Fortran 将共阵列子阵列传递给函数会导致阵列的错误部分
我试图理解如何将多维共数组的一部分传递给函数。我想使用如下函数:Fortran 将共阵列子阵列传递给函数会导致阵列的错误部分,fortran,parameter-passing,intel-fortran,fortran-coarrays,Fortran,Parameter Passing,Intel Fortran,Fortran Coarrays,我试图理解如何将多维共数组的一部分传递给函数。我想使用如下函数: function get_int_vec(vec_int_2get, rank) result(ret_val) implicit none integer, dimension(:), codimension[*], intent(in) :: vec_int_2get integer, intent(in) :: rank integer, allocatable, d
function get_int_vec(vec_int_2get, rank) result(ret_val)
implicit none
integer, dimension(:), codimension[*], intent(in) :: vec_int_2get
integer, intent(in) :: rank
integer, allocatable, dimension(:) :: ret_val
ret_val = vec_int_2get(:)[rank]
end function ! get_int_vec
它可以很好地获得整个阵列。
但是当经过一片丛林时,比如:
vec_getA(:) = get_int_vec(matrix_A(n, :), rank)
其中矩阵A
声明为
integer, dimension(:, :), codimension[:], allocatable :: matrix_A
如果分配得当,我总是得到矩阵A的第一列,而不是第n列
他们说:
“使用-fcoarray=lib
[…]属于不可分配的coarray伪参数的令牌和偏移量作为隐藏参数沿着字符长度隐藏参数传递。令牌是标识coarray的不透明指针,偏移量是一种传递值整数C\u PTRDIFF\u T
,表示coarr基址之间的字节偏移量ay和传递的标量或传递数组的第一个元素。“
因此,我希望函数也能很好地处理矩阵切片,因为从矩阵开始的偏移量应该传递给函数
我做错什么了
如果可能会引起一些兴趣:我使用的是英特尔并行工作室XE 2018群集版,而不是OpenCoArray版本的CoArray。这似乎是英特尔ifort 2018中的一个bug。代码的语法似乎符合Fortran 2008标准()。使用OpenCoArray和GFortran编译的相同代码产生了预期的结果。以下是对您的问题的一个(不是很小,但)有效实施:
module coarrayFunc
implicit none
contains
function get_int_vec(vec_int_2get, rank) result(ret_val)
implicit none
integer, dimension(:), codimension[*], intent(in) :: vec_int_2get
integer, intent(in) :: rank
integer :: ret_val(3)
!integer :: ret_val(size(vec_int_2get)) ! using this results in internal compiler error when compiled with ifort.
!integer, allocatable :: ret_val(:) ! both ifort and OpenCoarrays (GFortran) compile with this declaration, however both ifort give wrong results.
ret_val = vec_int_2get(:)[rank]
end function ! get_int_vec
end module coarrayFunc
program testNoncontiguousCoarray
use coarrayFunc
implicit none
integer, allocatable :: matrix_A(:,:)[:], dummy(:)
integer :: rank, n, i, j, image
integer, parameter :: ilower = 1, iupper = 5
integer, parameter :: jlower = 1, jupper = 3
allocate( matrix_A(ilower:iupper,jlower:jupper)[*] )
do i = ilower, iupper
do j = jlower, jupper
matrix_A(i,j) = this_image()*100 + i*10 + j
end do
end do
! print matrix_A on each image
sync all
if (this_image()==1) then
do image = 1, num_images()
write(*,"(*(g0))") "matrix_A on image ", image, ":"
do i = ilower, iupper
write(*,"(*(g8.1))") matrix_A(i,:)[image]
end do
write(*,"(*(g0))")
end do
sync images(*)
else
sync images(1)
end if
sync all
n = iupper
rank = this_image()
!rank = num_images()
sync all
if (this_image()==1) then
write(*,"(*(g0))")
write(*,"(*(g0))") "On all images: "
write(*,"(*(g0))") "n = ", n
write(*,"(*(g0))")
end if
sync all
if (this_image()==1) then
write(*,"(*(g0,' '))") "On Image ", this_image(), ": matrix_A( n =", n, ", : )[",rank,"] = ", matrix_A(n,:)[rank]
dummy = get_int_vec(matrix_A(n,:), rank)
write(*,"(*(g0,' '))") "On Image ", this_image(), ": get_int_vec( matrix_A( n =", n, ", : ), rank =", rank, ") = " &
, dummy
else
sync images (this_image()-1)
write(*,"(*(g0,' '))") "On Image ", this_image(), ": matrix_A( n =", n, ", : )[",rank,"] = ", matrix_A(n,:)[rank]
dummy = get_int_vec(matrix_A(n,:), rank)
write(*,"(*(g0,' '))") "On Image ", this_image(), ": get_int_vec( matrix_A( n =", n, ", : ), rank =", rank, ") = " &
, dummy
end if
call sleep(1)
if (this_image()<num_images()) sync images (this_image()+1)
end program testNoncontiguousCoarray
输出一个人期望得到的结果。请注意,我已经调整了原始函数,使该函数的结果是一个自动数组,而不是可分配的(这似乎是OpenCoArray中的另一个bug,即可分配的输出返回错误的结果)。使用ifort 2018 Windows运行相同的代码会重现您在自己的实现中观察到的错误:
>set FOR_COARRAY_NUM_IMAGES=4
>ifort /Qcoarray=shared testNoncontiguousCoarray.f90 -o run.exe
Intel(R) Visual Fortran Intel(R) 64 Compiler for applications running on Intel(R) 64, Version 18.0.2.185 Build 20180210
Copyright (C) 1985-2018 Intel Corporation. All rights reserved.
Microsoft (R) Incremental Linker Version 14.13.26129.0
Copyright (C) Microsoft Corporation. All rights reserved.
-out:run.exe
-subsystem:console
testNoncontiguousCoarray.obj
>run.exe
matrix_A on image 1:
111 112 113
121 122 123
131 132 133
141 142 143
151 152 153
matrix_A on image 2:
211 212 213
221 222 223
231 232 233
241 242 243
251 252 253
matrix_A on image 3:
311 312 313
321 322 323
331 332 333
341 342 343
351 352 353
matrix_A on image 4:
411 412 413
421 422 423
431 432 433
441 442 443
451 452 453
On all images:
n = 5
On Image 1 : matrix_A( n = 5 , : )[ 1 ] = 151 152 153
On Image 1 : get_int_vec( matrix_A( n = 5 , : ), rank = 1 ) = 111 112 113
On Image 2 : matrix_A( n = 5 , : )[ 2 ] = 251 252 253
On Image 2 : get_int_vec( matrix_A( n = 5 , : ), rank = 2 ) = 211 212 213
On Image 3 : matrix_A( n = 5 , : )[ 3 ] = 351 352 353
On Image 3 : get_int_vec( matrix_A( n = 5 , : ), rank = 3 ) = 311 312 313
On Image 4 : matrix_A( n = 5 , : )[ 4 ] = 451 452 453
On Image 4 : get_int_vec( matrix_A( n = 5 , : ), rank = 4 ) = 411 412 413
如在你的问题的评论中所提到的,考虑编写一个代码的最小工作示例,该代码复制你所得到的错误,并提交一张到英特尔iFuver编译器团队的票,以获得一个潜在的解决方案。您使用不相关的标记或没有人订阅的标记。标记在堆栈溢出中非常重要。所有Fortran问题都使用tag。对不起,请使用tag。我使用的是英特尔版本的CoArray,而不是OpenCoArray,正如我所说的,我使用的是英特尔编译器。好了,我现在可以看到混淆的原因了。这些约定不是Fortran标准约定,它们是特定于gfortran编译器的约定,当您停留在标准Fortran中时,它们实际上不应该太重要。您完全正确,我删掉了这一部分。谢谢你的评论,但我现在想知道引用是否相关,因为,正如你所说,这是一个特定于编译器的约定,我甚至没有使用这个编译器。我认为它不是真正相关的。与此相关的是Fortran标准文档。
>set FOR_COARRAY_NUM_IMAGES=4
>ifort /Qcoarray=shared testNoncontiguousCoarray.f90 -o run.exe
Intel(R) Visual Fortran Intel(R) 64 Compiler for applications running on Intel(R) 64, Version 18.0.2.185 Build 20180210
Copyright (C) 1985-2018 Intel Corporation. All rights reserved.
Microsoft (R) Incremental Linker Version 14.13.26129.0
Copyright (C) Microsoft Corporation. All rights reserved.
-out:run.exe
-subsystem:console
testNoncontiguousCoarray.obj
>run.exe
matrix_A on image 1:
111 112 113
121 122 123
131 132 133
141 142 143
151 152 153
matrix_A on image 2:
211 212 213
221 222 223
231 232 233
241 242 243
251 252 253
matrix_A on image 3:
311 312 313
321 322 323
331 332 333
341 342 343
351 352 353
matrix_A on image 4:
411 412 413
421 422 423
431 432 433
441 442 443
451 452 453
On all images:
n = 5
On Image 1 : matrix_A( n = 5 , : )[ 1 ] = 151 152 153
On Image 1 : get_int_vec( matrix_A( n = 5 , : ), rank = 1 ) = 111 112 113
On Image 2 : matrix_A( n = 5 , : )[ 2 ] = 251 252 253
On Image 2 : get_int_vec( matrix_A( n = 5 , : ), rank = 2 ) = 211 212 213
On Image 3 : matrix_A( n = 5 , : )[ 3 ] = 351 352 353
On Image 3 : get_int_vec( matrix_A( n = 5 , : ), rank = 3 ) = 311 312 313
On Image 4 : matrix_A( n = 5 , : )[ 4 ] = 451 452 453
On Image 4 : get_int_vec( matrix_A( n = 5 , : ), rank = 4 ) = 411 412 413