lbm_cl.py 4.35 KB
 ph committed Nov 28, 2017 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 ``````#!/usr/bin/env python3 # -*- coding: utf-8 -*- # resolution of a transport equation by the finite volume method # on regular grid # regular python implementation compared to a pyopencl version from __future__ import absolute_import, print_function import pyopencl as cl import numpy as np import matplotlib.pyplot as plt import time ##################" definition of default values # number of conservative variables `````` ph committed Dec 05, 2017 21 ``````_m = 2 `````` ph committed Nov 28, 2017 22 23 24 25 `````` # number of kinetic variables _n = 4 * _m `````` ph committed Dec 05, 2017 26 ``````_ivplot = 1 `````` ph committed Nov 28, 2017 27 28 `````` # grid size `````` ph committed Dec 05, 2017 29 30 ``````_nx = 64 _ny = 64 `````` ph committed Nov 28, 2017 31 `````` `````` ph committed Dec 05, 2017 32 33 34 35 36 ``````Lx = 2 * 3.14159265358979323846264338328 Ly = 2 * 3.14159265358979323846264338328 Lx = 1 Ly = 1 `````` ph committed Nov 28, 2017 37 38 39 40 41 42 43 44 `````` _dx = Lx / _nx _dy = Ly / _ny # transport velocity vel = np.array([1., 1.]) # lattice speed `````` ph committed Dec 05, 2017 45 ``````_vmax = 7. `````` ph committed Nov 28, 2017 46 47 48 `````` # time stepping `````` ph committed Nov 28, 2017 49 50 ``````_Tmax = 10. / _vmax #_Tmax = 0. `````` ph committed Nov 28, 2017 51 52 53 54 55 56 57 58 59 60 ``````cfl = 1 _dt = cfl * _dx / _vmax ############# end of default values def solve_ocl(m = _m, n = _n, nx = _nx, ny = _ny, Tmax = _Tmax, vmax = _vmax, dx = _dx, dy = _dy, `````` ph committed Dec 05, 2017 61 `````` dt = _dt, `````` ph committed Nov 28, 2017 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 `````` animate = False): # load and adjust C program source = open("lbm_kernels.cl", "r").read() source = source.replace("_nx_", "("+str(nx)+")") source = source.replace("_ny_", "("+str(ny)+")") source = source.replace("_dx_", "("+str(dx)+"f)") source = source.replace("_dy_", "("+str(dy)+"f)") source = source.replace("_dt_", "("+str(dt)+"f)") source = source.replace("_m_", "("+str(m)+")") source = source.replace("_n_", "("+str(n)+")") source = source.replace("_vx_", "("+str(vel[0])+"f)") source = source.replace("_vy_", "("+str(vel[1])+"f)") source = source.replace("_lambda_", "("+str(vmax)+"f)") #print(source) #exit(0) # OpenCL init ctx = cl.create_some_context() mf = cl.mem_flags # compile OpenCL C program prg = cl.Program(ctx, source).build(options = "-cl-strict-aliasing \ -cl-fast-relaxed-math") # create OpenCL buffers fn_gpu = cl.Buffer(ctx, mf.READ_WRITE, size=(4 * m * nx * ny * np.dtype('float32').itemsize)) fnp1_gpu = cl.Buffer(ctx, mf.READ_WRITE, size=(4 * m * nx * ny * np.dtype('float32').itemsize)) # create a queue (for submitting opencl operations) queue = cl.CommandQueue(ctx, properties=cl.command_queue_properties.PROFILING_ENABLE) # init data event = prg.init_sol(queue, (nx * ny, ), (32, ), fn_gpu) event.wait() # number of animation frames `````` ph committed Nov 28, 2017 104 `````` nbplots = 100 `````` ph committed Nov 28, 2017 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 `````` itermax = int(np.floor(Tmax / dt)) iterplot = int(itermax / nbplots) # time loop t = 0 iter = 0 elapsed = 0.; fn_cpu = np.empty((4 * m * nx * ny, ), dtype = np.float32) print("start OpenCL computations...") while t < Tmax: t = t + dt iter = iter + 1 #event = prg.time_step(queue, (nx * ny, ), (32, ), wn_gpu, wnp1_gpu) event = prg.time_step(queue, (nx * ny, ), (64, ), fn_gpu, fnp1_gpu) #event = prg.time_step(queue, (nx * ny, ), (32, ), wn_gpu, wnp1_gpu, wait_for = [event]) event.wait() elapsed += 1e-9 * (event.profile.end - event.profile.start) # exchange buffer references for avoiding a copy fn_gpu, fnp1_gpu = fnp1_gpu, fn_gpu print("iter=",iter, " t=",t, "elapsed (s)=",elapsed) if iter % iterplot == 0 and animate: cl.enqueue_copy(queue, fn_cpu, fn_gpu).wait() `````` ph committed Dec 05, 2017 128 `````` wplot = np.reshape(fn_cpu, (4, m, nx, ny)) `````` ph committed Nov 28, 2017 129 `````` plt.clf() `````` ph committed Nov 28, 2017 130 `````` #plt.imshow(np.sum(wplot, axis = 0),vmin=0, vmax=1) `````` ph committed Dec 05, 2017 131 `````` plt.imshow(np.sum(wplot[:, _ivplot, :, :], axis = 0)) `````` ph committed Nov 28, 2017 132 133 134 135 136 137 138 `````` plt.gca().invert_yaxis() plt.colorbar() plt.pause(0.01) # copy OpenCL data to CPU and return the results cl.enqueue_copy(queue, fn_cpu, fn_gpu).wait() `````` ph committed Dec 05, 2017 139 `````` wplot_gpu = np.reshape(fn_cpu,(4, m, nx, ny)) `````` ph committed Nov 28, 2017 140 141 142 `````` return wplot_gpu # gpu solve `````` ph committed Nov 28, 2017 143 ``````wplot_gpu = solve_ocl(animate = True) `````` ph committed Dec 05, 2017 144 ``````#print(np.sum(wplot_gpu[:, _ivplot, :, :],axis=0)) `````` ph committed Nov 28, 2017 145 ``````plt.clf() `````` ph committed Dec 05, 2017 146 147 ``````#plt.imshow(np.sum(wplot_gpu[:, _ivplot, :, :],axis=0), vmin=0, vmax=1) plt.imshow(np.sum(wplot_gpu[:, _ivplot, :, :],axis=0)) `````` ph committed Nov 28, 2017 148 149 150 151 ``````plt.gca().invert_yaxis() plt.colorbar() plt.show() `````` ph committed Nov 28, 2017 152 153 154 155 156 157 ``````# for iv in range(4): # plt.imshow(wplot_gpu[iv,:,:]) # plt.gca().invert_yaxis() # plt.colorbar() # plt.show() `````` ph committed Nov 28, 2017 158 159 160 161 162 163 164 165 166 `````` # check difference # plt.clf() # plt.imshow(wplot_cpu-wplot_gpu) # plt.gca().invert_yaxis() # plt.colorbar() # plt.show() ``````