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