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re-write EE2D_KP07_dimsplit.py with hip-python

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Hicham Agueny 2024-02-20 12:45:48 +01:00
parent 41e496634e
commit 9bf115ddfd
1 changed files with 408 additions and 115 deletions
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515
GPUSimulators/EE2D_KP07_dimsplit.py
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@ -23,9 +23,10 @@ along with this program. If not, see <http://www.gnu.org/licenses/>.
from GPUSimulators import Simulator, Common from GPUSimulators import Simulator, Common
from GPUSimulators.Simulator import BaseSimulator, BoundaryCondition from GPUSimulators.Simulator import BaseSimulator, BoundaryCondition
import numpy as np import numpy as np
import ctypes
from pycuda import gpuarray #from pycuda import gpuarray
from hip import hip,hiprtc
@ -54,6 +55,21 @@ class EE2D_KP07_dimsplit (BaseSimulator):
gamma: Gas constant gamma: Gas constant
p: pressure p: pressure
""" """
def hip_check(call_result):
err = call_result[0]
result = call_result[1:]
if len(result) == 1:
result = result[0]
if isinstance(err, hip.hipError_t) and err != hip.hipError_t.hipSuccess:
raise RuntimeError(str(err))
elif (
isinstance(err, hiprtc.hiprtcResult)
and err != hiprtc.hiprtcResult.HIPRTC_SUCCESS
):
raise RuntimeError(str(err))
return result
def __init__(self, def __init__(self,
context, context,
rho, rho_u, rho_v, E, rho, rho_u, rho_v, E,
@ -79,19 +95,44 @@ class EE2D_KP07_dimsplit (BaseSimulator):
self.theta = np.float32(theta) self.theta = np.float32(theta)
#Get kernels #Get kernels
module = context.get_module("cuda/EE2D_KP07_dimsplit.cu", #module = context.get_module("cuda/EE2D_KP07_dimsplit.cu",
defines={ # defines={
'BLOCK_WIDTH': self.block_size[0], # 'BLOCK_WIDTH': self.block_size[0],
'BLOCK_HEIGHT': self.block_size[1] # 'BLOCK_HEIGHT': self.block_size[1]
}, # },
compile_args={ # compile_args={
'no_extern_c': True, # 'no_extern_c': True,
'options': ["--use_fast_math"], # 'options': ["--use_fast_math"],
}, # },
jit_compile_args={}) # jit_compile_args={})
self.kernel = module.get_function("KP07DimsplitKernel") #self.kernel = module.get_function("KP07DimsplitKernel")
self.kernel.prepare("iiffffffiiPiPiPiPiPiPiPiPiPiiii") #self.kernel.prepare("iiffffffiiPiPiPiPiPiPiPiPiPiiii")
#
kernel_file_path = os.path.abspath(os.path.join('cuda', 'EE2D_KP07_dimsplit.cu'))
with open(kernel_file_path, 'r') as file:
kernel_source = file.read()
prog = hip_check(hiprtc.hiprtcCreateProgram(kernel_source.encode(), b"KP07DimsplitKernel", 0, [], []))
props = hip.hipDeviceProp_t()
hip_check(hip.hipGetDeviceProperties(props,0))
arch = props.gcnArchName
print(f"Compiling kernel for {arch}")
cflags = [b"--offload-arch="+arch]
err, = hiprtc.hiprtcCompileProgram(prog, len(cflags), cflags)
if err != hiprtc.hiprtcResult.HIPRTC_SUCCESS:
log_size = hip_check(hiprtc.hiprtcGetProgramLogSize(prog))
log = bytearray(log_size)
hip_check(hiprtc.hiprtcGetProgramLog(prog, log))
raise RuntimeError(log.decode())
code_size = hip_check(hiprtc.hiprtcGetCodeSize(prog))
code = bytearray(code_size)
hip_check(hiprtc.hiprtcGetCode(prog, code))
module = hip_check(hip.hipModuleLoadData(code))
kernel = hip_check(hip.hipModuleGetFunction(module, b"KP07DimsplitKernel"))
#Create data by uploading to device #Create data by uploading to device
self.u0 = Common.ArakawaA2D(self.stream, self.u0 = Common.ArakawaA2D(self.stream,
@ -102,7 +143,13 @@ class EE2D_KP07_dimsplit (BaseSimulator):
nx, ny, nx, ny,
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)
# init device array cfl_data
data_h = np.empty(self.grid_size, dtype=np.float32)
num_bytes = data_h.size * data_h.itemsize
self.cfl_data = hip_check(hip.hipMalloc(num_bytes)).configure(
typestr="float32",shape=self.grid_size)
dt_x = np.min(self.dx / (np.abs(rho_u/rho) + np.sqrt(gamma*rho))) dt_x = np.min(self.dx / (np.abs(rho_u/rho) + np.sqrt(gamma*rho)))
dt_y = np.min(self.dy / (np.abs(rho_v/rho) + np.sqrt(gamma*rho))) dt_y = np.min(self.dy / (np.abs(rho_v/rho) + np.sqrt(gamma*rho)))
self.dt = min(dt_x, dt_y) self.dt = min(dt_x, dt_y)
@ -116,25 +163,65 @@ class EE2D_KP07_dimsplit (BaseSimulator):
if external and internal: if external and internal:
#print("COMPLETE DOMAIN (dt=" + str(dt) + ")") #print("COMPLETE DOMAIN (dt=" + str(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,
self.nx, self.ny, # self.nx, self.ny,
self.dx, self.dy, dt, # self.dx, self.dy, dt,
self.g, # self.g,
self.gamma, # self.gamma,
self.theta, # self.theta,
substep, # substep,
self.boundary_conditions, # self.boundary_conditions,
self.u0[0].data.gpudata, self.u0[0].data.strides[0], # self.u0[0].data.gpudata, self.u0[0].data.strides[0],
self.u0[1].data.gpudata, self.u0[1].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[2].data.gpudata, self.u0[2].data.strides[0],
self.u0[3].data.gpudata, self.u0[3].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[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.u1[3].data.gpudata, self.u1[3].data.strides[0], # self.u1[3].data.gpudata, self.u1[3].data.strides[0],
self.cfl_data.gpudata, # self.cfl_data.gpudata,
0, 0, # 0, 0,
self.nx, self.ny) # self.nx, self.ny)
#launch kernel
hip_check(
hip.hipModuleLaunchKernel(
kernel,
*self.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.nx), ctypes.c_int(self.ny)
)
)
)
hip_check(hip.hipDeviceSynchronize())
hip_check(hip.hipModuleUnload(module))
hip_check(hip.hipFree(cfl_data))
print("--External & Internal: Launching Kernel is ok")
return return
if external and not internal: if external and not internal:
@ -147,96 +234,231 @@ class EE2D_KP07_dimsplit (BaseSimulator):
# NORTH # NORTH
# (x0, y0) x (x1, y1) # (x0, y0) x (x1, y1)
# (0, ny-y_halo) x (nx, ny) # (0, ny-y_halo) x (nx, ny)
self.kernel.prepared_async_call(ns_grid_size, self.block_size, self.stream, # self.kernel.prepared_async_call(ns_grid_size, self.block_size, self.stream,
self.nx, self.ny, # self.nx, self.ny,
self.dx, self.dy, dt, # self.dx, self.dy, dt,
self.g, # self.g,
self.gamma, # self.gamma,
self.theta, # self.theta,
substep, # substep,
self.boundary_conditions, # self.boundary_conditions,
self.u0[0].data.gpudata, self.u0[0].data.strides[0], # self.u0[0].data.gpudata, self.u0[0].data.strides[0],
self.u0[1].data.gpudata, self.u0[1].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[2].data.gpudata, self.u0[2].data.strides[0],
self.u0[3].data.gpudata, self.u0[3].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[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.u1[3].data.gpudata, self.u1[3].data.strides[0], # self.u1[3].data.gpudata, self.u1[3].data.strides[0],
self.cfl_data.gpudata, # self.cfl_data.gpudata,
0, self.ny - int(self.u0[0].y_halo), # 0, self.ny - int(self.u0[0].y_halo),
self.nx, self.ny) # self.nx, self.ny)
hip_check(
hip.hipModuleLaunchKernel(
kernel,
*ns_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, ctypes.c_int(self.ny) - ctypes.c_int(self.u0[0].y_halo),
ctypes.c_int(self.nx), ctypes.c_int(self.ny)
)
)
)
# SOUTH # SOUTH
# (x0, y0) x (x1, y1) # (x0, y0) x (x1, y1)
# (0, 0) x (nx, y_halo) # (0, 0) x (nx, y_halo)
self.kernel.prepared_async_call(ns_grid_size, self.block_size, self.stream, # self.kernel.prepared_async_call(ns_grid_size, self.block_size, self.stream,
self.nx, self.ny, # self.nx, self.ny,
self.dx, self.dy, dt, # self.dx, self.dy, dt,
self.g, # self.g,
self.gamma, # self.gamma,
self.theta, # self.theta,
substep, # substep,
self.boundary_conditions, # self.boundary_conditions,
self.u0[0].data.gpudata, self.u0[0].data.strides[0], # self.u0[0].data.gpudata, self.u0[0].data.strides[0],
self.u0[1].data.gpudata, self.u0[1].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[2].data.gpudata, self.u0[2].data.strides[0],
self.u0[3].data.gpudata, self.u0[3].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[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.u1[3].data.gpudata, self.u1[3].data.strides[0], # self.u1[3].data.gpudata, self.u1[3].data.strides[0],
self.cfl_data.gpudata, # self.cfl_data.gpudata,
0, 0, # 0, 0,
self.nx, int(self.u0[0].y_halo)) # self.nx, int(self.u0[0].y_halo))
hip_check(
hip.hipModuleLaunchKernel(
kernel,
*ns_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.nx), ctypes.c_int(self.u0[0].y_halo)
)
)
)
we_grid_size = (1, self.grid_size[1]) we_grid_size = (1, self.grid_size[1])
# WEST # WEST
# (x0, y0) x (x1, y1) # (x0, y0) x (x1, y1)
# (0, 0) x (x_halo, ny) # (0, 0) x (x_halo, ny)
self.kernel.prepared_async_call(we_grid_size, self.block_size, self.stream, # self.kernel.prepared_async_call(we_grid_size, self.block_size, self.stream,
self.nx, self.ny, # self.nx, self.ny,
self.dx, self.dy, dt, # self.dx, self.dy, dt,
self.g, # self.g,
self.gamma, # self.gamma,
self.theta, # self.theta,
substep, # substep,
self.boundary_conditions, # self.boundary_conditions,
self.u0[0].data.gpudata, self.u0[0].data.strides[0], # self.u0[0].data.gpudata, self.u0[0].data.strides[0],
self.u0[1].data.gpudata, self.u0[1].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[2].data.gpudata, self.u0[2].data.strides[0],
self.u0[3].data.gpudata, self.u0[3].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[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.u1[3].data.gpudata, self.u1[3].data.strides[0], # self.u1[3].data.gpudata, self.u1[3].data.strides[0],
self.cfl_data.gpudata, # self.cfl_data.gpudata,
0, 0, # 0, 0,
int(self.u0[0].x_halo), self.ny) # 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 # EAST
# (x0, y0) x (x1, y1) # (x0, y0) x (x1, y1)
# (nx-x_halo, 0) x (nx, ny) # (nx-x_halo, 0) x (nx, ny)
self.kernel.prepared_async_call(we_grid_size, self.block_size, self.stream, # self.kernel.prepared_async_call(we_grid_size, self.block_size, self.stream,
self.nx, self.ny, # self.nx, self.ny,
self.dx, self.dy, dt, # self.dx, self.dy, dt,
self.g, # self.g,
self.gamma, # self.gamma,
self.theta, # self.theta,
substep, # substep,
self.boundary_conditions, # self.boundary_conditions,
self.u0[0].data.gpudata, self.u0[0].data.strides[0], # self.u0[0].data.gpudata, self.u0[0].data.strides[0],
self.u0[1].data.gpudata, self.u0[1].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[2].data.gpudata, self.u0[2].data.strides[0],
self.u0[3].data.gpudata, self.u0[3].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[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.u1[3].data.gpudata, self.u1[3].data.strides[0], # self.u1[3].data.gpudata, self.u1[3].data.strides[0],
self.cfl_data.gpudata, # self.cfl_data.gpudata,
self.nx - int(self.u0[0].x_halo), 0, # self.nx - int(self.u0[0].x_halo), 0,
self.nx, self.ny) # 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 return
if internal and not external: if internal and not external:
@ -263,6 +485,45 @@ class EE2D_KP07_dimsplit (BaseSimulator):
self.cfl_data.gpudata, self.cfl_data.gpudata,
int(self.u0[0].x_halo), int(self.u0[0].y_halo), 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)) 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 return
def swapBuffers(self): def swapBuffers(self):
@ -277,6 +538,38 @@ class EE2D_KP07_dimsplit (BaseSimulator):
self.u1.check() self.u1.check()
return 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): 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();
max_dt = self.min_hipblas(self.cfl_data.size, self.cfl_data, self.stream)
return max_dt*0.5 return max_dt*0.5