Runge-Kutta 4 With CUDA Fortran - cuda

Question

I am trying to convert this FORTRAN program (motion of pendulum) to CUDA FORTRAN but I can use only 1 block with two threads. Is there any way to use more then 2 threads....
MODULE CB
REAL :: Q,B,W
END MODULE CB
PROGRAM PENDULUM
USE CB
IMPLICIT NONE
INTEGER, PARAMETER :: N=10,L=100,M=1
INTEGER :: I,count_rate,count_max,count(2)
REAL :: PI,H,T,Y1,Y2,G1,G1F,G2,G2F
REAL :: DK11,DK21,DK12,DK22,DK13,DK23,DK14,DK24
REAL, DIMENSION (2,N) :: Y
PI = 4.0*ATAN(1.0)
H = 3.0*PI/L
Q = 0.5
B = 0.9
W = 2.0/3.0
Y(1,1) = 0.0
Y(2,1) = 2.0
DO I = 1, N-1
T = H*I
Y1 = Y(1,I)
Y2 = Y(2,I)
DK11 = H*G1F(Y1,Y2,T)
DK21 = H*G2F(Y1,Y2,T)
DK12 = H*G1F((Y1+DK11/2.0),(Y2+DK21/2.0),(T+H/2.0))
DK22 = H*G2F((Y1+DK11/2.0),(Y2+DK21/2.0),(T+H/2.0))
DK13 = H*G1F((Y1+DK12/2.0),(Y2+DK22/2.0),(T+H/2.0))
DK23 = H*G2F((Y1+DK12/2.0),(Y2+DK22/2.0),(T+H/2.0))
DK14 = H*G1F((Y1+DK13),(Y2+DK23),(T+H))
DK24 = H*G2F((Y1+DK13),(Y2+DK23),(T+H))
Y(1,I+1) = Y(1,I)+(DK11+2.0*(DK12+DK13)+DK14)/6.0
Y(2,I+1) = Y(2,I)+(DK21+2.0*(DK22+DK23)+DK24)/6.0
! Bring theta back to the region [-pi,pi]
Y(1,I+1) = Y(1,I+1)-2.0*PI*NINT(Y(1,I+1)/(2.0*PI))
END DO
call system_clock ( count(2), count_rate, count_max )
WRITE (6,"(2F16.8)") (Y(1,I),Y(2,I),I=1,N,M)
END PROGRAM PENDULUM
FUNCTION G1F (Y1,Y2,T) RESULT (G1)
USE CB
IMPLICIT NONE
REAL :: Y1,Y2,T,G1
G1 = Y2
END FUNCTION G1F
FUNCTION G2F (Y1,Y2,T) RESULT (G2)
USE CB
IMPLICIT NONE
REAL :: Y1,Y2,T,G2
G2 = -Q*Y2-SIN(Y1)+B*COS(W*T)
END FUNCTION G2F
CUDA FORTRAN VERSION OF PROGRAM
MODULE KERNEL
CONTAINS
attributes(global) subroutine mykernel(Y_d,N,L,M)
INTEGER,value:: N,L,M
INTEGER ::tid
REAL:: Y_d(:,:)
REAL :: PI,H,T,G1,G1F,G2,G2F
REAL,shared :: DK11,DK21,DK12,DK22,DK13,DK23,DK14,DK24,Y1,Y2
PI = 4.0*ATAN(1.0)
H = 3.0*PI/L
Y_d(1,1) = 0.0
Y_d(2,1) = 2.0
tid=threadidx%x
DO I = 1, N-1
T = H*I
Y1 = Y_d(1,I)
Y2 = Y_d(2,I)
if(tid==1)then
DK11 = H*G1F(Y1,Y2,T)
else
DK21 = H*G2F(Y1,Y2,T)
endif
call syncthreads ()
if(tid==1)then
DK12 = H*G1F((Y1+DK11/2.0),(Y2+DK21/2.0),(T+H/2.0))
else
DK22 = H*G2F((Y1+DK11/2.0),(Y2+DK21/2.0),(T+H/2.0))
endif
call syncthreads ()
if(tid==1)then
DK13 = H*G1F((Y1+DK12/2.0),(Y2+DK22/2.0),(T+H/2.0))
else
DK23 = H*G2F((Y1+DK12/2.0),(Y2+DK22/2.0),(T+H/2.0))
endif
call syncthreads ()
if(tid==1)then
DK14 = H*G1F((Y1+DK13),(Y2+DK23),(T+H))
else
DK24 = H*G2F((Y1+DK13),(Y2+DK23),(T+H))
endif
call syncthreads ()
if(tid==1)then
Y_d(1,I+1) = Y1+(DK11+2.0*(DK12+DK13)+DK14)/6.0
else
Y_d(2,I+1) = Y2+(DK21+2.0*(DK22+DK23)+DK24)/6.0
endif
Y_d(1,I+1) = Y_d(1,I+1)-2.0*PI*NINT(Y_d(1,I+1)/(2.0*PI))
call syncthreads ()
END DO
end subroutine mykernel
attributes(device) FUNCTION G1F (Y1,Y2,T) RESULT (G1)
IMPLICIT NONE
REAL :: Y1,Y2,T,G1
G1 = Y2
END FUNCTION G1F
attributes(device) FUNCTION G2F (Y1,Y2,T) RESULT (G2)
IMPLICIT NONE
REAL :: Y1,Y2,T,G2
G2 = -0.5*Y2-SIN(Y1)+0.9*COS((2.0/3.0)*T)
END FUNCTION G2F
END MODULE KERNEL
PROGRAM PENDULUM
use cudafor
use KERNEL
IMPLICIT NONE
INTEGER, PARAMETER :: N=100000,L=1000,M=1
INTEGER :: I,d,count_max,count_rate
REAL,device :: Y_d(2,N)
REAL, DIMENSION (2,N) :: Y
INTEGER :: count(2)
call mykernel<<<1,2>>>(Y_d,N,L,M)
Y=Y_d
WRITE (6,"(2F16.8)") (Y(1,I),Y(2,I),I=1,N,M)
END PROGRAM PENDULUM

Answer 1

You can see that only two independent threads of execution are possible by doing a data-dependency analysis of your original serial code. It's easiest to think of this as an "outer" and an "inner" part.
The "outer" part is the dependence of Y(1:2,i+1) on Y(1:2,i). At each time step, you need to use the values of Y(1:2,i) to calculate Y(1:2,i+1), so it's not possible to perform the calculations for multiple time steps in parallel, simply because of the serial dependence structure -- you need to know what happens at time i to calculate what happens at time i+1, you need to know what happens at time i+1 to calculate what happens at time i+2, and so on. The best that you can hope to do is to calculate Y(1,i+1) and Y(2,i+1) in parallel, which is exactly what you do.
The "inner" part is based on the dependencies between the intermediate values in the Runge-Kutta scheme, the DK11, DK12, etc. values in your code. When calculating Y(1:2,i+1), each of the DK[n,m] depends on Y(1:2,i) and for m > 1, each of the DK[n,m] depends on both DK[1,m-1] and DK[2,m-1]. If you draw a graph of these dependencies (which my ASCII art skills aren't really good enough for!), you'll see that there are at each step of the calculation only two possible sub-calculations that can be performed in parallel.
The result of all this is that you cannot do better than two parallel threads for this calculation. As one of the commenters above said, you can certainly do much better if you're simulating a particle system or some other mechanical system with multiple independent degrees of freedom, which you can then integrate in parallel.