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PyCUMD.py
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PyCUMD.py
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'''
Created on 16 jan. 2016
@author: danhe
'''
import numpy as np
from math import ceil
from pycuda import autoinit, driver, compiler, gpuarray
from gpu_prefixsum import DoubleBuffer
def read_xyz(file_name):
i = 0
ion_type = []
coordinate = ''
file = open(file_name, 'r')
lines = file.readlines()
ions = int(lines[0])
while i < ions:
line = lines[2 + i].split()
ion_type.append(line[0])
coordinate += line[1] + ' ' + line[2] + ' ' + line[3] + '\n'
i += 1
coordinate = np.fromstring(coordinate, sep=' ').reshape(ions, 3)
return ions, ion_type, coordinate
class Simulation(object):
'''
classdocs
'''
def __init__(self, coordinate, mass, box_size, cutoff, eps, sig, dt=1):
'''
Constructor
'''
autoinit.context.set_cache_config(driver.func_cache.PREFER_L1)
# Scalars
self.dfloat = 'float32'
self.dint = 'int32'
self.iter = np.int32(0)
self.kb = np.float32(8.6173324e-5)
self.ions = np.int32(coordinate.shape[0])
self.mass = np.float32(mass)
self.cutoff = np.float32(cutoff)
self.eps = np.float32(eps)
self.sig = np.float32(sig)
self.dt = np.float32(dt)
self.threads = 256
self.block = (self.threads, 1, 1)
self.grid = (ceil(self.ions / self.threads), 1, 1)
self.ion_type = ['Ar'] * self.ions
# float3
self.box_size = np.array(box_size).astype(self.dfloat)
# 1D arrays
self.potential_energy = gpuarray.zeros(self.ions, np.float32)
self.kinetic_energy = gpuarray.zeros(self.ions, np.float32)
# 3D arrays
self.coordinate = gpuarray.to_gpu_async(coordinate.astype(self.dfloat))
self.coordinate_sorted = gpuarray.to_gpu_async(coordinate.astype(self.dfloat))
self.velocity = gpuarray.zeros_like(self.coordinate)
self.velocity_sorted = gpuarray.zeros_like(self.coordinate)
self.force = gpuarray.zeros_like(self.coordinate)
# Timers
self.start = driver.Event()
self.end = driver.Event()
self.timer = 0
# System data
self.system_pe = np.array([]).astype(self.dfloat)
self.system_ke = np.array([]).astype(self.dfloat)
# Create the bins
self.create_bins()
# Load kernels
float3 = gpuarray.vec.float3
int3 = gpuarray.vec.int3
self.prefixsum = DoubleBuffer(self.bins, self.threads)
self.fill_bins = self.load_function('lj_force.cu', 'fillBins', ('PPP', float3, int3, 'i'))
self.counting_sort = self.load_function('lj_force.cu', 'countingSort', 'PPPPPPi')
self.lj_force = self.load_function('lj_force.cu', 'ljForce', ('PPPPP', float3, float3, int3, 'fffi'))
self.verlet_pre = self.load_function('lj_force.cu', 'verletPre', ('PPPPP', float3, 'ffi'))
self.verlet_pos = self.load_function('lj_force.cu', 'verletPos', 'PPPffi')
return
def read_kernel(self, file_name):
file = open(file_name, 'r')
kernel = ''.join(file.readlines())
return kernel
def load_function(self, file_name, func_name, func_input):
mod = compiler.SourceModule(self.read_kernel(file_name), options=['-use_fast_math'], no_extern_c=True)
# mod = compiler.SourceModule(self.read_kernel(file_name), options=['-use_fast_math', '--maxrregcount=32'], no_extern_c=True)
func = mod.get_function(func_name)
func.prepare(func_input)
return func
def create_bins(self):
self.bin_dim = np.floor(2 * self.box_size / self.cutoff).astype(self.dint)
self.bin_length = (self.box_size / self.bin_dim).astype(self.dfloat)
self.bins = np.prod(self.bin_dim)
self.bin_index = gpuarray.zeros(self.ions, np.int32)
self.bin_count = gpuarray.zeros(self.bins, np.int32)
return
def write_xyz(self, file_name, write_delay=1, io='w'):
if self.iter % write_delay == 0:
coordinate = self.coordinate_sorted.get()
file = open(file_name, io)
file.write('%i\n' % self.ions)
file.write('Current iteration %i, simulation time %f fs.\n' % (self.iter, self.iter * self.dt))
for i in zip(self.ion_type, coordinate[:, 0], coordinate[:, 1], coordinate[:, 2]):
file.write('%3s %8.3f %8.3f %8.3f\n' % i)
file.close()
return
else:
return
def get_force(self):
self.fill_bins.prepared_call(self.grid, self.block,
self.coordinate.gpudata, self.bin_index.gpudata, self.bin_count.gpudata,
self.bin_length, self.bin_dim, self.ions)
self.prefixsum.run(self.bin_count)
self.counting_sort.prepared_call(self.grid, self.block,
self.bin_index.gpudata, self.prefixsum.output.gpudata, self.coordinate.gpudata, self.velocity.gpudata,
self.coordinate_sorted.gpudata, self.velocity_sorted.gpudata, self.ions)
self.lj_force.prepared_call(self.grid, self.block,
self.coordinate_sorted.gpudata, self.force.gpudata,
self.potential_energy.gpudata, self.bin_count.gpudata, self.prefixsum.output.gpudata,
self.box_size, self.bin_length, self.bin_dim, self.cutoff, self.eps, self.sig, self.ions)
self.bin_count = gpuarray.zeros(self.bins, np.int32)
return
def verlet_part1(self):
self.verlet_pre.prepared_call(self.grid, self.block,
self.coordinate.gpudata, self.velocity.gpudata,
self.coordinate_sorted.gpudata, self.velocity_sorted.gpudata,
self.force.gpudata, self.box_size, self.mass, self.dt, self.ions)
return
def verlet_part2(self):
self.verlet_pos.prepared_call(self.grid, self.block,
self.velocity_sorted.gpudata, self.force.gpudata, self.kinetic_energy.gpudata,
self.mass, self.dt, self.ions)
return
def run_nve(self):
self.start.record()
self.start.synchronize()
self.verlet_part1()
self.get_force()
self.verlet_part2()
self.end.record()
self.end.synchronize()
self.timer += 0.001 * self.start.time_till(self.end)
self.iter += 1
return
def get_system_info(self):
self.system_pe = np.append(self.system_pe, np.sum(self.potential_energy.get()))
self.system_ke = np.append(self.system_ke, np.sum(self.kinetic_energy.get()))
return
def print_status(self, write_delay=1):
if self.iter < 2:
print('PyCUMD')
print(' Simulation box size: (%1.2f %1.2f %1.2f)' % (self.box_size[0], self.box_size[1], self.box_size[2]))
print(' %i atoms' % self.ions)
print(' %i bins' % self.bins)
print(' %i threads\n' % self.threads)
print('%9s %13s %13s %13s %13s' % ('Iter', 'Kin. E. (eV)', 'Pot. E. (eV)', 'Tot. E. (eV)', 'Perf. (Mp/s)'))
elif self.iter % write_delay == 0:
self.get_system_info()
print('%9i %13.5f %13.5f %13.5f %13.5f' % (self.iter, self.system_ke[-1], self.system_pe[-1],
self.system_ke[-1] + self.system_pe[-1],
1e-6 * self.ions * self.iter / self.timer))
return
else:
return