working heat1d on gpu, but slow

main
Bryce Allen 4 years ago
parent be04d5dee2
commit 73fe0ff8f2

@ -0,0 +1,144 @@
#!/usr/bin/env julia
using DelimitedFiles
using CUDA
function heat1d_ftcs_cpu(diffusivity, xlength, left_boundary,
right_boundary, init_fn,
dt, nsteps, dx, print_at_steps, outf,
psource_x, psource_value)
npoints = ceil(Int, xlength / dx) + 1
T1 = zeros(Float32, npoints)
T2 = similar(T1)
xs = range(0.0, xlength, length=npoints)
c = diffusivity * dt / dx^2
psource_offset = ceil(Int, psource_x / xlength * npoints)
psource_dt = psource_value * dt
if c > 0.5
println("c = ", c)
return -1
end
T1[1] = left_boundary
T1[end] = right_boundary
T2[1] = left_boundary
T2[end] = right_boundary
T1[2:end-1] = init_fn.(xs[2:end-1])
# first line of output is x values, for plotting
writedlm(outf, xs', ',')
# output initial condition state
writedlm(outf, T1', ',')
for j in 1:2:nsteps
for i in 2:npoints-1
T2[i] = T1[i] + c * (T1[i+1] - 2.0 * T1[i] + T1[i-1])
if i == psource_offset
T2[i] += psource_dt
end
end
for i in 2:npoints-1
T1[i] = T2[i] + c * (T2[i+1] - 2.0 * T2[i] + T2[i-1])
if i == psource_offset
T1[i] += psource_dt
end
end
if mod(j+1, print_at_steps) == 0
writedlm(outf, T1', ',')
end
end
end
function gpu_ftcs_step!(T, Told, c, psource_offset, psource_dt)
start_idx = (blockIdx().x - 1) * blockDim().x + threadIdx().x + 1
stride = gridDim().x * blockDim().x
for i in start_idx:stride:length(T)-1
@inbounds Ti = Told[i] + c * (Told[i+1] - 2.0 * Told[i] + Told[i-1])
if i == psource_offset
Ti += psource_dt
end
T[i] = Ti
end
end
function heat1d_ftcs_gpu(diffusivity, xlength, left_boundary,
right_boundary, init_fn,
dt, nsteps, dx, print_at_steps, outf,
psource_x, psource_value)
npoints = Int(ceil(xlength / dx)) + 1
T = zeros(Float32, npoints)
xs = range(0.0, xlength, length=npoints)
T1_d = CuArray{Float32}(undef, length(T))
T2_d = similar(T1_d)
c = diffusivity * dt / dx^2
psource_offset = ceil(Int, psource_x / xlength * npoints)
psource_dt = psource_value * dt
if c > 0.5
println("c = ", c)
return -1
end
T[1] = left_boundary
T[end] = right_boundary
T[2:end-1] = init_fn.(xs[2:end-1])
# first line of output is x values, for plotting
writedlm(outf, xs', ',')
# output initial condition state
writedlm(outf, T', ',')
copyto!(T1_d, T)
NTHREADS = 128
NBLOCKS = ceil(Int, (length(T)-2) / NTHREADS)
for j in 1:2:nsteps
CUDA.@sync begin
@cuda threads=NTHREADS blocks=NBLOCKS gpu_ftcs_step!(T2_d, T1_d, c,
psource_offset,
psource_dt)
end
CUDA.@sync begin
@cuda threads=NTHREADS blocks=NBLOCKS gpu_ftcs_step!(T1_d, T2_d, c,
psource_offset,
psource_dt)
end
if mod(j+1, print_at_steps) == 0
copyto!(T, T1_d)
writedlm(outf, T', ',')
end
end
end
function gaussian1d(x)
return exp(-(5.0*(x-0.5))^2)
end
function test_cpu()
open("out/heat1d_cpu.txt", "w") do io
heat1d_ftcs_cpu(0.001, 1.0, 0.0, 0.0, gaussian1d,
0.0004, 2^20, 2^-10, 2^13, io, 0.2, 1.0)
end
end
function test_gpu()
CUDA.allowscalar(false)
open("out/heat1d_gpu.txt", "w") do io
heat1d_ftcs_gpu(0.001, 1.0, 0.0, 0.0, gaussian1d,
0.0004, 2^20, 2^-10, 2^13, io, 0.2, 1.0)
end
end
#@time test_cpu()
test_gpu()
#@time test_gpu()

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#!/usr/bin/env python3
import sys
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
fig, ax = plt.subplots()
data_path = sys.argv[1]
f = open(data_path)
# first line is x values
line = f.readline().strip()
if ',' in line:
sep = ','
else:
sep = ' '
x = np.fromstring(line, sep=sep)
# second line is y values at time 0
y = np.fromstring(f.readline().strip(), sep=sep)
graph, = ax.plot(x, y)
def animate(line):
y = np.fromstring(line.strip(), sep=sep)
print(np.max(y))
graph.set_ydata(y)
return graph,
ani = animation.FuncAnimation(fig, animate, f, interval=100, blit=True,
repeat=False)
plt.show()
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