smyalygames/FiniteVolumeGPU
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Implemented variable timestep

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This commit is contained in:
André R. Brodtkorb
2018-11-15 16:48:47 +01:00
parent 7592ad5b9f
commit ddac53271c
15 changed files with 224 additions and 29 deletions
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20
GPUSimulators/HLL.py
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@@ -24,6 +24,7 @@ from GPUSimulators import Simulator, Common
from GPUSimulators.Simulator import BaseSimulator, BoundaryCondition
import numpy as np
from pycuda import gpuarray
@@ -53,6 +54,7 @@ class HLL (Simulator.BaseSimulator):
nx, ny,
dx, dy, dt,
g,
cfl_scale=0.9,
boundary_conditions=BoundaryCondition(),
block_width=16, block_height=16):
@@ -62,6 +64,7 @@ class HLL (Simulator.BaseSimulator):
dx, dy, dt,
block_width, block_height);
self.g = np.float32(g)
self.cfl_scale = cfl_scale
self.boundary_conditions = boundary_conditions.asCodedInt()
#Get kernels
@@ -76,7 +79,7 @@ class HLL (Simulator.BaseSimulator):
},
jit_compile_args={})
self.kernel = module.get_function("HLLKernel")
self.kernel.prepare("iiffffiPiPiPiPiPiPi")
self.kernel.prepare("iiffffiPiPiPiPiPiPiP")
#Create data by uploading to device
self.u0 = Common.ArakawaA2D(self.stream,
@@ -87,6 +90,8 @@ class HLL (Simulator.BaseSimulator):
nx, ny,
1, 1,
[None, None, None])
self.cfl_data = gpuarray.GPUArray(self.grid_size, dtype=np.float32)
self.cfl_data.fill(self.dt, stream=self.stream)
def step(self, dt):
self.kernel.prepared_async_call(self.grid_size, self.block_size, self.stream,
@@ -99,10 +104,19 @@ class HLL (Simulator.BaseSimulator):
self.u0[2].data.gpudata, self.u0[2].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[2].data.gpudata, self.u1[2].data.strides[0],
self.cfl_data.gpudata)
self.u0, self.u1 = self.u1, self.u0
self.t += dt
self.nt += 1
def download(self):
return self.u0.download(self.stream)
return self.u0.download(self.stream)
def check(self):
self.u0.check()
self.u1.check()
def computeDt(self):
max_dt = gpuarray.min(self.cfl_data, stream=self.stream).get();
return max_dt*0.5*self.cfl_scale