branch, and you will get static dispatch to the correct function, without loss of performance.
This is idiomatic, and as far as I know the recommended solution in most cases.
I expect that with type dispatch you ultimately still are calling after a check on odd versus even, so the most economical of code, without a run-time penatly, is going to be having the caller check the argument and call the proper function.
If you nevertheless have to be type based, for some reason unrelated to run-time efficiency, here is an example of such:
abstract type HasParity end
struct Odd <: HasParity
i::Int64
Odd(i::Integer) = new(isodd(i) ? i : error("not odd"))
end
struct Even <: HasParity
i::Int64
Even(i::Integer) = new(iseven(i) ? i : error("not even"))
end
parity(i) = return iseven(i) ? Even(i) : Odd(i)
foo(i::Odd) = println("$i is odd.")
foo(i::Even) = println("$i is even.")
for n in 1:4
k::HasParity = parity(n)
foo(k)
end
So here's other option which I think is cleaner and more multiple dispatch oriented (given by a coworker). Let's think N is the natural number to be checked and I want two functions that do different stuff depending if N is even or odd. Thus
boolN = rem(N,2) == 0
(...)
function f1(::Val{true}, ...)
(...)
end
function f1(::Val{false}, ...)
(...)
end
and to call the function just do
f1(Val(boolN))
As #logankilpatrick pointed out the dispatch system is type based. What you are dispatching on, though, is well established pattern known as a trait.
Essentially your code looks like
myfunc(num) = iseven(num) ? _even_func(num) : _odd_func(num)
Generally speaking I want to rename allocatable variables in a derived type that are passed through subroutine arguments. Writing everything with 'derived%type_xx' is not so pleasant. Besides, I don't want to spend extra memory on copying the values of the derived type to a new variable which costs new allocated memory. Furthermore, I know allocatable arrays are preferred than pointers for many reasons. I try to define pointers to the allocatable variable, but failed. I tried this because I want to simplify my code, both to be readable and not to be too long. I wonder if there's a way of achieving the goal? Thanks.
Here's the demonstration code:
Module module_type
IMPLICIT NONE
TYPE type_1
REAL,ALLOCATABLE :: longname_1(:), longname_2(:)
END TYPE
END MODULE
!------------------------------------------------------------------------------------------
SUBROUTINE TEST(input)
USE MODULE module_type
IMPLICIT NONE
TYPE(type_1) :: input
input%longname_1 = input%longname_1 + input%longname_2 ! Use one line to show what I mean
END SUBROUTINE
And here's what failed:
Module module_type
IMPLICIT NONE
TYPE type_1
REAL,ALLOCATABLE :: longname_1(:), longname_2(:)
END TYPE
END MODULE
!------------------------------------------------------------------------------------------
SUBROUTINE TEST(input)
USE MODULE module_type
IMPLICIT NONE
TYPE(type_1),TARGET :: input
REAL,POINTER :: a => input%longname_1 &
& b => input%longname_2
a = a + b ! much better for reading
END SUBROUTINE
It seems like a small issue, but I'd like to read my code without too much pain in the future. So what's the best option? Thanks a lot.
You can use the ASSOCIATE construct to associate a simple name with a more complex designator or expression.
You could also use the subobjects of the derived type as actual arguments to a procedure that carried out the operation.
You pointer approach failed because you had a rank mismatch - you were attempting to associate scalar pointers with array targets. You may also have had problems if an explicit interface to your procedure was not available in the calling scope. An explicit interface is required for procedures with dummy arguments with the TARGET attribute.
Use of pointers for this sort of simple name aliasing may reduce the ability of the compiler to optimize the code. Something like ASSOCIATE should be preferred.
Update: After #IanH made his comment, I have gone back to check: I was completely and utterly wrong on why your code failed. As he pointed out in his answer, the main issue is that pointer and target have to have the same rank, so you'd have to declare a and b as:
real, pointer :: a(:), b(:)
Secondly, before you can actually point these pointers to the targets, the targets have to be allocated. Here's an example that works:
program allocatable_target
implicit none
type :: my_type
integer, allocatable :: my_array(:)
end type my_type
type(my_type), target :: dummy
integer, pointer :: a(:)
allocate(dummy%my_array(10))
a => dummy%my_array
a = 10
print *, dummy%my_array
end program allocatable_target
If you have a Fortran 2003 compatible compiler, you can use associate -- which is specifically meant for this kind of issue. Here's an example:
program associate_example
implicit none
type :: my_type
integer, allocatable :: long_name_1(:), long_name_2(:)
end type my_type
type(my_type) :: input
integer :: i
allocate(input%long_name_1(100), input%long_name_2(100))
associate (a=>input%long_name_1, b=>input%long_name_2)
a = (/ (i, i = 1, 100, 1) /)
b = (/ (2*i+4, i = 1, 100, 1) /)
a = a + b
end associate
print *, input%long_name_1
end program associate_example
Inside the associate block, you can use a and b as a shortform for the declared longer named variables.
But other than that, I suggest you get an editor with proper code completion, then long variable names are not that much of an issue any more. At the moment I'm trying out Atom and am quite happy with it. But I have used vim with the proper expansions for a long time.
Is there a way to enforce a dictionary being constant?
I have a function which reads out a file for parameters (and ignores comments) and stores it in a dict:
function getparameters(filename::AbstractString)
f = open(filename,"r")
dict = Dict{AbstractString, AbstractString}()
for ln in eachline(f)
m = match(r"^\s*(?P<key>\w+)\s+(?P<value>[\w+-.]+)", ln)
if m != nothing
dict[m[:key]] = m[:value]
end
end
close(f)
return dict
end
This works just fine. Since i have a lot of parameters, which i will end up using on different places, my idea was to let this dict be global. And as we all know, global variables are not that great, so i wanted to ensure that the dict and its members are immutable.
Is this a good approach? How do i do it? Do i have to do it?
Bonus answerable stuff :)
Is my code even ok? (it is the first thing i did with julia, and coming from c/c++ and python i have the tendencies to do things differently.) Do i need to check whether the file is actually open? Is my reading of the file "julia"-like? I could also readall and then use eachmatch. I don't see the "right way to do it" (like in python).
Why not use an ImmutableDict? It's defined in base but not exported. You use one as follows:
julia> id = Base.ImmutableDict("key1"=>1)
Base.ImmutableDict{String,Int64} with 1 entry:
"key1" => 1
julia> id["key1"]
1
julia> id["key1"] = 2
ERROR: MethodError: no method matching setindex!(::Base.ImmutableDict{String,Int64}, ::Int64, ::String)
in eval(::Module, ::Any) at .\boot.jl:234
in macro expansion at .\REPL.jl:92 [inlined]
in (::Base.REPL.##1#2{Base.REPL.REPLBackend})() at .\event.jl:46
julia> id2 = Base.ImmutableDict(id,"key2"=>2)
Base.ImmutableDict{String,Int64} with 2 entries:
"key2" => 2
"key1" => 1
julia> id.value
1
You may want to define a constructor which takes in an array of pairs (or keys and values) and uses that algorithm to define the whole dict (that's the only way to do so, see the note at the bottom).
Just an added note, the actual internal representation is that each dictionary only contains one key-value pair, and a dictionary. The get method just walks through the dictionaries checking if it has the right value. The reason for this is because arrays are mutable: if you did a naive construction of an immutable type with a mutable field, the field is still mutable and thus while id["key1"]=2 wouldn't work, id.keys[1]=2 would. They go around this by not using a mutable type for holding the values (thus holding only single values) and then also holding an immutable dict. If you wanted to make this work directly on arrays, you could use something like ImmutableArrays.jl but I don't think that you'd get a performance advantage because you'd still have to loop through the array when checking for a key...
First off, I am new to Julia (I have been using/learning it since only two weeks). So do not put any confidence in what I am going to say unless it is validated by others.
The dictionary data structure Dict is defined here
julia/base/dict.jl
There is also a data structure called ImmutableDict in that file. However as const variables aren't actually const why would immutable dictionaries be immutable?
The comment states:
ImmutableDict is a Dictionary implemented as an immutable linked list,
which is optimal for small dictionaries that are constructed over many individual insertions
Note that it is not possible to remove a value, although it can be partially overridden and hidden
by inserting a new value with the same key
So let us call what you want to define as a dictionary UnmodifiableDict to avoid confusion. Such object would probably have
a similar data structure as Dict.
a constructor that takes a Dict as input to fill its data structure.
specialization (a new dispatch?) of the the method setindex! that is called by the operator [] =
in order to forbid modification of the data structure. This should be the case of all other functions that end with ! and hence modify the data.
As far as I understood, It is only possible to have subtypes of abstract types. Therefore you can't make UnmodifiableDict as a subtype of Dict and only redefine functions such as setindex!
Unfortunately this is a needed restriction for having run-time types and not compile-time types. You can't have such a good performance without a few restrictions.
Bottom line:
The only solution I see is to copy paste the code of the type Dict and its functions, replace Dict by UnmodifiableDict everywhere and modify the functions that end with ! to raise an exception if called.
you may also want to have a look at those threads.
https://groups.google.com/forum/#!topic/julia-users/n-lqjybIO_w
https://github.com/JuliaLang/julia/issues/1974
REVISION
Thanks to Chris Rackauckas for pointing out the error in my earlier response. I'll leave it below as an illustration of what doesn't work. But, Chris is right, the const declaration doesn't actually seem to improve performance when you feed the dictionary into the function. Thus, see Chris' answer for the best resolution to this issue:
D1 = [i => sind(i) for i = 0.0:5:3600];
const D2 = [i => sind(i) for i = 0.0:5:3600];
function test(D)
for jdx = 1:1000
# D[2] = 2
for idx = 0.0:5:3600
a = D[idx]
end
end
end
## Times given after an initial run to allow for compiling
#time test(D1); # 0.017789 seconds (4 allocations: 160 bytes)
#time test(D2); # 0.015075 seconds (4 allocations: 160 bytes)
Old Response
If you want your dictionary to be a constant, you can use:
const MyDict = getparameters( .. )
Update Keep in mind though that in base Julia, unlike some other languages, it's not that you cannot redefine constants, instead, it's just that you get a warning when doing so.
julia> const a = 2
2
julia> a = 3
WARNING: redefining constant a
3
julia> a
3
It is odd that you don't get the constant redefinition warning when adding a new key-val pair to the dictionary. But, you still see the performance boost from declaring it as a constant:
D1 = [i => sind(i) for i = 0.0:5:3600];
const D2 = [i => sind(i) for i = 0.0:5:3600];
function test1()
for jdx = 1:1000
for idx = 0.0:5:3600
a = D1[idx]
end
end
end
function test2()
for jdx = 1:1000
for idx = 0.0:5:3600
a = D2[idx]
end
end
end
## Times given after an initial run to allow for compiling
#time test1(); # 0.049204 seconds (1.44 M allocations: 22.003 MB, 5.64% gc time)
#time test2(); # 0.013657 seconds (4 allocations: 160 bytes)
To add to the existing answers, if you like immutability and would like to get performant (but still persistent) operations which change and extend the dictionary, check out FunctionalCollections.jl's PersistentHashMap type.
If you want to maximize performance and take maximal advantage of immutability, and you don't plan on doing any operations on the dictionary whatsoever, consider implementing a perfect hash function-based dictionary. In fact, if your dictionary is a compile-time constant, these can even be computed ahead of time (using metaprogramming) and precompiled.
I'm getting this unhandled exception when I exit my program:
Unhandled exception at 0x102fe274 (msvcr100d.dll) in Parameters.exe: 0xC0000005: Access violation reading location 0x00000005.
The debugger stops in a module called crtdll.c on this line:
onexitbegin_new = (_PVFV *) DecodePointer(__onexitbegin);
The top line on the call stack reads:
msvcr100d.dll!__clean_type_info_names_internal(__type_info_node * p_type_info_root_node=0x04a6506c) Line 359 + 0x3 bytes C++
The program then remains in memory until I close down the IDE.
I'm more used to developing with managed languages so I expect I'm doing something wrong with my code maintenance. The code itself reads a memory mapped file and assoiciates it with pointers:
SUBROUTINE READ_MMF ()
USE IFWIN
USE, INTRINSIC :: iso_c_binding
USE, INTRINSIC :: iso_fortran_env
INTEGER(HANDLE) file_mapping_handle
INTEGER(LPVOID) memory_location
TYPE(C_PTR) memory_location_cptr
INTEGER memory_size
INTEGER (HANDLE) file_map
CHARACTER(5) :: map_name
TYPE(C_PTR) :: cdata
integer :: n = 3
integer(4), POINTER :: A, C
real(8), POINTER :: B
TYPE STRUCT
integer(4) :: A
real(8) :: B
integer(4) :: C
END TYPE STRUCT
TYPE(STRUCT), pointer :: STRUCT_PTR
memory_size = 100000
map_name = 'myMMF'
file_map = CreateFileMapping(INVALID_HANDLE_VALUE,
+ NULL,
+ PAGE_READWRITE,
+ 0,
+ memory_size,
+ map_name // C_NULL_CHAR )
memory_location = MapViewOfFile(file_map,
+IOR(FILE_MAP_WRITE, FILE_MAP_READ),
+ 0, 0, 0 )
cdata = TRANSFER(memory_location, memory_location_cptr)
call c_f_pointer(cdata, STRUCT_PTR, [n])
A => STRUCT_PTR%A
B => STRUCT_PTR%B
C => STRUCT_PTR%C
RETURN
END
Am I supposed to deallocate the c-pointers when I'm finished with them? I looked into that but can't see how I do it in Fortran...
Thanks for any help!
The nature of the access violation (during runtime library cleanup) suggests that your program is corrupting memory in some way. There are a number of programming errors that can lead to that - and the error or errors responsible could be anywhere in your program. The usual "compile and run with all diagnostic and debugging options enabled" approach may help identify these.
That said, there is a programming error in the code example shown. The C_F_POINTER procedure from the ISO_C_BINDING intrinsic module can operate on either scalar or array Fortran pointers (the second argument). If the Fortran pointer is a scalar then the third "shape" argument must not be present (it must be present if the Fortran pointer is an array).
Your code breaks this requirement - the Fortran pointer STRUCT_PTR in your code is a scalar, but yet you provide the third shape argument (as [n]). It is quite plausible that this error will result in memory corruption - typically the implementation of C_F_POINTER would try and populate a descriptor in memory for the Fortran pointer, and the descriptor for a pointer to an array may be very different from a pointer to a scalar.
Subsequent references to STRUCT_PTR may further the corruption.
While it is not required by the standard to diagnose this situation, I am a little surprised that the compiler does not issue a diagnostic (assuming you example code is what you actually are compiling). If you reported this to your compiler's vendor (Intel, presumably given IFWIN etc) I suspect they would regard it as a deficiency in their compiler.
To release the memory associated with the file mapping you use the UnmapViewOfFile and CloseHandle API's. To use these you should "store" (your program needs to remember in some way) the base address (memory_location, which can also be obtained by calling C_LOC on STRUCT_PTR once the problem above is fixed) returned by MapViewOfFile, and the handle to the mapping (file_map) returned by CreateFileMapping; respectively.
I've only ever done this with Cray Pointers: not with the ISO bindings and I know it does work with Cray Pointers.
What you don't say is whether this is happening the first time or second time the routine is being called. If it is called more than once, then there is a problem in the coding in that Create/OpenFileMapping should only be called once to get a handle.
You don't need to deallocate memory because the memory is not yours to deallocate: you need to call UnmapViewOfFile(memory_location). After you have called this, memory_location, memory_location_cptr and possibly cdata are no longer valid.
The way this works is with two or more programs:
One program calls CreateFileMapping, the others calls OpenFileMapping to obtain a handle to the data. This only needs to be called once at the start of the program: not every time you need to access the file. Multiple calls to Create/OpenFileMapping without a corresponding close can cause crashes.
They then call MapViewOfFile to map the file into memory. Note that only one program can do this at a time. When the program is finished with the memory file, it calls UnmapViewOfFile. The other program can now get to the file. There is a blocking mechanism. If you do not call UnmapViewOfFile, other programs using MapViewOfFile will be blocked.
When all is done, call close on the handle created by Create/OpenFileMapping.
Given below is some code in ada
with TYPE_VECT_B; use TYPE_VECT_B;
Package TEST01 is
procedure TEST01
( In_State : IN VECT_B ;
Out_State : IN OUT VECT_B );
function TEST02
( In_State : IN VECT_B ) return Boolean ;
end TEST01;
The TYPE_VECT_B package specification and body is also defined below
Package TYPE_VECT_B is
type VECT_B is array (INTEGER range <>) OF BOOLEAN ;
rounded_data : float ;
count : integer ;
trace : integer ;
end TYPE_VECT_B;
Package BODY TYPE_VECT_B is
begin
null;
end TYPE_VECT_B;
What does the variable In_State and Out_State actually mean? I think In_State means input variable. I just get confused to what actually Out_State means?
An in parameter can be read but not written by the subprogram. in is the default. Prior to Ada 2012, functions were only allowed to have in parameters. The actual parameter is an expression.
An out parameter implies that the previous value is of no interest. The subprogram is expected to write to the parameter. After writing to the parameter, the subprogram can read back what it has written. On exit the actual parameter receives the value written to it (there are complications in this area!). The actual parameter must be a variable.
An in out parameter is like an out parameter except that the previous value is of interest and can be read by the subprogram before assignment. For example,
procedure Add (V : Integer; To : in out Integer; Limited_To : Integer)
is
begin
-- Check that the result wont be too large. This involves reading
-- the initial value of the 'in out' parameter To, which would be
-- wrong if To was a mere 'out' parameter (it would be
-- uninitialized).
if To + V > Limited_To then
To := Limited_To;
else
To := To + V;
end if;
end Add;
Basically, every parameter to a function or procedure has a direction to it. The options are in, out, in out (both), or access. If you don't see one of those, then it defaults to in.
in means data can go into the subroutine from the caller (via the parameter). You are allowed to read from in parameters inside the routine. out means data can come out of the routine that way, and thus you are allowed to assign values to the parameter inside the routine. In general, how the compiler accomplishes the data passing is up to the compiler, which is in accord with Ada's general philosophy of allowing you to specify what you want done, not how you want it done.
access is a special case, and is roughly like putting a "*" in your parameter definition in Cish languages.
The next question folks usually have is "if I pass something large as an in parameter, is it going to push all that data on the stack or something?" The answer is "no", unless your compiler writers are unconsionably stupid. Every Ada compiler I know of under the hood passes objects larger than fit in a machine register by reference. It is the compiler, not the details of your parameter passing mechanisim, that enforces not writing data back out of the routine. Again, you tell Ada what you want done, it figures out the most efficient way to do it.