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nstream-cufortran.F90
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!
! Copyright (c) 2017, Intel Corporation
! Copyright (c) 2021, NVIDIA
!
! Redistribution and use in source and binary forms, with or without
! modification, are permitted provided that the following conditions
! are met:
!
! * Redistributions of source code must retain the above copyright
! notice, this list of conditions and the following disclaimer.
! * Redistributions in binary form must reproduce the above
! copyright notice, this list of conditions and the following
! disclaimer in the documentation and/or other materials provided
! with the distribution.
! * Neither the name of Intel Corporation nor the names of its
! contributors may be used to endorse or promote products
! derived from this software without specific prior written
! permission.
!
! THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
! "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
! LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
! FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
! COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
! INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
! BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
! LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
! CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
! LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
! ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
! POSSIBILITY OF SUCH DAMAGE.
!*******************************************************************
!
! NAME: nstream
!
! PURPOSE: To compute memory bandwidth when adding a vector of a given
! number of double precision values to the scalar multiple of
! another vector of the same length, and storing the result in
! a third vector.
!
! USAGE: The program takes as input the number
! of iterations to loop over the triad vectors, the length of the
! vectors, and the block_size for the GPU.
!
! <progname> <# iterations> <vector length> <block_size>
!
! The output consists of diagnostics to make sure the
! algorithm worked, and of timing statistics.
!
! NOTES: Bandwidth is determined as the number of words read, plus the
! number of words written, times the size of the words, divided
! by the execution time. For a vector length of N, the total
! number of words read and written is 4*N*sizeof(double).
!
!
! HISTORY: This code is loosely based on the Stream benchmark by John
! McCalpin, but does not follow all the Stream rules. Hence,
! reported results should not be associated with Stream in
! external publications
!
! Converted to C++11 by Jeff Hammond, November May 2017.
!
! *******************************************************************
module nstream
use iso_fortran_env
contains
attributes(global) subroutine kernel(n, scalar, A, B, C)
implicit none
integer(kind=INT64), intent(in), value :: n
real(kind=REAL64), intent(in), value :: scalar
real(kind=REAL64), intent(inout) :: A(n)
real(kind=REAL64), intent(in) :: B(n), C(n)
integer :: i
i = blockDim%x * (blockIdx%x - 1) + threadIdx%x
if (i <= n) then
A(i) = A(i) + B(i) + scalar * C(i)
endif
end subroutine kernel
end module nstream
program main
use iso_fortran_env
use cudafor
use nstream
use prk
implicit none
integer :: err
! problem definition
integer(kind=INT32) :: iterations, block_size
integer(kind=INT64) :: length, offset
real(kind=REAL64), allocatable, managed :: A(:)
real(kind=REAL64), allocatable, managed :: B(:)
real(kind=REAL64), allocatable, managed :: C(:)
real(kind=REAL64) :: scalar
integer(kind=INT64) :: bytes
! runtime variables
integer(kind=INT64) :: i
integer(kind=INT32) :: k
real(kind=REAL64) :: asum, ar, br, cr
real(kind=REAL64) :: t0, t1, nstream_time, avgtime
real(kind=REAL64), parameter :: epsilon=1.D-8
! CUDA stuff
type(dim3) :: grid, tblock
! ********************************************************************
! read and test input parameters
! ********************************************************************
write(*,'(a25)') 'Parallel Research Kernels'
write(*,'(a45)') 'CUDA Fortran STREAM triad: A = B + scalar * C'
call prk_get_arguments('nstream',iterations=iterations,length=length,offset=offset,gpu_block_size=block_size)
write(*,'(a23,i12)') 'Number of iterations = ', iterations
write(*,'(a23,i12)') 'Vector length = ', length
write(*,'(a23,i12)') 'Offset = ', offset
write(*,'(a23,i12)') 'GPU block size = ', block_size
tblock = dim3(block_size,1,1)
grid = dim3(ceiling(real(length)/tblock%x),1,1)
! ********************************************************************
! ** Allocate space and perform the computation
! ********************************************************************
allocate( A(length), B(length), C(length), stat=err)
if (err .ne. 0) then
write(*,'(a20,i3)') 'allocation returned ',err
stop 1
endif
do i=1,length
A(i) = 0
B(i) = 2
C(i) = 2
enddo
scalar = 3
t0 = 0
do k=0,iterations
if (k.eq.1) then
t0 = prk_get_wtime()
endif
call kernel<<<grid, tblock>>>(length, scalar, A, B, C)
enddo ! iterations
err = cudaDeviceSynchronize()
t1 = prk_get_wtime()
nstream_time = t1 - t0
! ********************************************************************
! ** Analyze and output results.
! ********************************************************************
ar = 0
br = 2
cr = 2
do k=0,iterations
ar = ar + br + scalar * cr;
enddo
asum = 0
do i=1,length
asum = asum + abs(A(i)-ar)
enddo
deallocate( A,B,C )
if (abs(asum) .gt. epsilon) then
write(*,'(a35)') 'Failed Validation on output array'
write(*,'(a30,f30.15)') ' Expected value: ', ar
write(*,'(a30,f30.15)') ' Observed value: ', A(1)
write(*,'(a35)') 'ERROR: solution did not validate'
stop 1
else
write(*,'(a17)') 'Solution validates'
avgtime = nstream_time/iterations;
bytes = 4 * int(length,INT64) * storage_size(A)/8
write(*,'(a12,f15.3,1x,a12,e15.6)') &
'Rate (MB/s): ', 1.d-6*bytes/avgtime, &
'Avg time (s): ', avgtime
endif
end program main