mirror of
https://github.com/smyalygames/FiniteVolumeGPU_HIP.git
synced 2025-07-08 00:21:00 +02:00
re-write EE2D_KP07_dimsplit.py with hip-python
This commit is contained in:
Hicham Agueny
parent
41e496634e
commit
9bf115ddfd
@ -23,9 +23,10 @@ along with this program. If not, see <http://www.gnu.org/licenses/>.
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from GPUSimulators import Simulator, Common
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from GPUSimulators.Simulator import BaseSimulator, BoundaryCondition
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import numpy as np
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import ctypes
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from pycuda import gpuarray
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#from pycuda import gpuarray
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from hip import hip,hiprtc
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@ -54,6 +55,21 @@ class EE2D_KP07_dimsplit (BaseSimulator):
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gamma: Gas constant
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p: pressure
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"""
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def hip_check(call_result):
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err = call_result[0]
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result = call_result[1:]
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if len(result) == 1:
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result = result[0]
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if isinstance(err, hip.hipError_t) and err != hip.hipError_t.hipSuccess:
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raise RuntimeError(str(err))
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elif (
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isinstance(err, hiprtc.hiprtcResult)
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and err != hiprtc.hiprtcResult.HIPRTC_SUCCESS
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):
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raise RuntimeError(str(err))
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return result
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def __init__(self,
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context,
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rho, rho_u, rho_v, E,
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@ -79,20 +95,45 @@ class EE2D_KP07_dimsplit (BaseSimulator):
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self.theta = np.float32(theta)
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#Get kernels
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module = context.get_module("cuda/EE2D_KP07_dimsplit.cu",
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defines={
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'BLOCK_WIDTH': self.block_size[0],
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'BLOCK_HEIGHT': self.block_size[1]
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},
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compile_args={
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'no_extern_c': True,
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'options': ["--use_fast_math"],
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},
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jit_compile_args={})
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self.kernel = module.get_function("KP07DimsplitKernel")
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self.kernel.prepare("iiffffffiiPiPiPiPiPiPiPiPiPiiii")
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#module = context.get_module("cuda/EE2D_KP07_dimsplit.cu",
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# defines={
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# 'BLOCK_WIDTH': self.block_size[0],
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# 'BLOCK_HEIGHT': self.block_size[1]
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# },
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# compile_args={
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# 'no_extern_c': True,
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# 'options': ["--use_fast_math"],
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# },
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# jit_compile_args={})
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#self.kernel = module.get_function("KP07DimsplitKernel")
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#self.kernel.prepare("iiffffffiiPiPiPiPiPiPiPiPiPiiii")
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#
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kernel_file_path = os.path.abspath(os.path.join('cuda', 'EE2D_KP07_dimsplit.cu'))
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with open(kernel_file_path, 'r') as file:
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kernel_source = file.read()
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prog = hip_check(hiprtc.hiprtcCreateProgram(kernel_source.encode(), b"KP07DimsplitKernel", 0, [], []))
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props = hip.hipDeviceProp_t()
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hip_check(hip.hipGetDeviceProperties(props,0))
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arch = props.gcnArchName
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print(f"Compiling kernel for {arch}")
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cflags = [b"--offload-arch="+arch]
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err, = hiprtc.hiprtcCompileProgram(prog, len(cflags), cflags)
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if err != hiprtc.hiprtcResult.HIPRTC_SUCCESS:
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log_size = hip_check(hiprtc.hiprtcGetProgramLogSize(prog))
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log = bytearray(log_size)
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hip_check(hiprtc.hiprtcGetProgramLog(prog, log))
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raise RuntimeError(log.decode())
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code_size = hip_check(hiprtc.hiprtcGetCodeSize(prog))
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code = bytearray(code_size)
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hip_check(hiprtc.hiprtcGetCode(prog, code))
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module = hip_check(hip.hipModuleLoadData(code))
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kernel = hip_check(hip.hipModuleGetFunction(module, b"KP07DimsplitKernel"))
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#Create data by uploading to device
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self.u0 = Common.ArakawaA2D(self.stream,
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nx, ny,
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@ -102,7 +143,13 @@ class EE2D_KP07_dimsplit (BaseSimulator):
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nx, ny,
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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 = gpuarray.GPUArray(self.grid_size, dtype=np.float32)
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# init device array cfl_data
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data_h = np.empty(self.grid_size, dtype=np.float32)
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num_bytes = data_h.size * data_h.itemsize
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self.cfl_data = hip_check(hip.hipMalloc(num_bytes)).configure(
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typestr="float32",shape=self.grid_size)
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dt_x = np.min(self.dx / (np.abs(rho_u/rho) + np.sqrt(gamma*rho)))
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dt_y = np.min(self.dy / (np.abs(rho_v/rho) + np.sqrt(gamma*rho)))
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self.dt = min(dt_x, dt_y)
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@ -116,25 +163,65 @@ class EE2D_KP07_dimsplit (BaseSimulator):
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if external and internal:
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#print("COMPLETE DOMAIN (dt=" + str(dt) + ")")
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self.kernel.prepared_async_call(self.grid_size, self.block_size, self.stream,
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self.nx, self.ny,
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self.dx, self.dy, dt,
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self.g,
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self.gamma,
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self.theta,
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substep,
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self.boundary_conditions,
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self.u0[0].data.gpudata, self.u0[0].data.strides[0],
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self.u0[1].data.gpudata, self.u0[1].data.strides[0],
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self.u0[2].data.gpudata, self.u0[2].data.strides[0],
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self.u0[3].data.gpudata, self.u0[3].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[3].data.gpudata, self.u1[3].data.strides[0],
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self.cfl_data.gpudata,
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0, 0,
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self.nx, self.ny)
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# self.kernel.prepared_async_call(self.grid_size, self.block_size, self.stream,
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# self.nx, self.ny,
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# self.dx, self.dy, dt,
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# self.g,
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# self.gamma,
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# self.theta,
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# substep,
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# self.boundary_conditions,
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# self.u0[0].data.gpudata, self.u0[0].data.strides[0],
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# self.u0[1].data.gpudata, self.u0[1].data.strides[0],
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# self.u0[2].data.gpudata, self.u0[2].data.strides[0],
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# self.u0[3].data.gpudata, self.u0[3].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[3].data.gpudata, self.u1[3].data.strides[0],
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# self.cfl_data.gpudata,
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# 0, 0,
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# self.nx, self.ny)
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#launch kernel
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hip_check(
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hip.hipModuleLaunchKernel(
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kernel,
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*self.grid_size,
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*self.block_size,
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sharedMemBytes=0,
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stream=self.stream,
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kernelParams=None,
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extra=( # pass kernel's arguments
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ctypes.c_int(self.nx), ctypes.c_int(self.ny),
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ctypes.c_float(self.dx), ctypes.c_float(self.dy), ctypes.c_float(self.dt),
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ctypes.c_float(self.g),
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ctypes.c_float(self.gamma),
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ctypes.c_float(self.theta),
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ctypes.c_int(substep),
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ctypes.c_int(self.boundary_conditions),
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ctypes.c_float(self.u0[0].data), ctypes.c_float(self.u0[0].data.strides[0]),
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ctypes.c_float(self.u0[1].data), ctypes.c_float(self.u0[1].data.strides[0]),
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ctypes.c_float(self.u0[2].data), ctypes.c_float(self.u0[2].data.strides[0]),
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ctypes.c_float(self.u0[3].data), ctypes.c_float(self.u0[3].data.strides[0]),
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ctypes.c_float(self.u1[0].data), ctypes.c_float(self.u1[0].data.strides[0]),
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ctypes.c_float(self.u1[1].data), ctypes.c_float(self.u1[1].data.strides[0]),
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ctypes.c_float(self.u1[2].data), ctypes.c_float(self.u1[2].data.strides[0]),
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ctypes.c_float(self.u1[3].data), ctypes.c_float(self.u1[3].data.strides[0]),
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self.cfl_data,
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0, 0,
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ctypes.c_int(self.nx), ctypes.c_int(self.ny)
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)
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)
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)
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hip_check(hip.hipDeviceSynchronize())
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hip_check(hip.hipModuleUnload(module))
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hip_check(hip.hipFree(cfl_data))
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print("--External & Internal: Launching Kernel is ok")
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return
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if external and not internal:
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@ -147,96 +234,231 @@ class EE2D_KP07_dimsplit (BaseSimulator):
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# NORTH
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# (x0, y0) x (x1, y1)
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# (0, ny-y_halo) x (nx, ny)
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self.kernel.prepared_async_call(ns_grid_size, self.block_size, self.stream,
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self.nx, self.ny,
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self.dx, self.dy, dt,
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self.g,
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self.gamma,
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self.theta,
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substep,
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self.boundary_conditions,
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self.u0[0].data.gpudata, self.u0[0].data.strides[0],
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self.u0[1].data.gpudata, self.u0[1].data.strides[0],
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self.u0[2].data.gpudata, self.u0[2].data.strides[0],
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self.u0[3].data.gpudata, self.u0[3].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[3].data.gpudata, self.u1[3].data.strides[0],
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self.cfl_data.gpudata,
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0, self.ny - int(self.u0[0].y_halo),
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self.nx, self.ny)
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# self.kernel.prepared_async_call(ns_grid_size, self.block_size, self.stream,
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# self.nx, self.ny,
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# self.dx, self.dy, dt,
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# self.g,
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# self.gamma,
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# self.theta,
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# substep,
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# self.boundary_conditions,
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# self.u0[0].data.gpudata, self.u0[0].data.strides[0],
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# self.u0[1].data.gpudata, self.u0[1].data.strides[0],
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# self.u0[2].data.gpudata, self.u0[2].data.strides[0],
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# self.u0[3].data.gpudata, self.u0[3].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[3].data.gpudata, self.u1[3].data.strides[0],
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# self.cfl_data.gpudata,
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# 0, self.ny - int(self.u0[0].y_halo),
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# self.nx, self.ny)
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hip_check(
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hip.hipModuleLaunchKernel(
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kernel,
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*ns_grid_size,
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*self.block_size,
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sharedMemBytes=0,
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stream=self.stream,
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kernelParams=None,
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extra=( # pass kernel's arguments
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ctypes.c_int(self.nx), ctypes.c_int(self.ny),
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ctypes.c_float(self.dx), ctypes.c_float(self.dy), ctypes.c_float(self.dt),
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ctypes.c_float(self.g),
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ctypes.c_float(self.gamma),
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ctypes.c_float(self.theta),
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ctypes.c_int(substep),
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ctypes.c_int(self.boundary_conditions),
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ctypes.c_float(self.u0[0].data), ctypes.c_float(self.u0[0].data.strides[0]),
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ctypes.c_float(self.u0[1].data), ctypes.c_float(self.u0[1].data.strides[0]),
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ctypes.c_float(self.u0[2].data), ctypes.c_float(self.u0[2].data.strides[0]),
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ctypes.c_float(self.u0[3].data), ctypes.c_float(self.u0[3].data.strides[0]),
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ctypes.c_float(self.u1[0].data), ctypes.c_float(self.u1[0].data.strides[0]),
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ctypes.c_float(self.u1[1].data), ctypes.c_float(self.u1[1].data.strides[0]),
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ctypes.c_float(self.u1[2].data), ctypes.c_float(self.u1[2].data.strides[0]),
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ctypes.c_float(self.u1[3].data), ctypes.c_float(self.u1[3].data.strides[0]),
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self.cfl_data,
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0, ctypes.c_int(self.ny) - ctypes.c_int(self.u0[0].y_halo),
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ctypes.c_int(self.nx), ctypes.c_int(self.ny)
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)
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)
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)
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# SOUTH
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# (x0, y0) x (x1, y1)
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# (0, 0) x (nx, y_halo)
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self.kernel.prepared_async_call(ns_grid_size, self.block_size, self.stream,
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self.nx, self.ny,
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self.dx, self.dy, dt,
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self.g,
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self.gamma,
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self.theta,
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substep,
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self.boundary_conditions,
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self.u0[0].data.gpudata, self.u0[0].data.strides[0],
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self.u0[1].data.gpudata, self.u0[1].data.strides[0],
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self.u0[2].data.gpudata, self.u0[2].data.strides[0],
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self.u0[3].data.gpudata, self.u0[3].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[3].data.gpudata, self.u1[3].data.strides[0],
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self.cfl_data.gpudata,
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0, 0,
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self.nx, int(self.u0[0].y_halo))
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# self.kernel.prepared_async_call(ns_grid_size, self.block_size, self.stream,
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# self.nx, self.ny,
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# self.dx, self.dy, dt,
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# self.g,
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# self.gamma,
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# self.theta,
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# substep,
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# self.boundary_conditions,
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# self.u0[0].data.gpudata, self.u0[0].data.strides[0],
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# self.u0[1].data.gpudata, self.u0[1].data.strides[0],
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# self.u0[2].data.gpudata, self.u0[2].data.strides[0],
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# self.u0[3].data.gpudata, self.u0[3].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[3].data.gpudata, self.u1[3].data.strides[0],
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# self.cfl_data.gpudata,
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# 0, 0,
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# self.nx, int(self.u0[0].y_halo))
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hip_check(
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hip.hipModuleLaunchKernel(
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kernel,
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*ns_grid_size,
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*self.block_size,
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sharedMemBytes=0,
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stream=self.stream,
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kernelParams=None,
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extra=( # pass kernel's arguments
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ctypes.c_int(self.nx), ctypes.c_int(self.ny),
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ctypes.c_float(self.dx), ctypes.c_float(self.dy), ctypes.c_float(self.dt),
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ctypes.c_float(self.g),
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ctypes.c_float(self.gamma),
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ctypes.c_float(self.theta),
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ctypes.c_int(substep),
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ctypes.c_int(self.boundary_conditions),
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ctypes.c_float(self.u0[0].data), ctypes.c_float(self.u0[0].data.strides[0]),
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ctypes.c_float(self.u0[1].data), ctypes.c_float(self.u0[1].data.strides[0]),
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ctypes.c_float(self.u0[2].data), ctypes.c_float(self.u0[2].data.strides[0]),
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ctypes.c_float(self.u0[3].data), ctypes.c_float(self.u0[3].data.strides[0]),
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ctypes.c_float(self.u1[0].data), ctypes.c_float(self.u1[0].data.strides[0]),
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ctypes.c_float(self.u1[1].data), ctypes.c_float(self.u1[1].data.strides[0]),
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ctypes.c_float(self.u1[2].data), ctypes.c_float(self.u1[2].data.strides[0]),
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ctypes.c_float(self.u1[3].data), ctypes.c_float(self.u1[3].data.strides[0]),
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self.cfl_data,
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0, 0,
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ctypes.c_int(self.nx), ctypes.c_int(self.u0[0].y_halo)
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)
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)
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)
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we_grid_size = (1, self.grid_size[1])
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# WEST
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# (x0, y0) x (x1, y1)
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# (0, 0) x (x_halo, ny)
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self.kernel.prepared_async_call(we_grid_size, self.block_size, self.stream,
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self.nx, self.ny,
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self.dx, self.dy, dt,
|
||||
self.g,
|
||||
self.gamma,
|
||||
self.theta,
|
||||
substep,
|
||||
self.boundary_conditions,
|
||||
self.u0[0].data.gpudata, self.u0[0].data.strides[0],
|
||||
self.u0[1].data.gpudata, self.u0[1].data.strides[0],
|
||||
self.u0[2].data.gpudata, self.u0[2].data.strides[0],
|
||||
self.u0[3].data.gpudata, self.u0[3].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[3].data.gpudata, self.u1[3].data.strides[0],
|
||||
self.cfl_data.gpudata,
|
||||
0, 0,
|
||||
int(self.u0[0].x_halo), self.ny)
|
||||
# self.kernel.prepared_async_call(we_grid_size, self.block_size, self.stream,
|
||||
# self.nx, self.ny,
|
||||
# self.dx, self.dy, dt,
|
||||
# self.g,
|
||||
# self.gamma,
|
||||
# self.theta,
|
||||
# substep,
|
||||
# self.boundary_conditions,
|
||||
# self.u0[0].data.gpudata, self.u0[0].data.strides[0],
|
||||
# self.u0[1].data.gpudata, self.u0[1].data.strides[0],
|
||||
# self.u0[2].data.gpudata, self.u0[2].data.strides[0],
|
||||
# self.u0[3].data.gpudata, self.u0[3].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[3].data.gpudata, self.u1[3].data.strides[0],
|
||||
# self.cfl_data.gpudata,
|
||||
# 0, 0,
|
||||
# int(self.u0[0].x_halo), self.ny)
|
||||
|
||||
hip_check(
|
||||
hip.hipModuleLaunchKernel(
|
||||
kernel,
|
||||
*we_grid_size,
|
||||
*self.block_size,
|
||||
sharedMemBytes=0,
|
||||
stream=self.stream,
|
||||
kernelParams=None,
|
||||
extra=( # pass kernel's arguments
|
||||
ctypes.c_int(self.nx), ctypes.c_int(self.ny),
|
||||
ctypes.c_float(self.dx), ctypes.c_float(self.dy), ctypes.c_float(self.dt),
|
||||
ctypes.c_float(self.g),
|
||||
ctypes.c_float(self.gamma),
|
||||
ctypes.c_float(self.theta),
|
||||
ctypes.c_int(substep),
|
||||
ctypes.c_int(self.boundary_conditions),
|
||||
ctypes.c_float(self.u0[0].data), ctypes.c_float(self.u0[0].data.strides[0]),
|
||||
ctypes.c_float(self.u0[1].data), ctypes.c_float(self.u0[1].data.strides[0]),
|
||||
ctypes.c_float(self.u0[2].data), ctypes.c_float(self.u0[2].data.strides[0]),
|
||||
ctypes.c_float(self.u0[3].data), ctypes.c_float(self.u0[3].data.strides[0]),
|
||||
ctypes.c_float(self.u1[0].data), ctypes.c_float(self.u1[0].data.strides[0]),
|
||||
ctypes.c_float(self.u1[1].data), ctypes.c_float(self.u1[1].data.strides[0]),
|
||||
ctypes.c_float(self.u1[2].data), ctypes.c_float(self.u1[2].data.strides[0]),
|
||||
ctypes.c_float(self.u1[3].data), ctypes.c_float(self.u1[3].data.strides[0]),
|
||||
self.cfl_data,
|
||||
0, 0,
|
||||
ctypes.c_int(self.u0[0].x_halo), ctypes.c_int(self.ny)
|
||||
)
|
||||
)
|
||||
)
|
||||
|
||||
|
||||
# EAST
|
||||
# (x0, y0) x (x1, y1)
|
||||
# (nx-x_halo, 0) x (nx, ny)
|
||||
self.kernel.prepared_async_call(we_grid_size, self.block_size, self.stream,
|
||||
self.nx, self.ny,
|
||||
self.dx, self.dy, dt,
|
||||
self.g,
|
||||
self.gamma,
|
||||
self.theta,
|
||||
substep,
|
||||
self.boundary_conditions,
|
||||
self.u0[0].data.gpudata, self.u0[0].data.strides[0],
|
||||
self.u0[1].data.gpudata, self.u0[1].data.strides[0],
|
||||
self.u0[2].data.gpudata, self.u0[2].data.strides[0],
|
||||
self.u0[3].data.gpudata, self.u0[3].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[3].data.gpudata, self.u1[3].data.strides[0],
|
||||
self.cfl_data.gpudata,
|
||||
self.nx - int(self.u0[0].x_halo), 0,
|
||||
self.nx, self.ny)
|
||||
# self.kernel.prepared_async_call(we_grid_size, self.block_size, self.stream,
|
||||
# self.nx, self.ny,
|
||||
# self.dx, self.dy, dt,
|
||||
# self.g,
|
||||
# self.gamma,
|
||||
# self.theta,
|
||||
# substep,
|
||||
# self.boundary_conditions,
|
||||
# self.u0[0].data.gpudata, self.u0[0].data.strides[0],
|
||||
# self.u0[1].data.gpudata, self.u0[1].data.strides[0],
|
||||
# self.u0[2].data.gpudata, self.u0[2].data.strides[0],
|
||||
# self.u0[3].data.gpudata, self.u0[3].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[3].data.gpudata, self.u1[3].data.strides[0],
|
||||
# self.cfl_data.gpudata,
|
||||
# self.nx - int(self.u0[0].x_halo), 0,
|
||||
# self.nx, self.ny)
|
||||
|
||||
hip_check(
|
||||
hip.hipModuleLaunchKernel(
|
||||
kernel,
|
||||
*we_grid_size,
|
||||
*self.block_size,
|
||||
sharedMemBytes=0,
|
||||
stream=self.stream,
|
||||
kernelParams=None,
|
||||
extra=( # pass kernel's arguments
|
||||
ctypes.c_int(self.nx), ctypes.c_int(self.ny),
|
||||
ctypes.c_float(self.dx), ctypes.c_float(self.dy), ctypes.c_float(self.dt),
|
||||
ctypes.c_float(self.g),
|
||||
ctypes.c_float(self.gamma),
|
||||
ctypes.c_float(self.theta),
|
||||
ctypes.c_int(substep),
|
||||
ctypes.c_int(self.boundary_conditions),
|
||||
ctypes.c_float(self.u0[0].data), ctypes.c_float(self.u0[0].data.strides[0]),
|
||||
ctypes.c_float(self.u0[1].data), ctypes.c_float(self.u0[1].data.strides[0]),
|
||||
ctypes.c_float(self.u0[2].data), ctypes.c_float(self.u0[2].data.strides[0]),
|
||||
ctypes.c_float(self.u0[3].data), ctypes.c_float(self.u0[3].data.strides[0]),
|
||||
ctypes.c_float(self.u1[0].data), ctypes.c_float(self.u1[0].data.strides[0]),
|
||||
ctypes.c_float(self.u1[1].data), ctypes.c_float(self.u1[1].data.strides[0]),
|
||||
ctypes.c_float(self.u1[2].data), ctypes.c_float(self.u1[2].data.strides[0]),
|
||||
ctypes.c_float(self.u1[3].data), ctypes.c_float(self.u1[3].data.strides[0]),
|
||||
self.cfl_data,
|
||||
ctypes.c_int(self.nx) - ctypes.c_int(self.u0[0].x_halo), 0,
|
||||
ctypes.c_int(self.nx), ctypes.c_int(self.ny)
|
||||
)
|
||||
)
|
||||
)
|
||||
|
||||
hip_check(hip.hipDeviceSynchronize())
|
||||
hip_check(hip.hipModuleUnload(module))
|
||||
|
||||
hip_check(hip.hipFree(cfl_data))
|
||||
|
||||
print("--External and not Internal: Launching Kernel is ok")
|
||||
|
||||
return
|
||||
|
||||
if internal and not external:
|
||||
@ -263,6 +485,45 @@ class EE2D_KP07_dimsplit (BaseSimulator):
|
||||
self.cfl_data.gpudata,
|
||||
int(self.u0[0].x_halo), int(self.u0[0].y_halo),
|
||||
self.nx - int(self.u0[0].x_halo), self.ny - int(self.u0[0].y_halo))
|
||||
|
||||
|
||||
hip_check(
|
||||
hip.hipModuleLaunchKernel(
|
||||
kernel,
|
||||
*self.grid_size,
|
||||
*self.block_size,
|
||||
sharedMemBytes=0,
|
||||
stream=self.internal_stream,
|
||||
kernelParams=None,
|
||||
extra=( # pass kernel's arguments
|
||||
ctypes.c_int(self.nx), ctypes.c_int(self.ny),
|
||||
ctypes.c_float(self.dx), ctypes.c_float(self.dy), ctypes.c_float(self.dt),
|
||||
ctypes.c_float(self.g),
|
||||
ctypes.c_float(self.gamma),
|
||||
ctypes.c_float(self.theta),
|
||||
ctypes.c_int(substep),
|
||||
ctypes.c_int(self.boundary_conditions),
|
||||
ctypes.c_float(self.u0[0].data), ctypes.c_float(self.u0[0].data.strides[0]),
|
||||
ctypes.c_float(self.u0[1].data), ctypes.c_float(self.u0[1].data.strides[0]),
|
||||
ctypes.c_float(self.u0[2].data), ctypes.c_float(self.u0[2].data.strides[0]),
|
||||
ctypes.c_float(self.u0[3].data), ctypes.c_float(self.u0[3].data.strides[0]),
|
||||
ctypes.c_float(self.u1[0].data), ctypes.c_float(self.u1[0].data.strides[0]),
|
||||
ctypes.c_float(self.u1[1].data), ctypes.c_float(self.u1[1].data.strides[0]),
|
||||
ctypes.c_float(self.u1[2].data), ctypes.c_float(self.u1[2].data.strides[0]),
|
||||
ctypes.c_float(self.u1[3].data), ctypes.c_float(self.u1[3].data.strides[0]),
|
||||
self.cfl_data,
|
||||
ctypes.c_int(self.u0[0].x_halo), ctypes.c_int(self.u0[0].y_halo),
|
||||
ctypes.c_int(self.nx) - ctypes.c_int(self.u0[0].x_halo), ctypes.c_int(self.ny) - ctypes.c_int(self.u0[0].y_halo)
|
||||
)
|
||||
)
|
||||
)
|
||||
|
||||
hip_check(hip.hipDeviceSynchronize())
|
||||
hip_check(hip.hipModuleUnload(module))
|
||||
|
||||
hip_check(hip.hipFree(cfl_data))
|
||||
|
||||
print("--Internal and not External: Launching Kernel is ok")
|
||||
return
|
||||
|
||||
def swapBuffers(self):
|
||||
@ -277,6 +538,38 @@ class EE2D_KP07_dimsplit (BaseSimulator):
|
||||
self.u1.check()
|
||||
return
|
||||
|
||||
# computing min with hipblas: the output is an index
|
||||
def min_hipblas(self, num_elements, cfl_data, stream):
|
||||
num_bytes = num_elements * np.dtype(np.float32).itemsize
|
||||
num_bytes_i = np.dtype(np.int32).itemsize
|
||||
indx_d = hip_check(hip.hipMalloc(num_bytes_i))
|
||||
indx_h = np.zeros(1, dtype=np.int32)
|
||||
x_temp = np.zeros(num_elements, dtype=np.float32)
|
||||
|
||||
#print("--size.data:", cfl_data.size)
|
||||
handle = hip_check(hipblas.hipblasCreate())
|
||||
|
||||
#hip_check(hipblas.hipblasGetStream(handle, stream))
|
||||
#"incx" [int] specifies the increment for the elements of x. incx must be > 0.
|
||||
hip_check(hipblas.hipblasIsamin(handle, num_elements, cfl_data, 1, indx_d))
|
||||
|
||||
# destruction of handle
|
||||
hip_check(hipblas.hipblasDestroy(handle))
|
||||
|
||||
# copy result (stored in indx_d) back to the host (store in indx_h)
|
||||
hip_check(hip.hipMemcpyAsync(indx_h,indx_d,num_bytes_i,hip.hipMemcpyKind.hipMemcpyDeviceToHost,stream))
|
||||
hip_check(hip.hipMemcpyAsync(x_temp,cfl_data,num_bytes,hip.hipMemcpyKind.hipMemcpyDeviceToHost,stream))
|
||||
#hip_check(hip.hipMemsetAsync(cfl_data,0,num_bytes,self.stream))
|
||||
hip_check(hip.hipStreamSynchronize(stream))
|
||||
|
||||
min_value = x_temp.flatten()[indx_h[0]-1]
|
||||
|
||||
# clean up
|
||||
hip_check(hip.hipStreamDestroy(stream))
|
||||
hip_check(hip.hipFree(cfl_data))
|
||||
return min_value
|
||||
|
||||
def computeDt(self):
|
||||
max_dt = gpuarray.min(self.cfl_data, stream=self.stream).get();
|
||||
return max_dt*0.5
|
||||
#max_dt = gpuarray.min(self.cfl_data, stream=self.stream).get();
|
||||
max_dt = self.min_hipblas(self.cfl_data.size, self.cfl_data, self.stream)
|
||||
return max_dt*0.5
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user