ID=227

• Dataset: 6n4o
• Software: OPENMM.cuda (openmm/7.7.0-gofbc-2020.1.403.114-avx512)
• Resource: 1 tasks, 2 cores, nodes, 2 GPUs, with NVLink
• CPU: Xeon Gold 6148 (Skylake), 2.4 GHz
• GPU: Tesla-V100-SXM2-16GB, 10 cores/GPU
• Simulation speed: 32.93531573407496 ns/day
• Efficiency: 65.9 %
• Site: Beluga
• Date: Aug. 30, 2023, 9:03 p.m.
• Submission script:

  #!/bin/bash
  #SBATCH -c2 --gpus-per-node=v100:2
  #SBATCH --mem-per-cpu=4000 --time=1:0:0
  
  module purge
  ml StdEnv/2020  gcc/9.3.0  cuda/11.4  openmpi/4.0.3 python/3.8.10
  ml openmm/7.7.0 netcdf/4.7.4 hdf5/1.10.6 mpi4py/3.0.3
  
  virtualenv ${SLURM_TMPDIR}/env
  source ${SLURM_TMPDIR}/env/bin/activate
  pip install --no-index netCDF4 parmed
  
  python openmm_input.py

• Notes:

  Benchmark time: 32.12375733784062 ns/day, Using 2 GPUs, bg11802
  Benchmark time: 32.15613303547002 ns/day, Using 2 GPUs, bg12410
  Benchmark time: 32.23951869227949 ns/day, Using 2 GPUs, bg12410
  Benchmark time: 32.31724742432879 ns/day, Using 2 GPUs, bg12301
  Benchmark time: 32.51384980939154 ns/day, Using 2 GPUs, bg11606
  Benchmark time: 32.584039567260945 ns/day, Using 2 GPUs, bg11801
  Benchmark time: 32.62073416284589 ns/day, Using 2 GPUs, bg11807
  Benchmark time: 32.93531573407496 ns/day, Using 2 GPUs, bg12308

• Simulation input file:

  #!/cvmfs/soft.computecanada.ca/easybuild/software/2020/avx512/Core/python/3.8.10/bin/python
  
  # FILE openmm_input.py
  
  import openmm as mm
  import openmm.app as app
  from openmm.unit import *
  import sys, time, netCDF4, ctypes
  from parmed import load_file
  from parmed.openmm import StateDataReporter, NetCDFReporter
  
  CUDA_SUCCESS = 0
  cuda = ctypes.CDLL("libcuda.so")
  device = ctypes.c_int()
  nGpus = ctypes.c_int()
  name = b" " * 100
  devID=[]
  
  result = cuda.cuInit(0)
  if result != CUDA_SUCCESS:
      print("CUDA is not available")
      quit()
  cuda.cuDeviceGetCount(ctypes.byref(nGpus))
  for i in range(nGpus.value):
      result = cuda.cuDeviceGet(ctypes.byref(device), i)
      result = cuda.cuDeviceGetName(ctypes.c_char_p(name), len(name), device)
      print("Device %s:  %s"  % (device.value, name.split(b"\0", 1)[0].decode()))
      devID.append(device.value)
  dvi=",".join(str(i) for i in devID)
  
  amber_sys=load_file("prmtop.parm7", "restart.rst7")
  ncrst=app.amberinpcrdfile.AmberInpcrdFile("restart.rst7")
  
  nsteps=100000
  system=amber_sys.createSystem(
              nonbondedMethod=app.PME, 
              ewaldErrorTolerance=0.0004,
              nonbondedCutoff=8.0*angstroms,
              constraints=app.HBonds,
              removeCMMotion = True,
  )
  
  #PME Grids:
  #EwaldTolerance=0.00040  Grid=[144, 144, 144]
  #EwaldTolerance=0.00045  Grid=[140, 140, 140]
  #EwaldTolerance=0.00050  Grid=[135, 135, 135]
  #EwaldTolerance=0.00065  Grid=[128, 128, 128]
  
  integrator = mm.LangevinIntegrator(300*kelvin, 1.0/picoseconds, 1.0*femtoseconds,)
  barostat = mm.MonteCarloBarostat(1.0*atmosphere, 300.0*kelvin, 25)
  system.addForce(barostat)
  
  platform = mm.Platform.getPlatformByName("CUDA")
  prop = dict(CudaPrecision="mixed", DeviceIndex=dvi)
  
  sim = app.Simulation(amber_sys.topology, system, integrator, platform, prop)
  sim.context.setPositions(amber_sys.positions)
  sim.context.setVelocities(ncrst.velocities)
  
  sim.reporters.append(
          StateDataReporter(
              sys.stdout, 
              400, 
              step=True,
              time=False, 
              potentialEnergy=True,
              kineticEnergy=True, 
              temperature=True, 
              volume=True
          )
  )
  
  sim.reporters.append(
          NetCDFReporter(
              "trajectory.nc", 
              50000, 
              crds=True
          )
  )
  
  print("Running dynamics")
  start = time.time()
  sim.step(nsteps)
  elapsed=time.time() - start
  benchmark_time=3.6*2.4*nsteps*0.01/elapsed
  print(f"Elapsed time: {elapsed} sec\nBenchmark time: {benchmark_time} ns/day")