FORTRAN OMP Parallel Taylor Scaling problem

Hi i have trouble with OMPing my DEM code. The problem is that my OMP talyor expansions are not scaling, which is embarrassing because as Taylor only theoretically “embarrassingly parallel” part of the code and things like Collision Detection and force models aren’t a problem with good scaling.

I am using a window 7 computer using PGI visual studio 13.5 with 2 Intel® Xeon® CPU E5-2687W 0 @ 3.10GHz, with the environmental OMP_NUM_THREADS 16

first if this program is run in visual studio in either release or the debugger it crashes on 11 (I think its reached 12 but beside the piont). If running it with with out visual studio we can get results

Now the problem is compound with different compiler options
With the standard release

-Bstatic -Mbackslash -mp -I"c:\program files\pgi\win64\13.5\include" -I"C:\Program Files\PGI\Microsoft Open Tools 11\include" -I"C:\Program Files (x86)\Windows Kits\8.0\Include\shared" -I"C:\Program Files (x86)\Windows Kits\8.0\Include\um" -fastsse -Minform=warn

WITHOUT OMP 0.007539
OMP using 1 Threads, took 0.049737 15.158576 % compared to not omp
OMP using 2 Threads, took 0.011979 62.938803 % compared to not omp
OMP using 3 Threads, took 0.011377 66.266989 % compared to not omp
OMP using 4 Threads, took 0.010057 74.965431 % compared to not omp
OMP using 5 Threads, took 0.009997 75.414831 % compared to not omp
OMP using 6 Threads, took 0.009970 75.617694 % compared to not omp
OMP using 7 Threads, took 0.019982 37.730534 % compared to not omp
OMP using 8 Threads, took 0.010585 71.229706 % compared to not omp
OMP using 9 Threads, took 0.010700 70.460453 % compared to not omp
OMP using 10 Threads, took 0.009990 75.472323 % compared to not omp
OMP using 11 Threads, took 0.019917 37.854732 % compared to not omp
OMP using 12 Threads, took 0.019918 37.852215 % compared to not omp
OMP using 13 Threads, took 0.019913 37.861656 % compared to not omp
OMP using 14 Threads, took 0.017349 43.457516 % compared to not omp
OMP using 15 Threads, took 0.019815 38.048927 % compared to not omp
OMP using 16 Threads, took 0.010039 75.101422 % compared to not omp

Then with the optimization turned off

-Bstatic -Mbackslash -mp -I"c:\program files\pgi\win64\13.5\include" -I"C:\Program Files\PGI\Microsoft Open Tools 11\include" -I"C:\Program Files (x86)\Windows Kits\8.0\Include\shared" -I"C:\Program Files (x86)\Windows Kits\8.0\Include\um" -Minform=warn
gives

WITHOUT OMP 0.032620
OMP using 1 Threads, took 0.027060 120.548683 % compared to not omp
OMP using 2 Threads, took 0.014288 228.299963 % compared to not omp
OMP using 3 Threads, took 0.011752 277.580232 % compared to not omp
OMP using 4 Threads, took 0.010447 312.243669 % compared to not omp
OMP using 5 Threads, took 0.009992 326.449732 % compared to not omp
OMP using 6 Threads, took 0.010884 299.695790 % compared to not omp
OMP using 7 Threads, took 0.009995 326.374027 % compared to not omp
OMP using 8 Threads, took 0.010520 310.062002 % compared to not omp
OMP using 9 Threads, took 0.010348 315.231025 % compared to not omp
OMP using 10 Threads, took 0.009983 326.763740 % compared to not omp
OMP using 11 Threads, took 0.020017 162.962963 % compared to not omp
OMP using 12 Threads, took 0.019957 163.455061 % compared to not omp
OMP using 13 Threads, took 0.019844 164.382373 % compared to not omp
OMP using 14 Threads, took 0.019579 166.606349 % compared to not omp
OMP using 15 Threads, took 0.029464 110.712038 % compared to not omp
OMP using 16 Threads, took 0.023021 141.698670 % compared to not omp

Preferably I would like to have SIMD and OMP because you know in theory 16 cores vectoring 4 loops at a time would be so fast that I would never have to worry about the Taylor expansion again. Can some one explain where i am going wrong? The code is bellow it might look weird but that’s because its part of a much larger code.

Thanks for any help in advance!
Marc

!
!  ConsoleApp.f90
!
!  Fortran Console Application 
!  Generated by PGI Visual Fortran(R)
!  5/16/2013 5:39:09 PM
!

      program prog
!$ use omp_lib !omp values

      implicit none

      ! Variables
	  
	
	 INTEGER :: i, np, threads
	 REAL*8 :: Acc_tmp, Accel_diff_tmp 

	 REAL*8, DIMENSION(3,2000000), TARGET:: xyz, fxyz,Accxyz, vXYZ
	 REAL*8, DIMENSION(2000000) :: Paricle_live, m, mInvert

	 REAL*8, POINTER:: y(:), fy(:),Accy(:), vY(:)
	 REAL*8, SAVE  :: dt, dt_half, dt_Squared, dt_Squared_half, dt_Squared_Sixth
	 REAL*8 :: FreeFlightTotal, FreeFlightS, FreeFlightE, FreeFlightTotal_compare
	 !$OMP THREADPRIVATE(dt, dt_half, dt_Squared,dt_Squared_half, dt_Squared_Sixth)
	

      ! Body
	 
	 
	 dt = 0.001D0
	 dt_half = dt * 0.5D0 
	 dt_Squared = dt * dt
	 dt_Squared_half = dt*dt*0.5D0
	 dt_Squared_Sixth = (dt*dt) / 6.0D0

	
	 
	 fY => fXYZ(2,1:2000000)
	 Y => XYZ(2,1:2000000)
	 vY => vXYZ(2,1:2000000)
	 accY => accXYZ(2,1:2000000)
	
	 fY = 10.d0
	 Y = 200000.D0
	 Y = 100.D0
     accY = 10.D0

	 m = 1.D0
	 mInvert = 1.D0/ m
	 
	 np = 2000000
	 Paricle_live = 1.D0
	 Paricle_live(300:500) = 0.D0

	 threads = 0

	 CALL CPU_TIME (FreeFlightS) 
     !$ FreeFlightS = OMP_get_wtime()

     DO i=1, np
	 	!   
		Acc_tmp = fy(i)*Paricle_live(i) !F = MA  !F/M = A
		Acc_tmp = Acc_tmp* mInvert(i) !F = MA  !F/M = A
        Accel_diff_tmp = Acc_tmp  - Accy(i)
		Accy(i) = Acc_tmp
		y(i) = y(i) + (vy(i) * dt) + (Acc_tmp* dt_Squared_half) + (Accel_diff_tmp * dt_Squared_Sixth)
        vy(i) = vy(i) + (Acc_tmp * dt) + (Accel_diff_tmp * dt_half) 
	 END DO 

	 CALL CPU_TIME (FreeFlightE) 
     !$ FreeFlightE = OMP_get_wtime()

	 
	 FreeFlightTotal =  FreeFlightE - FreeFlightS
	!
	 WRITE(6,'(a,f12.6)') "WITHOUT OMP", FreeFlightTotal

	 FreeFlightTotal_compare = FreeFlightTotal




	 !$ DO threads = 1, 16 
	 fY = 10.d0
	 Y = 200000.D0
	 Y = 100.D0
     accY = 10.D0
	 
	 !$OMP PARALLEL PRIVATE(i, Acc_tmp,Accel_diff_tmp), num_threads (threads)



	 CALL CPU_TIME (FreeFlightS) 
     !$ FreeFlightS = OMP_get_wtime()
	 !$OMP DO 
     DO i=1, np
	 	!   
		Acc_tmp = fy(i)*Paricle_live(i) !F = MA  !F/M = A
		Acc_tmp = Acc_tmp* mInvert(i) !F = MA  !F/M = A
        Accel_diff_tmp = Acc_tmp  - Accy(i)
		Accy(i) = Acc_tmp
		y(i) = y(i) + (vy(i) * dt) + (Acc_tmp* dt_Squared_half) + (Accel_diff_tmp * dt_Squared_Sixth)
        vy(i) = vy(i) + (Acc_tmp * dt) + (Accel_diff_tmp * dt_half) 
	 END DO 
	 !$OMP END DO
	 CALL CPU_TIME (FreeFlightE) 
     !$ FreeFlightE = OMP_get_wtime()
	 !$OMP END PARALLEL 
	 
	 FreeFlightTotal =  FreeFlightE - FreeFlightS
	!
	 WRITE(6,'(a,i3,a,f12.6,5x,f12.6,a)') "OMP using ", threads,  " Threads, took ", FreeFlightTotal,  ((FreeFlightTotal_compare/FreeFlightTotal)*100.D0), " % compared to not omp"
	 !$ END DO

	 pause 

      end program prog



Hi Marc,

First, the only reason the unoptimized version scales better is because the serial loop slows down more relative to the parallel loop.

Though, the drop off after the 11 thread and why it doesn’t continue to scale after the 4 threads is most likely because you’re on a NUMA based system. NUMA divides the memory across multiple cores so that each core has faster access to it’s memory. However, if the data is not located in memory attached to the core that needs it, that data needs to be fetched through the other core. The law of “first-touch” determines which memory bank the data is placed so it’s important to initialize data in parallel so the core’s data is close.

Next, I see you’re using pointers. In general pointers will give poor performance. But this is true for both serial and parallel versions.

The next problem is that you don’t have enough work in these loops. Hence, the overhead of launching threads impacts your overall performance and limits your scaling.

With these ideas in mind, I rewrote your program, initialize data in parallel, remove pointers, and increase the amount of work performed. While I’m running on Linux, you should see approximately the same scaling on Windows.

% cat scaling2.F90

!
!  ConsoleApp.f90
!
!  Fortran Console Application
!  Generated by PGI Visual Fortran(R)
!  5/16/2013 5:39:09 PM
!

      program prog
!$ use omp_lib !omp values

      implicit none

      ! Variables
    
   
    INTEGER :: i, np, threads, it, iters
    PARAMETER np = 30000000
    REAL*8 :: Acc_tmp, Accel_diff_tmp

    REAL*8, DIMENSION(np) :: Paricle_live, m, mInvert
    REAL*8 :: y(np), fy(np),Accy(np), vY(np)

    REAL*8, SAVE  :: dt, dt_half, dt_Squared, dt_Squared_half, dt_Squared_Sixth
    REAL*8 :: FreeFlightTotal, FreeFlightS, FreeFlightE, FreeFlightTotal_compare
    !$OMP THREADPRIVATE(dt, dt_half, dt_Squared,dt_Squared_half, dt_Squared_Sixth)
   

      ! Body
    iters= 100
    dt = 0.001D0
    dt_half = dt * 0.5D0
    dt_Squared = dt * dt
    dt_Squared_half = dt*dt*0.5D0
    dt_Squared_Sixth = (dt*dt) / 6.0D0
    FreeFlightTotal   = 0.D0

    !$OMP PARALLEL PRIVATE(i,Acc_tmp,Accel_diff_tmp, FreeFlightS, FreeFlightE)
#ifdef _OPENMP
       threads =  omp_get_num_threads()
#else 
	threads = 1
#endif

    !$OMP DO 
    DO i=1,np 
       	fY(i) = 10.d0	
   	 Y(i) = i
    	 vY(i) = 100.D0	
    	 accY(i) = 10.D0
    	 m(i) = 1.D0
    	 mInvert(i) = 1.D0/ m(i)
	 Paricle_live(i) = 1.D0
    enddo
    !$OMP END DO

    Paricle_live(300:500) = 0.D0

#ifdef _OPENMP
       FreeFlightS = OMP_get_wtime()	
#else
    CALL CPU_TIME (FreeFlightS)
#endif

    !$OMP DO
     DO i=1, np
    DO it=1,iters	
       !   
      Acc_tmp = fy(i)*Paricle_live(i) !F = MA  !F/M = A
      Acc_tmp = Acc_tmp* mInvert(i) !F = MA  !F/M = A
      Accel_diff_tmp = Acc_tmp  - Accy(i)
      Accy(i) = Acc_tmp
      y(i) = y(i) + (vy(i) * dt) + (Acc_tmp* dt_Squared_half) + (Accel_diff_tmp * dt_Squared_Sixth)
        vy(i) = vy(i) + (Acc_tmp * dt) + (Accel_diff_tmp * dt_half)
    END DO
    END DO
    !$OMP END DO
#ifdef _OPENMP
       FreeFlightE = OMP_get_wtime()	
#else
    CALL CPU_TIME (FreeFlightE)
#endif

!$OMP CRITICAL
    FreeFlightTotal =  FreeFlightTotal + FreeFlightE - FreeFlightS
!$OMP END CRITICAL

    !$OMP END PARALLEL
   
    FreeFlightTotal =  FreeFlightTotal / threads
   !
   #ifdef _OPENMP	
    WRITE(6,'(a,i3,a,f12.6)') "OMP using ", threads,  " Threads, took ", FreeFlightTotal
   #else
    WRITE(6,'(a,f12.6)') "SERIAL took ", FreeFlightTotal
   #endif
    ! END DO
    
    !pause

      end program prog 

% pgf90 -fast -Mfprelaxed scaling2.F90 -o scale2.out 
% pgf90 -fast -Mfprelaxed scaling2.F90 -o scale2mp.out -mp
% scale2.out 
SERIAL took     6.120110
% env OMP_NUM_THREADS=1 scale2mp.out
OMP using   1 Threads, took     6.140261
% env OMP_NUM_THREADS=2 scale2mp.out
OMP using   2 Threads, took     3.150713
% env OMP_NUM_THREADS=4 scale2mp.out
OMP using   4 Threads, took     1.874532
% env OMP_NUM_THREADS=8 scale2mp.out
OMP using   8 Threads, took     0.901755
% env OMP_NUM_THREADS=16 scale2mp.out
OMP using  16 Threads, took     0.846744
  • Mat

Hi mat

Didn’t know about the first touch principal. How can I make sure that threads stay locked to a set task on a set core? Also is there away to reset this first touch?

Also how comes that this is not enough work when the much simpler gravity routine which does scale perfectly? (when inserted on a single loop example as I used above)

 !$OMP DO
DO i = 1, 2000000 
 y(i) = m(i)*gravity 
END DO
 !$OMP END DO

Regards,
Marc

How can I make sure that threads stay locked to a set task on a set core?

Either by setting the PGI environment variable “MP_BIND=yes” or using a system utility. For MP_BIND, the default is to assign the threads to cores in order 0,1,2,3,etc. To change the order, you can use the variable “MP_BLIST=2,4,6,etc”.

The Windows method to set affinity is via the "start /AFFINITY ". Note that the bind list is a hexadecimal mask, so “F” would would be cores 0-3.

Also how comes that this is not enough work when the much simpler gravity routine which does scale perfectly?

Hmm. Maybe it’s my system or my coding, but I don’t see any scaling with this little loop.

  • Mat