Hi All,
I run into this problem with the Fortran-CUDA interface. Basically, in the pme_force.F90, I called a function in the cuda/gpu.cpp as shown below. The calculations inside the gpu function run fine, but it seems the potential energies got changed *strangely* in the first place when they are passed for calling the function:
pme_force.F90:
write(*,'(a,2f22.12)') "Debug-p1) (pot_ene%total, pot_ene%dihedral) = ", &
pot_ene%total, pot_ene%dihedral
call gpu_calculate_and_apply_gamd_weights(pot_ene%total, pot_ene%dihedral, &
pot_ene%gamd_boost,num_gamd_lag)
...
cuda/gpu.cpp:
extern "C" void gpu_calculate_and_apply_gamd_weights_(double* pot_ene_tot, double* dih_ene_tot,
double* gamd_ene_tot,
double* num_gamd_lag)
{
PRINTMETHOD("gpu_calculate_and_apply_gamd_weights");
double tboost = 0.0;
double fwgtd = 1.0;
double fwgt = 1.0;
double tboostall = 0.0;
double temp0 = gpu->sim.gamd_temp0;
double ONE_KB = 1.0 / (temp0 * KB);
printf("Debug-GPU-p0) (pot_ene_tot, dih_ene_tot) = (%12.5f, %12.5f)\n", *pot_ene_tot, *dih_ene_tot);
...
Output:
Debug-p1) (pot_ene%total, pot_ene%dihedral) = -5991.862400868107 9.501277353615
Debug-GPU-p0) (pot_ene_tot, dih_ene_tot) = ( -5988.16828, 9.89661)
=========
As you can see, the energy values before and after they are passed are different. And this problem appeared to depend on the simulation length. The energy differences are negligible when I test the code with several thousand steps, but get larger with hundreds of thousand steps or more like the above. Has anyone come across similar issues before? My workstation has a new NVIDIA Quadro P5000 GPU card. Could this be related to the hardware? If not, how may I fix it?
Any suggestions will be much appreciated,
Yinglong
Yinglong Miao, Ph.D.
Assistant Professor
Center for Computational Biology and
Department of Molecular Biosciences
University of Kansas
http://miao.compbio.ku.edu
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Received on Fri Nov 03 2017 - 08:00:03 PDT
