我建议你不要重新发明轮子,而是使用
cublas fortran bindings
这是为此目的而提供的。
“砰砰”的包装不是你想要的。在fortran中使用cublas调用时,它会根据需要执行隐式复制操作。
您需要“非thunking”包装器,因此您可以显式控制正在进行的复制
Get/SetMatrix
和
Get/SetVector
来回复制数据。
有一个示例代码(示例B.2)显示了如何使用cublas文档中包含的非敲击包装器。
即使您确实想重新发明轮子,包装器也会向您展示如何使必要的语法在C和Fortran之间移动。
在标准的linux CUDA安装中,包装器位于
/usr/local/cuda/src
非敲击包装是
/usr/local/cuda/src/fortran.c
下面是一个充分发挥作用的示例:
立方英尺:
program cublas_fortran_example
implicit none
integer i, j
c helper functions
integer cublas_init
integer cublas_shutdown
integer cublas_alloc
integer cublas_free
integer cublas_set_vector
integer cublas_get_vector
c selected blas functions
double precision cublas_ddot
external cublas_daxpy
external cublas_dscal
external cublas_dcopy
double precision cublas_dnrm2
c cublas variables
integer cublas_status
real*8 x(30), y(30)
double precision alpha, beta
double precision nrm
integer*8 d_x, d_y, d_alpha, d_beta, d_nrm
integer*8 dsize1, dlength1, dlength2
double precision dresult
write(*,*) "testing cublas fortran example"
c initialize cublas library
c CUBLAS_STATUS_SUCCESS=0
cublas_status = cublas_init()
if (cublas_status /= 0) then
write(*,*) "CUBLAS Library initialization failed"
write(*,*) "cublas_status=",cublas_status
stop
endif
c initialize data
do j=1,30
x(j) = 1.0
y(j) = 2.0
enddo
dsize1 = 8
dlength1 = 30
dlength2 = 1
alpha = 2.0
beta = 3.0
c allocate device storage
cublas_status = cublas_alloc(dlength1, dsize1, d_x)
if (cublas_status /= 0) then
write(*,*) "CUBLAS device malloc failed"
stop
endif
cublas_status = cublas_alloc(dlength1, dsize1, d_y)
if (cublas_status /= 0) then
write(*,*) "CUBLAS device malloc failed"
stop
endif
cublas_status = cublas_alloc(dlength2, dsize1, d_alpha)
if (cublas_status /= 0) then
write(*,*) "CUBLAS device malloc failed"
stop
endif
cublas_status = cublas_alloc(dlength2, dsize1, d_beta)
if (cublas_status /= 0) then
write(*,*) "CUBLAS device malloc failed"
stop
endif
cublas_status = cublas_alloc(dlength2, dsize1, d_nrm)
if (cublas_status /= 0) then
write(*,*) "CUBLAS device malloc failed"
stop
endif
c copy data from host to device
cublas_status = cublas_set_vector(dlength1, dsize1, x, dlength2,
> d_x, dlength2)
if (cublas_status /= 0) then
write(*,*) "CUBLAS copy to device failed"
write(*,*) "cublas_status=",cublas_status
stop
endif
cublas_status = cublas_set_vector(dlength1, dsize1, y, dlength2,
> d_y, dlength2)
if (cublas_status /= 0) then
write(*,*) "CUBLAS copy to device failed"
write(*,*) "cublas_status=",cublas_status
stop
endif
dresult = cublas_ddot(dlength1, d_x, dlength2, d_y, dlength2)
write(*,*) "dot product result=",dresult
dresult = cublas_dnrm2(dlength1, d_x, dlength2)
write(*,*) "nrm2 of x result=",dresult
dresult = cublas_dnrm2(dlength1, d_y, dlength2)
write(*,*) "nrm2 of y result=",dresult
call cublas_daxpy(dlength1, alpha, d_x, dlength2, d_y, dlength2)
cublas_status = cublas_get_vector(dlength1, dsize1, d_y, dlength2,
> y, dlength2)
if (cublas_status /= 0) then
write(*,*) "CUBLAS copy to host failed"
write(*,*) "cublas_status=",cublas_status
stop
endif
write(*,*) "daxpy y(1) =", y(1)
write(*,*) "daxpy y(30) =", y(30)
call cublas_dscal(dlength1, beta, d_x, dlength2)
cublas_status = cublas_get_vector(dlength1, dsize1, d_x, dlength2,
> x, dlength2)
if (cublas_status /= 0) then
write(*,*) "CUBLAS copy to host failed"
write(*,*) "cublas_status=",cublas_status
stop
endif
write(*,*) "dscal x(1) =", x(1)
write(*,*) "dscal x(30) =", x(30)
call cublas_dcopy(dlength1, d_x, dlength2, d_y, dlength2)
cublas_status = cublas_get_vector(dlength1, dsize1, d_y, dlength2,
> y, dlength2)
if (cublas_status /= 0) then
write(*,*) "CUBLAS copy to host failed"
write(*,*) "cublas_status=",cublas_status
stop
endif
write(*,*) "dcopy y(1) =", y(1)
write(*,*) "dcopy y(30) =", y(30)
c deallocate GPU memory and exit
cublas_status = cublas_free(d_x)
cublas_status = cublas_free(d_y)
cublas_status = cublas_free(d_alpha)
cublas_status = cublas_free(d_beta)
cublas_status = cublas_free(d_nrm)
cublas_status = cublas_shutdown()
stop
end
编译/运行:
$ gfortran -c -o cublasf.o cublasf.f
$ gcc -c -DCUBLAS_GFORTRAN -I/usr/local/cuda/include -I/usr/local/cuda/src -o fortran.o /usr/local/cuda/src/fortran.c
$ gfortran -L/usr/local/cuda/lib64 -lcublas -o cublasf cublasf.o fortran.o
$ ./cublasf
testing cublas fortran example
dot product result= 60.0000000000000
nrm2 of x result= 5.47722557505166
nrm2 of y result= 10.9544511501033
daxpy y(1) = 4.00000000000000
daxpy y(30) = 4.00000000000000
dscal x(1) = 3.00000000000000
dscal x(30) = 3.00000000000000
dcopy y(1) = 3.00000000000000
dcopy y(30) = 3.00000000000000
$
CUDA 5.0,RHEL 5.5
