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https://github.com/smyalygames/FiniteVolumeGPU.git
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276 lines
11 KiB
Python
276 lines
11 KiB
Python
# -*- coding: utf-8 -*-
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"""
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This python module implements the 2nd order HLL flux
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Copyright (C) 2016 SINTEF ICT
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This program is free software: you can redistribute it and/or modify
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it under the terms of the GNU General Public License as published by
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the Free Software Foundation, either version 3 of the License, or
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(at your option) any later version.
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This program is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public License
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along with this program. If not, see <http://www.gnu.org/licenses/>.
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"""
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#Import packages we need
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from GPUSimulators import Simulator, Common
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from GPUSimulators.Simulator import BaseSimulator, BoundaryCondition
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import numpy as np
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from pycuda import gpuarray
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class EE2D_KP07_dimsplit (BaseSimulator):
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"""
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Class that solves the SW equations using the Forward-Backward linear scheme
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"""
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def __init__(self,
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context,
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rho, rho_u, rho_v, E,
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nx, ny,
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dx, dy,
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g,
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gamma,
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theta=1.3,
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cfl_scale=0.9,
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boundary_conditions=BoundaryCondition(),
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block_width=16, block_height=8):
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"""
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Initialization routine
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Args:
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rho: Density
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rho_u: Momentum along x-axis
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rho_v: Momentum along y-axis
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E: energy
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nx: Number of cells along x-axis
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ny: Number of cells along y-axis
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dx: Grid cell spacing along x-axis
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dy: Grid cell spacing along y-axis
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dt: Size of each timestep
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g: Gravitational constant
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gamma: Gas constant
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p: pressure
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"""
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# Call super constructor
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super().__init__(context,
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nx, ny,
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dx, dy,
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boundary_conditions,
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cfl_scale,
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2,
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block_width, block_height)
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self.g = np.float32(g)
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self.gamma = np.float32(gamma)
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self.theta = np.float32(theta)
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#Get kernels
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module = context.get_module("cuda/EE2D_KP07_dimsplit.cu",
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defines={
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'BLOCK_WIDTH': self.block_size[0],
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'BLOCK_HEIGHT': self.block_size[1]
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},
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compile_args={
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'no_extern_c': True,
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'options': ["--use_fast_math"],
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},
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jit_compile_args={})
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self.kernel = module.get_function("KP07DimsplitKernel")
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self.kernel.prepare("iiffffffiiPiPiPiPiPiPiPiPiPiiii")
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#Create data by uploading to device
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self.u0 = Common.ArakawaA2D(self.stream,
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nx, ny,
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2, 2,
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[rho, rho_u, rho_v, E])
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self.u1 = Common.ArakawaA2D(self.stream,
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nx, ny,
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2, 2,
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[None, None, None, None])
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self.cfl_data = gpuarray.GPUArray(self.grid_size, dtype=np.float32)
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dt_x = np.min(self.dx / (np.abs(rho_u/rho) + np.sqrt(gamma*rho)))
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dt_y = np.min(self.dy / (np.abs(rho_v/rho) + np.sqrt(gamma*rho)))
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self.dt = min(dt_x, dt_y)
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self.cfl_data.fill(self.dt, stream=self.stream)
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def substep(self, dt, step_number, external=True, internal=True):
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self.substepDimsplit(0.5*dt, step_number, external, internal)
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def substepDimsplit(self, dt, substep, external, internal):
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if external and internal:
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#print("COMPLETE DOMAIN (dt=" + str(dt) + ")")
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self.kernel.prepared_async_call(self.grid_size, self.block_size, self.stream,
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self.nx, self.ny,
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self.dx, self.dy, dt,
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self.g,
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self.gamma,
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self.theta,
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substep,
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self.boundary_conditions,
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self.u0[0].data.gpudata, self.u0[0].data.strides[0],
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self.u0[1].data.gpudata, self.u0[1].data.strides[0],
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self.u0[2].data.gpudata, self.u0[2].data.strides[0],
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self.u0[3].data.gpudata, self.u0[3].data.strides[0],
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self.u1[0].data.gpudata, self.u1[0].data.strides[0],
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self.u1[1].data.gpudata, self.u1[1].data.strides[0],
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self.u1[2].data.gpudata, self.u1[2].data.strides[0],
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self.u1[3].data.gpudata, self.u1[3].data.strides[0],
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self.cfl_data.gpudata,
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0, 0,
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self.nx, self.ny)
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return
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if external and not internal:
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###################################
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# XXX: Corners are treated twice! #
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###################################
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ns_grid_size = (self.grid_size[0], 1)
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# NORTH
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# (x0, y0) x (x1, y1)
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# (0, ny-y_halo) x (nx, ny)
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self.kernel.prepared_async_call(ns_grid_size, self.block_size, self.stream,
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self.nx, self.ny,
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self.dx, self.dy, dt,
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self.g,
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self.gamma,
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self.theta,
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substep,
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self.boundary_conditions,
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self.u0[0].data.gpudata, self.u0[0].data.strides[0],
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self.u0[1].data.gpudata, self.u0[1].data.strides[0],
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self.u0[2].data.gpudata, self.u0[2].data.strides[0],
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self.u0[3].data.gpudata, self.u0[3].data.strides[0],
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self.u1[0].data.gpudata, self.u1[0].data.strides[0],
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self.u1[1].data.gpudata, self.u1[1].data.strides[0],
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self.u1[2].data.gpudata, self.u1[2].data.strides[0],
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self.u1[3].data.gpudata, self.u1[3].data.strides[0],
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self.cfl_data.gpudata,
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0, self.ny - int(self.u0[0].y_halo),
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self.nx, self.ny)
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# SOUTH
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# (x0, y0) x (x1, y1)
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# (0, 0) x (nx, y_halo)
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self.kernel.prepared_async_call(ns_grid_size, self.block_size, self.stream,
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self.nx, self.ny,
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self.dx, self.dy, dt,
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self.g,
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self.gamma,
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self.theta,
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substep,
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self.boundary_conditions,
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self.u0[0].data.gpudata, self.u0[0].data.strides[0],
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self.u0[1].data.gpudata, self.u0[1].data.strides[0],
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self.u0[2].data.gpudata, self.u0[2].data.strides[0],
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self.u0[3].data.gpudata, self.u0[3].data.strides[0],
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self.u1[0].data.gpudata, self.u1[0].data.strides[0],
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self.u1[1].data.gpudata, self.u1[1].data.strides[0],
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self.u1[2].data.gpudata, self.u1[2].data.strides[0],
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self.u1[3].data.gpudata, self.u1[3].data.strides[0],
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self.cfl_data.gpudata,
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0, 0,
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self.nx, int(self.u0[0].y_halo))
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we_grid_size = (1, self.grid_size[1])
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# WEST
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# (x0, y0) x (x1, y1)
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# (0, 0) x (x_halo, ny)
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self.kernel.prepared_async_call(we_grid_size, self.block_size, self.stream,
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self.nx, self.ny,
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self.dx, self.dy, dt,
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self.g,
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self.gamma,
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self.theta,
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substep,
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self.boundary_conditions,
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self.u0[0].data.gpudata, self.u0[0].data.strides[0],
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self.u0[1].data.gpudata, self.u0[1].data.strides[0],
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self.u0[2].data.gpudata, self.u0[2].data.strides[0],
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self.u0[3].data.gpudata, self.u0[3].data.strides[0],
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self.u1[0].data.gpudata, self.u1[0].data.strides[0],
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self.u1[1].data.gpudata, self.u1[1].data.strides[0],
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self.u1[2].data.gpudata, self.u1[2].data.strides[0],
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self.u1[3].data.gpudata, self.u1[3].data.strides[0],
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self.cfl_data.gpudata,
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0, 0,
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int(self.u0[0].x_halo), self.ny)
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# EAST
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# (x0, y0) x (x1, y1)
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# (nx-x_halo, 0) x (nx, ny)
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self.kernel.prepared_async_call(we_grid_size, self.block_size, self.stream,
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self.nx, self.ny,
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self.dx, self.dy, dt,
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self.g,
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self.gamma,
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self.theta,
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substep,
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self.boundary_conditions,
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self.u0[0].data.gpudata, self.u0[0].data.strides[0],
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self.u0[1].data.gpudata, self.u0[1].data.strides[0],
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self.u0[2].data.gpudata, self.u0[2].data.strides[0],
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self.u0[3].data.gpudata, self.u0[3].data.strides[0],
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self.u1[0].data.gpudata, self.u1[0].data.strides[0],
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self.u1[1].data.gpudata, self.u1[1].data.strides[0],
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self.u1[2].data.gpudata, self.u1[2].data.strides[0],
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self.u1[3].data.gpudata, self.u1[3].data.strides[0],
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self.cfl_data.gpudata,
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self.nx - int(self.u0[0].x_halo), 0,
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self.nx, self.ny)
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return
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if internal and not external:
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# INTERNAL DOMAIN
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# (x0, y0) x (x1, y1)
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# (x_halo, y_halo) x (nx - x_halo, ny - y_halo)
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self.kernel.prepared_async_call(self.grid_size, self.block_size, self.internal_stream,
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self.nx, self.ny,
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self.dx, self.dy, dt,
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self.g,
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self.gamma,
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self.theta,
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substep,
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self.boundary_conditions,
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self.u0[0].data.gpudata, self.u0[0].data.strides[0],
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self.u0[1].data.gpudata, self.u0[1].data.strides[0],
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self.u0[2].data.gpudata, self.u0[2].data.strides[0],
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self.u0[3].data.gpudata, self.u0[3].data.strides[0],
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self.u1[0].data.gpudata, self.u1[0].data.strides[0],
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self.u1[1].data.gpudata, self.u1[1].data.strides[0],
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self.u1[2].data.gpudata, self.u1[2].data.strides[0],
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self.u1[3].data.gpudata, self.u1[3].data.strides[0],
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self.cfl_data.gpudata,
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int(self.u0[0].x_halo), int(self.u0[0].y_halo),
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self.nx - int(self.u0[0].x_halo), self.ny - int(self.u0[0].y_halo))
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return
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def swapBuffers(self):
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self.u0, self.u1 = self.u1, self.u0
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return
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def getOutput(self):
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return self.u0
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def check(self):
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self.u0.check()
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self.u1.check()
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return
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def computeDt(self):
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max_dt = gpuarray.min(self.cfl_data, stream=self.stream).get();
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return max_dt*0.5 |