File size: 7,299 Bytes
66c9c8a
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
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
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
# Copyright (c) 2022 NVIDIA CORPORATION.  All rights reserved.
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto.  Any use, reproduction, disclosure or
# distribution of this software and related documentation without an express
# license agreement from NVIDIA CORPORATION is strictly prohibited.

###########################################################################
# Example Fluid
#
# Shows how to implement a simple 2D Stable Fluids solver using
# multidimensional arrays and launches.
#
###########################################################################

import math

import warp as wp
import warp.render

wp.init()

grid_width = wp.constant(256)
grid_height = wp.constant(128)


@wp.func
def lookup_float(f: wp.array2d(dtype=float), x: int, y: int):
    x = wp.clamp(x, 0, grid_width - 1)
    y = wp.clamp(y, 0, grid_height - 1)

    return f[x, y]


@wp.func
def sample_float(f: wp.array2d(dtype=float), x: float, y: float):
    lx = int(wp.floor(x))
    ly = int(wp.floor(y))

    tx = x - float(lx)
    ty = y - float(ly)

    s0 = wp.lerp(lookup_float(f, lx, ly), lookup_float(f, lx + 1, ly), tx)
    s1 = wp.lerp(lookup_float(f, lx, ly + 1), lookup_float(f, lx + 1, ly + 1), tx)

    s = wp.lerp(s0, s1, ty)
    return s


@wp.func
def lookup_vel(f: wp.array2d(dtype=wp.vec2), x: int, y: int):
    if x < 0 or x >= grid_width:
        return wp.vec2()
    if y < 0 or y >= grid_height:
        return wp.vec2()

    return f[x, y]


@wp.func
def sample_vel(f: wp.array2d(dtype=wp.vec2), x: float, y: float):
    lx = int(wp.floor(x))
    ly = int(wp.floor(y))

    tx = x - float(lx)
    ty = y - float(ly)

    s0 = wp.lerp(lookup_vel(f, lx, ly), lookup_vel(f, lx + 1, ly), tx)
    s1 = wp.lerp(lookup_vel(f, lx, ly + 1), lookup_vel(f, lx + 1, ly + 1), tx)

    s = wp.lerp(s0, s1, ty)
    return s


@wp.kernel
def advect(
    u0: wp.array2d(dtype=wp.vec2),
    u1: wp.array2d(dtype=wp.vec2),
    rho0: wp.array2d(dtype=float),
    rho1: wp.array2d(dtype=float),
    dt: float,
):
    i, j = wp.tid()

    u = u0[i, j]

    # trace backward
    p = wp.vec2(float(i), float(j))
    p = p - u * dt

    # advect
    u1[i, j] = sample_vel(u0, p[0], p[1])
    rho1[i, j] = sample_float(rho0, p[0], p[1])


@wp.kernel
def divergence(u: wp.array2d(dtype=wp.vec2), div: wp.array2d(dtype=float)):
    i, j = wp.tid()

    if i == grid_width - 1:
        return
    if j == grid_height - 1:
        return

    dx = (u[i + 1, j][0] - u[i, j][0]) * 0.5
    dy = (u[i, j + 1][1] - u[i, j][1]) * 0.5

    div[i, j] = dx + dy


@wp.kernel
def pressure_solve(p0: wp.array2d(dtype=float), p1: wp.array2d(dtype=float), div: wp.array2d(dtype=float)):
    i, j = wp.tid()

    s1 = lookup_float(p0, i - 1, j)
    s2 = lookup_float(p0, i + 1, j)
    s3 = lookup_float(p0, i, j - 1)
    s4 = lookup_float(p0, i, j + 1)

    # Jacobi update
    err = s1 + s2 + s3 + s4 - div[i, j]

    p1[i, j] = err * 0.25


@wp.kernel
def pressure_apply(p: wp.array2d(dtype=float), u: wp.array2d(dtype=wp.vec2)):
    i, j = wp.tid()

    if i == 0 or i == grid_width - 1:
        return
    if j == 0 or j == grid_height - 1:
        return

    # pressure gradient
    f_p = wp.vec2(p[i + 1, j] - p[i - 1, j], p[i, j + 1] - p[i, j - 1]) * 0.5

    u[i, j] = u[i, j] - f_p


@wp.kernel
def integrate(u: wp.array2d(dtype=wp.vec2), rho: wp.array2d(dtype=float), dt: float):
    i, j = wp.tid()

    # gravity
    f_g = wp.vec2(-90.8, 0.0) * rho[i, j]

    # integrate
    u[i, j] = u[i, j] + dt * f_g

    # fade
    rho[i, j] = rho[i, j] * (1.0 - 0.1 * dt)


@wp.kernel
def init(rho: wp.array2d(dtype=float), u: wp.array2d(dtype=wp.vec2), radius: int, dir: wp.vec2):
    i, j = wp.tid()

    d = wp.length(wp.vec2(float(i - grid_width / 2), float(j - grid_height / 2)))

    if d < radius:
        rho[i, j] = 1.0
        u[i, j] = dir


class Example:
    def __init__(self, **kwargs):
        self.device = wp.get_device()

        self.sim_fps = 60.0
        self.sim_substeps = 2
        self.iterations = 100
        self.sim_dt = (1.0 / self.sim_fps) / self.sim_substeps
        self.sim_time = 0.0

        self.device = wp.get_device()

        shape = (grid_width, grid_height)

        self.u0 = wp.zeros(shape, dtype=wp.vec2)
        self.u1 = wp.zeros(shape, dtype=wp.vec2)

        self.rho0 = wp.zeros(shape, dtype=float)
        self.rho1 = wp.zeros(shape, dtype=float)

        self.p0 = wp.zeros(shape, dtype=float)
        self.p1 = wp.zeros(shape, dtype=float)
        self.div = wp.zeros(shape, dtype=float)

        # capture pressure solve as a CUDA graph
        if self.device.is_cuda:
            wp.capture_begin(self.device)
            try:
                self.pressure_iterations()
            finally:
                self.graph = wp.capture_end(self.device)

    def update(self):
        with wp.ScopedTimer("update"):
            for _ in range(self.sim_substeps):
                shape = (grid_width, grid_height)
                dt = self.sim_dt

                speed = 400.0
                angle = math.sin(self.sim_time * 4.0) * 1.5
                vel = wp.vec2(math.cos(angle) * speed, math.sin(angle) * speed)

                # update emitters
                wp.launch(init, dim=shape, inputs=[self.rho0, self.u0, 5, vel])

                # force integrate
                wp.launch(integrate, dim=shape, inputs=[self.u0, self.rho0, dt])
                wp.launch(divergence, dim=shape, inputs=[self.u0, self.div])

                # pressure solve
                self.p0.zero_()
                self.p1.zero_()

                if self.device.is_cuda:
                    wp.capture_launch(self.graph)

                else:
                    self.pressure_iterations()

                # velocity update
                wp.launch(pressure_apply, dim=shape, inputs=[self.p0, self.u0])

                # semi-Lagrangian advection
                wp.launch(advect, dim=shape, inputs=[self.u0, self.u1, self.rho0, self.rho1, dt])

                # swap buffers
                (self.u0, self.u1) = (self.u1, self.u0)
                (self.rho0, self.rho1) = (self.rho1, self.rho0)

                self.sim_time += dt

    def render(self):
        pass

    def pressure_iterations(self):
        for _ in range(self.iterations):
            wp.launch(pressure_solve, dim=self.p0.shape, inputs=[self.p0, self.p1, self.div])

            # swap pressure fields
            (self.p0, self.p1) = (self.p1, self.p0)

    def update_and_render_frame(self, frame_num=None, img=None):
        self.update()

        with wp.ScopedTimer("render"):
            if img:
                img.set_array(self.rho0.numpy())

        return (img,)


if __name__ == "__main__":
    import matplotlib
    import matplotlib.animation as anim
    import matplotlib.pyplot as plt

    example = Example()

    fig = plt.figure()

    img = plt.imshow(example.rho0.numpy(), origin="lower", animated=True, interpolation="antialiased")
    img.set_norm(matplotlib.colors.Normalize(0.0, 1.0))
    seq = anim.FuncAnimation(
        fig, example.update_and_render_frame, fargs=(img,), frames=100000, blit=True, interval=8, repeat=False
    )

    plt.show()