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Removed fixed timestep size

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This commit is contained in:
André R. Brodtkorb 2018-11-15 17:25:01 +01:00
parent ddac53271c
commit 815b4493b5
9 changed files with 79 additions and 50 deletions
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17
GPUSimulators/EE2D_KP07_dimsplit.py
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@ -58,7 +58,7 @@ class EE2D_KP07_dimsplit (BaseSimulator):
context, context,
rho, rho_u, rho_v, E, rho, rho_u, rho_v, E,
nx, ny, nx, ny,
dx, dy, dt, dx, dy,
g, g,
gamma, gamma,
theta=1.3, theta=1.3,
@ -67,14 +67,14 @@ class EE2D_KP07_dimsplit (BaseSimulator):
block_width=16, block_height=8): block_width=16, block_height=8):
# Call super constructor # Call super constructor
super().__init__(context, \ super().__init__(context,
nx, ny, \ nx, ny,
dx, dy, 2*dt, \ dx, dy,
cfl_scale,
block_width, block_height) block_width, block_height)
self.g = np.float32(g) self.g = np.float32(g)
self.gamma = np.float32(gamma) self.gamma = np.float32(gamma)
self.theta = np.float32(theta) self.theta = np.float32(theta)
self.cfl_scale = cfl_scale
self.boundary_conditions = boundary_conditions.asCodedInt() self.boundary_conditions = boundary_conditions.asCodedInt()
#Get kernels #Get kernels
@ -102,7 +102,10 @@ class EE2D_KP07_dimsplit (BaseSimulator):
2, 2, 2, 2,
[None, None, None, None]) [None, None, None, None])
self.cfl_data = gpuarray.GPUArray(self.grid_size, dtype=np.float32) self.cfl_data = gpuarray.GPUArray(self.grid_size, dtype=np.float32)
self.cfl_data.fill(self.dt, stream=self.stream) dt_x = np.min(self.dx / (np.abs(hu0/h0) + np.sqrt(gamma*h0)))
dt_y = np.min(self.dy / (np.abs(hv0/h0) + np.sqrt(gamma*h0)))
dt = min(dt_x, dt_y)
self.cfl_data.fill(dt, stream=self.stream)
def step(self, dt): def step(self, dt):
@ -140,4 +143,4 @@ class EE2D_KP07_dimsplit (BaseSimulator):
def computeDt(self): def computeDt(self):
max_dt = gpuarray.min(self.cfl_data, stream=self.stream).get(); max_dt = gpuarray.min(self.cfl_data, stream=self.stream).get();
return max_dt*0.5*self.cfl_scale return max_dt*0.5

13
GPUSimulators/FORCE.py
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@ -57,7 +57,7 @@ class FORCE (Simulator.BaseSimulator):
context, context,
h0, hu0, hv0, h0, hu0, hv0,
nx, ny, nx, ny,
dx, dy, dt, dx, dy,
g, g,
cfl_scale=0.9, cfl_scale=0.9,
boundary_conditions=BoundaryCondition(), boundary_conditions=BoundaryCondition(),
@ -66,10 +66,10 @@ class FORCE (Simulator.BaseSimulator):
# Call super constructor # Call super constructor
super().__init__(context, super().__init__(context,
nx, ny, nx, ny,
dx, dy, dt, dx, dy,
cfl_scale,
block_width, block_height) block_width, block_height)
self.g = np.float32(g) self.g = np.float32(g)
self.cfl_scale = cfl_scale
self.boundary_conditions = boundary_conditions.asCodedInt() self.boundary_conditions = boundary_conditions.asCodedInt()
#Get kernels #Get kernels
@ -96,7 +96,10 @@ class FORCE (Simulator.BaseSimulator):
1, 1, 1, 1,
[None, None, None]) [None, None, None])
self.cfl_data = gpuarray.GPUArray(self.grid_size, dtype=np.float32) self.cfl_data = gpuarray.GPUArray(self.grid_size, dtype=np.float32)
self.cfl_data.fill(self.dt, stream=self.stream) dt_x = np.min(self.dx / (np.abs(hu0/h0) + np.sqrt(g*h0)))
dt_y = np.min(self.dy / (np.abs(hv0/h0) + np.sqrt(g*h0)))
dt = min(dt_x, dt_y)
self.cfl_data.fill(dt, stream=self.stream)
def step(self, dt): def step(self, dt):
self.kernel.prepared_async_call(self.grid_size, self.block_size, self.stream, self.kernel.prepared_async_call(self.grid_size, self.block_size, self.stream,
@ -124,4 +127,4 @@ class FORCE (Simulator.BaseSimulator):
def computeDt(self): def computeDt(self):
max_dt = gpuarray.min(self.cfl_data, stream=self.stream).get(); max_dt = gpuarray.min(self.cfl_data, stream=self.stream).get();
return max_dt*0.5*self.cfl_scale return max_dt*0.5

13
GPUSimulators/HLL.py
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@ -52,7 +52,7 @@ class HLL (Simulator.BaseSimulator):
context, context,
h0, hu0, hv0, h0, hu0, hv0,
nx, ny, nx, ny,
dx, dy, dt, dx, dy,
g, g,
cfl_scale=0.9, cfl_scale=0.9,
boundary_conditions=BoundaryCondition(), boundary_conditions=BoundaryCondition(),
@ -61,10 +61,10 @@ class HLL (Simulator.BaseSimulator):
# Call super constructor # Call super constructor
super().__init__(context, super().__init__(context,
nx, ny, nx, ny,
dx, dy, dt, dx, dy,
cfl_scale,
block_width, block_height); block_width, block_height);
self.g = np.float32(g) self.g = np.float32(g)
self.cfl_scale = cfl_scale
self.boundary_conditions = boundary_conditions.asCodedInt() self.boundary_conditions = boundary_conditions.asCodedInt()
#Get kernels #Get kernels
@ -91,7 +91,10 @@ class HLL (Simulator.BaseSimulator):
1, 1, 1, 1,
[None, None, None]) [None, None, None])
self.cfl_data = gpuarray.GPUArray(self.grid_size, dtype=np.float32) self.cfl_data = gpuarray.GPUArray(self.grid_size, dtype=np.float32)
self.cfl_data.fill(self.dt, stream=self.stream) dt_x = np.min(self.dx / (np.abs(hu0/h0) + np.sqrt(g*h0)))
dt_y = np.min(self.dy / (np.abs(hv0/h0) + np.sqrt(g*h0)))
dt = min(dt_x, dt_y)
self.cfl_data.fill(dt, stream=self.stream)
def step(self, dt): def step(self, dt):
self.kernel.prepared_async_call(self.grid_size, self.block_size, self.stream, self.kernel.prepared_async_call(self.grid_size, self.block_size, self.stream,
@ -119,4 +122,4 @@ class HLL (Simulator.BaseSimulator):
def computeDt(self): def computeDt(self):
max_dt = gpuarray.min(self.cfl_data, stream=self.stream).get(); max_dt = gpuarray.min(self.cfl_data, stream=self.stream).get();
return max_dt*0.5*self.cfl_scale return max_dt*0.5

12
GPUSimulators/HLL2.py
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@ -54,7 +54,7 @@ class HLL2 (Simulator.BaseSimulator):
context, context,
h0, hu0, hv0, h0, hu0, hv0,
nx, ny, nx, ny,
dx, dy, dt, dx, dy,
g, g,
theta=1.8, theta=1.8,
cfl_scale=0.9, cfl_scale=0.9,
@ -64,7 +64,8 @@ class HLL2 (Simulator.BaseSimulator):
# Call super constructor # Call super constructor
super().__init__(context, super().__init__(context,
nx, ny, nx, ny,
dx, dy, dt*2, dx, dy,
cfl_scale,
block_width, block_height); block_width, block_height);
self.g = np.float32(g) self.g = np.float32(g)
self.theta = np.float32(theta) self.theta = np.float32(theta)
@ -95,7 +96,10 @@ class HLL2 (Simulator.BaseSimulator):
2, 2, 2, 2,
[None, None, None]) [None, None, None])
self.cfl_data = gpuarray.GPUArray(self.grid_size, dtype=np.float32) self.cfl_data = gpuarray.GPUArray(self.grid_size, dtype=np.float32)
self.cfl_data.fill(self.dt, stream=self.stream) dt_x = np.min(self.dx / (np.abs(hu0/h0) + np.sqrt(g*h0)))
dt_y = np.min(self.dy / (np.abs(hv0/h0) + np.sqrt(g*h0)))
dt = min(dt_x, dt_y)
self.cfl_data.fill(dt, stream=self.stream)
def step(self, dt): def step(self, dt):
self.substepDimsplit(dt*0.5, 0) self.substepDimsplit(dt*0.5, 0)
@ -130,4 +134,4 @@ class HLL2 (Simulator.BaseSimulator):
def computeDt(self): def computeDt(self):
max_dt = gpuarray.min(self.cfl_data, stream=self.stream).get(); max_dt = gpuarray.min(self.cfl_data, stream=self.stream).get();
return max_dt*0.5*self.cfl_scale return max_dt*0.5

13
GPUSimulators/KP07.py
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@ -55,7 +55,7 @@ class KP07 (Simulator.BaseSimulator):
context, context,
h0, hu0, hv0, h0, hu0, hv0,
nx, ny, nx, ny,
dx, dy, dt, dx, dy,
g, g,
theta=1.3, theta=1.3,
cfl_scale=0.9, cfl_scale=0.9,
@ -66,11 +66,11 @@ class KP07 (Simulator.BaseSimulator):
# Call super constructor # Call super constructor
super().__init__(context, super().__init__(context,
nx, ny, nx, ny,
dx, dy, dt, dx, dy,
cfl_scale,
block_width, block_height); block_width, block_height);
self.g = np.float32(g) self.g = np.float32(g)
self.theta = np.float32(theta) self.theta = np.float32(theta)
self.cfl_scale = cfl_scale
self.order = np.int32(order) self.order = np.int32(order)
self.boundary_conditions = boundary_conditions.asCodedInt() self.boundary_conditions = boundary_conditions.asCodedInt()
@ -98,7 +98,10 @@ class KP07 (Simulator.BaseSimulator):
2, 2, 2, 2,
[None, None, None]) [None, None, None])
self.cfl_data = gpuarray.GPUArray(self.grid_size, dtype=np.float32) self.cfl_data = gpuarray.GPUArray(self.grid_size, dtype=np.float32)
self.cfl_data.fill(self.dt, stream=self.stream) dt_x = np.min(self.dx / (np.abs(hu0/h0) + np.sqrt(g*h0)))
dt_y = np.min(self.dy / (np.abs(hv0/h0) + np.sqrt(g*h0)))
dt = min(dt_x, dt_y)
self.cfl_data.fill(dt, stream=self.stream)
def step(self, dt): def step(self, dt):
@ -140,4 +143,4 @@ class KP07 (Simulator.BaseSimulator):
def computeDt(self): def computeDt(self):
max_dt = gpuarray.min(self.cfl_data, stream=self.stream).get(); max_dt = gpuarray.min(self.cfl_data, stream=self.stream).get();
return max_dt*0.5**self.order*self.cfl_scale return max_dt*0.5**self.order

15
GPUSimulators/KP07_dimsplit.py
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@ -38,7 +38,7 @@ from pycuda import gpuarray
""" """
Class that solves the SW equations using the dimentionally split KP07 scheme Class that solves the SW equations using the dimentionally split KP07 scheme
""" """
class KP07_dimsplit (Simulator.BaseSimulator): class KP07_dimsplit(Simulator.BaseSimulator):
""" """
Initialization routine Initialization routine
@ -56,7 +56,7 @@ class KP07_dimsplit (Simulator.BaseSimulator):
context, context,
h0, hu0, hv0, h0, hu0, hv0,
nx, ny, nx, ny,
dx, dy, dt, dx, dy,
g, g,
theta=1.3, theta=1.3,
cfl_scale=0.9, cfl_scale=0.9,
@ -66,13 +66,13 @@ class KP07_dimsplit (Simulator.BaseSimulator):
# Call super constructor # Call super constructor
super().__init__(context, super().__init__(context,
nx, ny, nx, ny,
dx, dy, dt*2, dx, dy,
cfl_scale,
block_width, block_height) block_width, block_height)
self.gc_x = 2 self.gc_x = 2
self.gc_y = 2 self.gc_y = 2
self.g = np.float32(g) self.g = np.float32(g)
self.theta = np.float32(theta) self.theta = np.float32(theta)
self.cfl_scale = cfl_scale
self.boundary_conditions = boundary_conditions.asCodedInt() self.boundary_conditions = boundary_conditions.asCodedInt()
#Get kernels #Get kernels
@ -99,7 +99,10 @@ class KP07_dimsplit (Simulator.BaseSimulator):
self.gc_x, self.gc_y, self.gc_x, self.gc_y,
[None, None, None]) [None, None, None])
self.cfl_data = gpuarray.GPUArray(self.grid_size, dtype=np.float32) self.cfl_data = gpuarray.GPUArray(self.grid_size, dtype=np.float32)
self.cfl_data.fill(self.dt, stream=self.stream) dt_x = np.min(self.dx / (np.abs(hu0/h0) + np.sqrt(g*h0)))
dt_y = np.min(self.dy / (np.abs(hv0/h0) + np.sqrt(g*h0)))
dt = min(dt_x, dt_y)
self.cfl_data.fill(dt, stream=self.stream)
def step(self, dt): def step(self, dt):
self.substepDimsplit(dt*0.5, 0) self.substepDimsplit(dt*0.5, 0)
@ -135,4 +138,4 @@ class KP07_dimsplit (Simulator.BaseSimulator):
def computeDt(self): def computeDt(self):
max_dt = gpuarray.min(self.cfl_data, stream=self.stream).get(); max_dt = gpuarray.min(self.cfl_data, stream=self.stream).get();
return max_dt*0.5*self.cfl_scale return max_dt*0.5

13
GPUSimulators/LxF.py
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@ -53,7 +53,7 @@ class LxF (Simulator.BaseSimulator):
context, context,
h0, hu0, hv0, h0, hu0, hv0,
nx, ny, nx, ny,
dx, dy, dt, dx, dy,
g, g,
cfl_scale=0.9, cfl_scale=0.9,
boundary_conditions=BoundaryCondition(), boundary_conditions=BoundaryCondition(),
@ -62,10 +62,10 @@ class LxF (Simulator.BaseSimulator):
# Call super constructor # Call super constructor
super().__init__(context, super().__init__(context,
nx, ny, nx, ny,
dx, dy, dt, dx, dy,
cfl_scale,
block_width, block_height); block_width, block_height);
self.g = np.float32(g) self.g = np.float32(g)
self.cfl_scale = cfl_scale
self.boundary_conditions = boundary_conditions.asCodedInt() self.boundary_conditions = boundary_conditions.asCodedInt()
# Get kernels # Get kernels
@ -92,7 +92,10 @@ class LxF (Simulator.BaseSimulator):
1, 1, 1, 1,
[None, None, None]) [None, None, None])
self.cfl_data = gpuarray.GPUArray(self.grid_size, dtype=np.float32) self.cfl_data = gpuarray.GPUArray(self.grid_size, dtype=np.float32)
self.cfl_data.fill(self.dt, stream=self.stream) dt_x = np.min(self.dx / (np.abs(hu0/h0) + np.sqrt(g*h0)))
dt_y = np.min(self.dy / (np.abs(hv0/h0) + np.sqrt(g*h0)))
dt = min(dt_x, dt_y)
self.cfl_data.fill(dt, stream=self.stream)
def step(self, dt): def step(self, dt):
self.kernel.prepared_async_call(self.grid_size, self.block_size, self.stream, self.kernel.prepared_async_call(self.grid_size, self.block_size, self.stream,
@ -116,4 +119,4 @@ class LxF (Simulator.BaseSimulator):
def computeDt(self): def computeDt(self):
max_dt = gpuarray.min(self.cfl_data, stream=self.stream).get(); max_dt = gpuarray.min(self.cfl_data, stream=self.stream).get();
return max_dt*0.5*self.cfl_scale return max_dt*0.5

15
GPUSimulators/Simulator.py
View File

@ -104,7 +104,8 @@ class BaseSimulator(object):
def __init__(self, def __init__(self,
context, context,
nx, ny, nx, ny,
dx, dy, dt, dx, dy,
cfl_scale,
block_width, block_height): block_width, block_height):
""" """
Initialization routine Initialization routine
@ -130,7 +131,7 @@ class BaseSimulator(object):
self.ny = np.int32(ny) self.ny = np.int32(ny)
self.dx = np.float32(dx) self.dx = np.float32(dx)
self.dy = np.float32(dy) self.dy = np.float32(dy)
self.dt = np.float32(dt) self.cfl_scale = cfl_scale
#Handle autotuning block size #Handle autotuning block size
if (self.context.autotuner): if (self.context.autotuner):
@ -168,20 +169,22 @@ class BaseSimulator(object):
t_end = self.simTime() + t t_end = self.simTime() + t
dt = None
while(self.simTime() < t_end): while(self.simTime() < t_end):
if (self.simSteps() % 100 == 0): if (self.simSteps() % 100 == 0):
self.dt = self.computeDt() dt = self.computeDt()*self.cfl_scale
# Compute timestep for "this" iteration (i.e., shorten last timestep) # Compute timestep for "this" iteration (i.e., shorten last timestep)
local_dt = np.float32(min(self.dt, t_end-self.simTime())) dt = np.float32(min(dt, t_end-self.simTime()))
# Stop if end reached (should not happen) # Stop if end reached (should not happen)
if (local_dt <= 0.0): if (dt <= 0.0):
self.logger.warning("Timestep size {:d} is less than or equal to zero!".format(self.simSteps())) self.logger.warning("Timestep size {:d} is less than or equal to zero!".format(self.simSteps()))
break break
# Step forward in time # Step forward in time
self.step(local_dt) self.step(dt)
#Print info #Print info
print_string = printer.getPrintString(t_end - self.simTime()) print_string = printer.getPrintString(t_end - self.simTime())

18
GPUSimulators/WAF.py
View File

@ -51,7 +51,7 @@ class WAF (Simulator.BaseSimulator):
context, context,
h0, hu0, hv0, h0, hu0, hv0,
nx, ny, nx, ny,
dx, dy, dt, dx, dy,
g, g,
cfl_scale=0.9, cfl_scale=0.9,
boundary_conditions=BoundaryCondition(), boundary_conditions=BoundaryCondition(),
@ -60,10 +60,10 @@ class WAF (Simulator.BaseSimulator):
# Call super constructor # Call super constructor
super().__init__(context, super().__init__(context,
nx, ny, nx, ny,
dx, dy, dt*2, dx, dy,
cfl_scale,
block_width, block_height); block_width, block_height);
self.g = np.float32(g) self.g = np.float32(g)
self.cfl_scale = cfl_scale
self.boundary_conditions = boundary_conditions.asCodedInt() self.boundary_conditions = boundary_conditions.asCodedInt()
#Get kernels #Get kernels
@ -78,7 +78,7 @@ class WAF (Simulator.BaseSimulator):
}, },
jit_compile_args={}) jit_compile_args={})
self.kernel = module.get_function("WAFKernel") self.kernel = module.get_function("WAFKernel")
self.kernel.prepare("iiffffiiPiPiPiPiPiPi") self.kernel.prepare("iiffffiiPiPiPiPiPiPiP")
#Create data by uploading to device #Create data by uploading to device
self.u0 = Common.ArakawaA2D(self.stream, self.u0 = Common.ArakawaA2D(self.stream,
@ -90,7 +90,10 @@ class WAF (Simulator.BaseSimulator):
2, 2, 2, 2,
[None, None, None]) [None, None, None])
self.cfl_data = gpuarray.GPUArray(self.grid_size, dtype=np.float32) self.cfl_data = gpuarray.GPUArray(self.grid_size, dtype=np.float32)
self.cfl_data.fill(self.dt, stream=self.stream) dt_x = np.min(self.dx / (np.abs(hu0/h0) + np.sqrt(g*h0)))
dt_y = np.min(self.dy / (np.abs(hv0/h0) + np.sqrt(g*h0)))
dt = min(dt_x, dt_y)
self.cfl_data.fill(dt, stream=self.stream)
def step(self, dt): def step(self, dt):
self.substepDimsplit(dt*0.5, substep=0) self.substepDimsplit(dt*0.5, substep=0)
@ -110,7 +113,8 @@ class WAF (Simulator.BaseSimulator):
self.u0[2].data.gpudata, self.u0[2].data.strides[0], self.u0[2].data.gpudata, self.u0[2].data.strides[0],
self.u1[0].data.gpudata, self.u1[0].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[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.u0, self.u1 = self.u1, self.u0
def download(self): def download(self):
@ -122,4 +126,4 @@ class WAF (Simulator.BaseSimulator):
def computeDt(self): def computeDt(self):
max_dt = gpuarray.min(self.cfl_data, stream=self.stream).get(); max_dt = gpuarray.min(self.cfl_data, stream=self.stream).get();
return max_dt*0.5*self.cfl_scale return max_dt*0.5