mirror of
https://github.com/smyalygames/FiniteVolumeGPU.git
synced 2025-05-18 14:34:13 +02:00
Removed fixed timestep size
This commit is contained in:
parent
ddac53271c
commit
815b4493b5
@ -58,7 +58,7 @@ class EE2D_KP07_dimsplit (BaseSimulator):
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context,
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rho, rho_u, rho_v, E,
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nx, ny,
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dx, dy, dt,
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dx, dy,
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g,
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gamma,
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theta=1.3,
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@ -67,14 +67,14 @@ class EE2D_KP07_dimsplit (BaseSimulator):
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block_width=16, block_height=8):
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# Call super constructor
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super().__init__(context, \
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nx, ny, \
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dx, dy, 2*dt, \
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super().__init__(context,
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nx, ny,
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dx, dy,
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cfl_scale,
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block_width, block_height)
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self.g = np.float32(g)
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self.gamma = np.float32(gamma)
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self.theta = np.float32(theta)
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self.cfl_scale = cfl_scale
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self.boundary_conditions = boundary_conditions.asCodedInt()
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#Get kernels
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@ -102,7 +102,10 @@ class EE2D_KP07_dimsplit (BaseSimulator):
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2, 2,
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[None, None, None, None])
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self.cfl_data = gpuarray.GPUArray(self.grid_size, dtype=np.float32)
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self.cfl_data.fill(self.dt, stream=self.stream)
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dt_x = np.min(self.dx / (np.abs(hu0/h0) + np.sqrt(gamma*h0)))
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dt_y = np.min(self.dy / (np.abs(hv0/h0) + np.sqrt(gamma*h0)))
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dt = min(dt_x, dt_y)
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self.cfl_data.fill(dt, stream=self.stream)
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def step(self, dt):
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@ -140,4 +143,4 @@ class EE2D_KP07_dimsplit (BaseSimulator):
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def computeDt(self):
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max_dt = gpuarray.min(self.cfl_data, stream=self.stream).get();
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return max_dt*0.5*self.cfl_scale
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return max_dt*0.5
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@ -57,7 +57,7 @@ class FORCE (Simulator.BaseSimulator):
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context,
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h0, hu0, hv0,
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nx, ny,
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dx, dy, dt,
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dx, dy,
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g,
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cfl_scale=0.9,
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boundary_conditions=BoundaryCondition(),
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@ -66,10 +66,10 @@ class FORCE (Simulator.BaseSimulator):
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# Call super constructor
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super().__init__(context,
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nx, ny,
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dx, dy, dt,
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dx, dy,
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cfl_scale,
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block_width, block_height)
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self.g = np.float32(g)
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self.cfl_scale = cfl_scale
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self.boundary_conditions = boundary_conditions.asCodedInt()
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#Get kernels
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@ -96,7 +96,10 @@ class FORCE (Simulator.BaseSimulator):
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1, 1,
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[None, None, None])
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self.cfl_data = gpuarray.GPUArray(self.grid_size, dtype=np.float32)
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self.cfl_data.fill(self.dt, stream=self.stream)
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dt_x = np.min(self.dx / (np.abs(hu0/h0) + np.sqrt(g*h0)))
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dt_y = np.min(self.dy / (np.abs(hv0/h0) + np.sqrt(g*h0)))
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dt = min(dt_x, dt_y)
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self.cfl_data.fill(dt, stream=self.stream)
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def step(self, dt):
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self.kernel.prepared_async_call(self.grid_size, self.block_size, self.stream,
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@ -124,4 +127,4 @@ class FORCE (Simulator.BaseSimulator):
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def computeDt(self):
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max_dt = gpuarray.min(self.cfl_data, stream=self.stream).get();
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return max_dt*0.5*self.cfl_scale
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return max_dt*0.5
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@ -52,7 +52,7 @@ class HLL (Simulator.BaseSimulator):
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context,
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h0, hu0, hv0,
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nx, ny,
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dx, dy, dt,
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dx, dy,
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g,
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cfl_scale=0.9,
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boundary_conditions=BoundaryCondition(),
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@ -61,10 +61,10 @@ class HLL (Simulator.BaseSimulator):
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# Call super constructor
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super().__init__(context,
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nx, ny,
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dx, dy, dt,
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dx, dy,
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cfl_scale,
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block_width, block_height);
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self.g = np.float32(g)
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self.cfl_scale = cfl_scale
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self.boundary_conditions = boundary_conditions.asCodedInt()
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#Get kernels
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@ -91,7 +91,10 @@ class HLL (Simulator.BaseSimulator):
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1, 1,
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[None, None, None])
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self.cfl_data = gpuarray.GPUArray(self.grid_size, dtype=np.float32)
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self.cfl_data.fill(self.dt, stream=self.stream)
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dt_x = np.min(self.dx / (np.abs(hu0/h0) + np.sqrt(g*h0)))
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dt_y = np.min(self.dy / (np.abs(hv0/h0) + np.sqrt(g*h0)))
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dt = min(dt_x, dt_y)
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self.cfl_data.fill(dt, stream=self.stream)
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def step(self, dt):
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self.kernel.prepared_async_call(self.grid_size, self.block_size, self.stream,
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@ -119,4 +122,4 @@ class HLL (Simulator.BaseSimulator):
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def computeDt(self):
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max_dt = gpuarray.min(self.cfl_data, stream=self.stream).get();
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return max_dt*0.5*self.cfl_scale
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return max_dt*0.5
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@ -54,7 +54,7 @@ class HLL2 (Simulator.BaseSimulator):
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context,
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h0, hu0, hv0,
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nx, ny,
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dx, dy, dt,
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dx, dy,
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g,
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theta=1.8,
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cfl_scale=0.9,
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@ -64,7 +64,8 @@ class HLL2 (Simulator.BaseSimulator):
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# Call super constructor
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super().__init__(context,
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nx, ny,
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dx, dy, dt*2,
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dx, dy,
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cfl_scale,
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block_width, block_height);
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self.g = np.float32(g)
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self.theta = np.float32(theta)
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@ -95,7 +96,10 @@ class HLL2 (Simulator.BaseSimulator):
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2, 2,
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[None, None, None])
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self.cfl_data = gpuarray.GPUArray(self.grid_size, dtype=np.float32)
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self.cfl_data.fill(self.dt, stream=self.stream)
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dt_x = np.min(self.dx / (np.abs(hu0/h0) + np.sqrt(g*h0)))
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dt_y = np.min(self.dy / (np.abs(hv0/h0) + np.sqrt(g*h0)))
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dt = min(dt_x, dt_y)
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self.cfl_data.fill(dt, stream=self.stream)
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def step(self, dt):
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self.substepDimsplit(dt*0.5, 0)
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@ -130,4 +134,4 @@ class HLL2 (Simulator.BaseSimulator):
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def computeDt(self):
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max_dt = gpuarray.min(self.cfl_data, stream=self.stream).get();
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return max_dt*0.5*self.cfl_scale
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return max_dt*0.5
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@ -55,7 +55,7 @@ class KP07 (Simulator.BaseSimulator):
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context,
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h0, hu0, hv0,
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nx, ny,
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dx, dy, dt,
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dx, dy,
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g,
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theta=1.3,
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cfl_scale=0.9,
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@ -66,11 +66,11 @@ class KP07 (Simulator.BaseSimulator):
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# Call super constructor
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super().__init__(context,
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nx, ny,
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dx, dy, dt,
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dx, dy,
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cfl_scale,
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block_width, block_height);
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self.g = np.float32(g)
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self.theta = np.float32(theta)
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self.cfl_scale = cfl_scale
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self.order = np.int32(order)
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self.boundary_conditions = boundary_conditions.asCodedInt()
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@ -98,7 +98,10 @@ class KP07 (Simulator.BaseSimulator):
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2, 2,
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[None, None, None])
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self.cfl_data = gpuarray.GPUArray(self.grid_size, dtype=np.float32)
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self.cfl_data.fill(self.dt, stream=self.stream)
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dt_x = np.min(self.dx / (np.abs(hu0/h0) + np.sqrt(g*h0)))
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dt_y = np.min(self.dy / (np.abs(hv0/h0) + np.sqrt(g*h0)))
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dt = min(dt_x, dt_y)
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self.cfl_data.fill(dt, stream=self.stream)
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def step(self, dt):
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@ -140,4 +143,4 @@ class KP07 (Simulator.BaseSimulator):
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def computeDt(self):
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max_dt = gpuarray.min(self.cfl_data, stream=self.stream).get();
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return max_dt*0.5**self.order*self.cfl_scale
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return max_dt*0.5**self.order
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@ -38,7 +38,7 @@ from pycuda import gpuarray
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"""
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Class that solves the SW equations using the dimentionally split KP07 scheme
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"""
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class KP07_dimsplit (Simulator.BaseSimulator):
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class KP07_dimsplit(Simulator.BaseSimulator):
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"""
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Initialization routine
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@ -56,7 +56,7 @@ class KP07_dimsplit (Simulator.BaseSimulator):
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context,
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h0, hu0, hv0,
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nx, ny,
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dx, dy, dt,
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dx, dy,
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g,
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theta=1.3,
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cfl_scale=0.9,
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@ -66,13 +66,13 @@ class KP07_dimsplit (Simulator.BaseSimulator):
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# Call super constructor
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super().__init__(context,
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nx, ny,
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dx, dy, dt*2,
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dx, dy,
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cfl_scale,
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block_width, block_height)
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self.gc_x = 2
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self.gc_y = 2
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self.g = np.float32(g)
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self.theta = np.float32(theta)
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self.cfl_scale = cfl_scale
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self.boundary_conditions = boundary_conditions.asCodedInt()
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#Get kernels
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@ -99,7 +99,10 @@ class KP07_dimsplit (Simulator.BaseSimulator):
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self.gc_x, self.gc_y,
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[None, None, None])
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self.cfl_data = gpuarray.GPUArray(self.grid_size, dtype=np.float32)
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self.cfl_data.fill(self.dt, stream=self.stream)
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dt_x = np.min(self.dx / (np.abs(hu0/h0) + np.sqrt(g*h0)))
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dt_y = np.min(self.dy / (np.abs(hv0/h0) + np.sqrt(g*h0)))
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dt = min(dt_x, dt_y)
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self.cfl_data.fill(dt, stream=self.stream)
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def step(self, dt):
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self.substepDimsplit(dt*0.5, 0)
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@ -135,4 +138,4 @@ class KP07_dimsplit (Simulator.BaseSimulator):
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def computeDt(self):
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max_dt = gpuarray.min(self.cfl_data, stream=self.stream).get();
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return max_dt*0.5*self.cfl_scale
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return max_dt*0.5
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@ -53,7 +53,7 @@ class LxF (Simulator.BaseSimulator):
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context,
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h0, hu0, hv0,
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nx, ny,
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dx, dy, dt,
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dx, dy,
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g,
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cfl_scale=0.9,
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boundary_conditions=BoundaryCondition(),
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@ -62,10 +62,10 @@ class LxF (Simulator.BaseSimulator):
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# Call super constructor
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super().__init__(context,
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nx, ny,
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dx, dy, dt,
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dx, dy,
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cfl_scale,
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block_width, block_height);
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self.g = np.float32(g)
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self.cfl_scale = cfl_scale
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self.boundary_conditions = boundary_conditions.asCodedInt()
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# Get kernels
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@ -92,7 +92,10 @@ class LxF (Simulator.BaseSimulator):
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1, 1,
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[None, None, None])
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self.cfl_data = gpuarray.GPUArray(self.grid_size, dtype=np.float32)
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self.cfl_data.fill(self.dt, stream=self.stream)
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dt_x = np.min(self.dx / (np.abs(hu0/h0) + np.sqrt(g*h0)))
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dt_y = np.min(self.dy / (np.abs(hv0/h0) + np.sqrt(g*h0)))
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dt = min(dt_x, dt_y)
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self.cfl_data.fill(dt, stream=self.stream)
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def step(self, dt):
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self.kernel.prepared_async_call(self.grid_size, self.block_size, self.stream,
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@ -116,4 +119,4 @@ class LxF (Simulator.BaseSimulator):
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def computeDt(self):
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max_dt = gpuarray.min(self.cfl_data, stream=self.stream).get();
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return max_dt*0.5*self.cfl_scale
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return max_dt*0.5
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@ -104,7 +104,8 @@ class BaseSimulator(object):
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def __init__(self,
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context,
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nx, ny,
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dx, dy, dt,
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dx, dy,
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cfl_scale,
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block_width, block_height):
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"""
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Initialization routine
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@ -130,7 +131,7 @@ class BaseSimulator(object):
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self.ny = np.int32(ny)
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self.dx = np.float32(dx)
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self.dy = np.float32(dy)
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self.dt = np.float32(dt)
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self.cfl_scale = cfl_scale
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#Handle autotuning block size
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if (self.context.autotuner):
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@ -168,20 +169,22 @@ class BaseSimulator(object):
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t_end = self.simTime() + t
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dt = None
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while(self.simTime() < t_end):
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if (self.simSteps() % 100 == 0):
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self.dt = self.computeDt()
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dt = self.computeDt()*self.cfl_scale
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# Compute timestep for "this" iteration (i.e., shorten last timestep)
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local_dt = np.float32(min(self.dt, t_end-self.simTime()))
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dt = np.float32(min(dt, t_end-self.simTime()))
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# Stop if end reached (should not happen)
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if (local_dt <= 0.0):
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if (dt <= 0.0):
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self.logger.warning("Timestep size {:d} is less than or equal to zero!".format(self.simSteps()))
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break
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# Step forward in time
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self.step(local_dt)
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self.step(dt)
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#Print info
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print_string = printer.getPrintString(t_end - self.simTime())
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@ -51,7 +51,7 @@ class WAF (Simulator.BaseSimulator):
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context,
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h0, hu0, hv0,
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nx, ny,
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dx, dy, dt,
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dx, dy,
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g,
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cfl_scale=0.9,
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boundary_conditions=BoundaryCondition(),
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@ -60,10 +60,10 @@ class WAF (Simulator.BaseSimulator):
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# Call super constructor
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super().__init__(context,
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nx, ny,
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dx, dy, dt*2,
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dx, dy,
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cfl_scale,
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block_width, block_height);
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self.g = np.float32(g)
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self.cfl_scale = cfl_scale
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self.boundary_conditions = boundary_conditions.asCodedInt()
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#Get kernels
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@ -78,7 +78,7 @@ class WAF (Simulator.BaseSimulator):
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},
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jit_compile_args={})
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self.kernel = module.get_function("WAFKernel")
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self.kernel.prepare("iiffffiiPiPiPiPiPiPi")
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self.kernel.prepare("iiffffiiPiPiPiPiPiPiP")
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#Create data by uploading to device
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self.u0 = Common.ArakawaA2D(self.stream,
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@ -90,7 +90,10 @@ class WAF (Simulator.BaseSimulator):
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2, 2,
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[None, None, None])
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self.cfl_data = gpuarray.GPUArray(self.grid_size, dtype=np.float32)
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self.cfl_data.fill(self.dt, stream=self.stream)
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dt_x = np.min(self.dx / (np.abs(hu0/h0) + np.sqrt(g*h0)))
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dt_y = np.min(self.dy / (np.abs(hv0/h0) + np.sqrt(g*h0)))
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dt = min(dt_x, dt_y)
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self.cfl_data.fill(dt, stream=self.stream)
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def step(self, dt):
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self.substepDimsplit(dt*0.5, substep=0)
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@ -110,7 +113,8 @@ class WAF (Simulator.BaseSimulator):
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self.u0[2].data.gpudata, self.u0[2].data.strides[0],
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self.u1[0].data.gpudata, self.u1[0].data.strides[0],
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self.u1[1].data.gpudata, self.u1[1].data.strides[0],
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self.u1[2].data.gpudata, self.u1[2].data.strides[0])
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self.u1[2].data.gpudata, self.u1[2].data.strides[0],
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self.cfl_data.gpudata)
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self.u0, self.u1 = self.u1, self.u0
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def download(self):
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@ -122,4 +126,4 @@ class WAF (Simulator.BaseSimulator):
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def computeDt(self):
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max_dt = gpuarray.min(self.cfl_data, stream=self.stream).get();
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return max_dt*0.5*self.cfl_scale
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return max_dt*0.5
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