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已同步 2025-08-08 07:24:19 +08:00
Basic functional GPU solver with cylinder_Ascan_2D example.
这个提交包含在：
craig-warren
@@ -18,21 +18,24 @@
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from importlib import import_module
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import logging
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import sys
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import numpy as np
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import gprMax.config as config
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from .cuda.fields_updates import kernel_template_fields
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from .cuda.snapshots import kernel_template_store_snapshot
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from .cuda.source_updates import kernel_template_sources
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from .cython.fields_updates_normal import update_electric
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from .cython.fields_updates_normal import update_magnetic
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from .fields_outputs import store_outputs
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from .receivers import gpu_initialise_rx_arrays
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from .receivers import gpu_get_rx_array
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from .cython.fields_updates_normal import update_electric as update_electric_cpu
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from .cython.fields_updates_normal import update_magnetic as update_magnetic_cpu
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from .fields_outputs import store_outputs as store_outputs_cpu
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from .fields_outputs import kernel_template_store_outputs
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from .receivers import initialise_rx_arrays_gpu
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from .receivers import get_rx_array_gpu
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from .snapshots import Snapshot
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from .snapshots import gpu_initialise_snapshot_array
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from .snapshots import gpu_get_snapshot_array
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from .sources import gpu_initialise_src_arrays
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from .snapshots import initialise_snapshot_array_gpu
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from .snapshots import get_snapshot_array_gpu
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from .sources import initialise_src_arrays_gpu
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from .utilities import round32
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from .utilities import timer
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log = logging.getLogger(__name__)
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@@ -52,7 +55,7 @@ class CPUUpdates:
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def store_outputs(self):
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"""Store field component values for every receiver and transmission line."""
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store_outputs(self.grid)
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store_outputs_cpu(self.grid)
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def store_snapshots(self, iteration):
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"""Store any snapshots.
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@@ -66,7 +69,7 @@ class CPUUpdates:
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def update_magnetic(self):
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"""Update magnetic field components."""
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update_magnetic(self.grid.nx,
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update_magnetic_cpu(self.grid.nx,
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self.grid.ny,
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self.grid.nz,
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config.sim_config.hostinfo['ompthreads'],
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@@ -99,18 +102,18 @@ class CPUUpdates:
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"""Update electric field components."""
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# All materials are non-dispersive so do standard update.
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if config.model_configs[self.grid.model_num].materials['maxpoles'] == 0:
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update_electric(self.grid.nx,
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self.grid.ny,
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self.grid.nz,
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config.sim_config.hostinfo['ompthreads'],
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self.grid.updatecoeffsE,
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self.grid.ID,
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self.grid.Ex,
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self.grid.Ey,
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self.grid.Ez,
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self.grid.Hx,
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self.grid.Hy,
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self.grid.Hz)
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update_electric_cpu(self.grid.nx,
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self.grid.ny,
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self.grid.nz,
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config.sim_config.hostinfo['ompthreads'],
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self.grid.updatecoeffsE,
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self.grid.ID,
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self.grid.Ex,
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self.grid.Ey,
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self.grid.Ez,
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self.grid.Hx,
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self.grid.Hy,
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self.grid.Hz)
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# If there are any dispersive materials do 1st part of dispersive update
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# (it is split into two parts as it requires present and updated electric field values).
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@@ -247,20 +250,14 @@ class CUDAUpdates:
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self.dispersive_update_a = None
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self.dispersive_update_b = None
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import pycuda.driver as drv
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from pycuda.compiler import SourceModule
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drv.init()
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# Suppress nvcc warnings on Windows
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log.debug('Move nvcc compiler options to simulation config')
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if sys.platform == 'win32':
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self.compiler_opts = ['-w']
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else:
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self.compiler_opts = None
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# Import PyCUDA modules
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self.drv = import_module('pycuda.driver')
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self.source_module = getattr(import_module('pycuda.compiler'), 'SourceModule')
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self.drv.init()
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# Create device handle and context on specifc GPU device (and make it current context)
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self.dev = drv.Device(self.grid.gpu.deviceID)
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self.ctx = dev.make_context()
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self.dev = self.drv.Device(config.model_configs[self.grid.model_num].cuda['gpu'].deviceID)
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self.ctx = self.dev.make_context()
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# Initialise arrays on GPU, prepare kernels, and get kernel functions
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self.set_field_kernels()
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@@ -274,56 +271,56 @@ class CUDAUpdates:
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get kernel functions.
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"""
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if config.model_configs[self.grid.model_num].materials['maxpoles'] > 0:
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kernels_fields = SourceModule(kernels_template_fields.substitute(
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REAL=cudafloattype,
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COMPLEX=cudacomplextype,
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N_updatecoeffsE=self.grid.updatecoeffsE.size,
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N_updatecoeffsH=self.grid.updatecoeffsH.size,
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NY_MATCOEFFS=self.grid.updatecoeffsE.shape[1],
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NY_MATDISPCOEFFS=self.grid.updatecoeffsdispersive.shape[1],
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NX_FIELDS=self.grid.nx + 1,
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NY_FIELDS=self.grid.ny + 1,
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NZ_FIELDS=self.grid.nz + 1,
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NX_ID=self.grid.ID.shape[1],
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NY_ID=self.grid.ID.shape[2],
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NZ_ID=self.grid.ID.shape[3],
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NX_T=self.grid.Tx.shape[1],
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NY_T=self.grid.Tx.shape[2],
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NZ_T=self.grid.Tx.shape[3]),
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options=self.compiler_opts)
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kernels_fields = self.source_module(kernels_template_fields.substitute(
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REAL=config.sim_config.dtypes['C_float_or_double'],
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COMPLEX=config.sim_config.dtypes['C_complex'],
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N_updatecoeffsE=self.grid.updatecoeffsE.size,
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N_updatecoeffsH=self.grid.updatecoeffsH.size,
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NY_MATCOEFFS=self.grid.updatecoeffsE.shape[1],
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NY_MATDISPCOEFFS=self.grid.updatecoeffsdispersive.shape[1],
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NX_FIELDS=self.grid.nx + 1,
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NY_FIELDS=self.grid.ny + 1,
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NZ_FIELDS=self.grid.nz + 1,
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NX_ID=self.grid.ID.shape[1],
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NY_ID=self.grid.ID.shape[2],
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NZ_ID=self.grid.ID.shape[3],
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NX_T=self.grid.Tx.shape[1],
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NY_T=self.grid.Tx.shape[2],
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NZ_T=self.grid.Tx.shape[3]),
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options=config.sim_config.cuda['nvcc_opts'])
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else: # Set to one any substitutions for dispersive materials
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kernels_fields = SourceModule(kernels_template_fields.substitute(
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REAL=cudafloattype,
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COMPLEX=cudacomplextype,
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N_updatecoeffsE=self.grid.updatecoeffsE.size,
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N_updatecoeffsH=self.grid.updatecoeffsH.size,
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NY_MATCOEFFS=self.grid.updatecoeffsE.shape[1],
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NY_MATDISPCOEFFS=1,
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NX_FIELDS=self.grid.nx + 1,
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NY_FIELDS=self.grid.ny + 1,
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NZ_FIELDS=self.grid.nz + 1,
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NX_ID=self.grid.ID.shape[1],
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NY_ID=self.grid.ID.shape[2],
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NZ_ID=self.grid.ID.shape[3],
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NX_T=1,
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NY_T=1,
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NZ_T=1),
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options=self.compiler_opts)
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self.update_electric = kernels_fields.get_function("update_electric")
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self.update_magnetic = kernels_fields.get_function("update_magnetic")
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if self.grid.updatecoeffsE.nbytes + self.grid.updatecoeffsH.nbytes > self.grid.gpu.constmem:
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raise GeneralError(log.exception(f'Too many materials in the model to fit onto constant memory of size {human_size(self.grid.gpu.constmem)} on {self.grid.gpu.deviceID} - {self.grid.gpu.name} GPU'))
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self.copy_mat_coeffs()
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kernels_fields = self.source_module(kernel_template_fields.substitute(
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REAL=config.sim_config.dtypes['C_float_or_double'],
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COMPLEX=config.sim_config.dtypes['C_complex'],
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N_updatecoeffsE=self.grid.updatecoeffsE.size,
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N_updatecoeffsH=self.grid.updatecoeffsH.size,
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NY_MATCOEFFS=self.grid.updatecoeffsE.shape[1],
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NY_MATDISPCOEFFS=1,
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NX_FIELDS=self.grid.nx + 1,
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NY_FIELDS=self.grid.ny + 1,
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NZ_FIELDS=self.grid.nz + 1,
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NX_ID=self.grid.ID.shape[1],
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NY_ID=self.grid.ID.shape[2],
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NZ_ID=self.grid.ID.shape[3],
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NX_T=1,
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NY_T=1,
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NZ_T=1),
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options=config.sim_config.cuda['nvcc_opts'])
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self.update_electric_gpu = kernels_fields.get_function("update_electric")
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self.update_magnetic_gpu = kernels_fields.get_function("update_magnetic")
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if (self.grid.updatecoeffsE.nbytes + self.grid.updatecoeffsH.nbytes > config.model_configs[self.grid.model_num].cuda['gpu'].constmem):
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raise GeneralError(log.exception(f"Too many materials in the model to fit onto constant memory of size {human_size(config.model_configs[self.grid.model_num].cuda['gpu'].constmem)} on {config.model_configs[self.grid.model_num].cuda['gpu'].deviceID} - {config.model_configs[self.grid.model_num].cuda['gpu'].name} GPU"))
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self.copy_mat_coeffs(kernels_fields, kernels_fields)
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# Electric and magnetic field updates - dispersive materials - get kernel functions and initialise array on GPU
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if config.model_configs[self.grid.model_num].materials['maxpoles'] > 0: # If there are any dispersive materials (updates are split into two parts as they require present and updated electric field values).
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self.dispersive_update_a = kernels_fields.get_function("update_electric_dispersive_A")
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self.dispersive_update_b = kernels_fields.get_function("update_electric_dispersive_B")
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self.grid.gpu_initialise_dispersive_arrays()
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self.grid.initialise_dispersive_arrays()
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# Electric and magnetic field updates - set blocks per grid and initialise field arrays on GPU
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self.grid.gpu_set_blocks_per_grid()
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self.grid.gpu_initialise_arrays()
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self.grid.set_blocks_per_grid()
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self.grid.initialise_arrays()
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def set_pml_kernels(self):
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"""PMLS - prepare kernels and get kernel functions."""
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@@ -336,81 +333,81 @@ class CUDAUpdates:
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kernelmagneticfunc = getattr(import_module(pmlmodulemagnetic),
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'kernels_template_pml_magnetic_' +
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self.grid.pmlformulation)
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kernels_pml_electric = SourceModule(kernelelectricfunc.substitute(
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REAL=cudafloattype,
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N_updatecoeffsE=self.grid.updatecoeffsE.size,
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NY_MATCOEFFS=self.grid.updatecoeffsE.shape[1],
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NX_FIELDS=self.grid.nx + 1,
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NY_FIELDS=self.grid.ny + 1,
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NZ_FIELDS=self.grid.nz + 1,
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NX_ID=self.grid.ID.shape[1],
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NY_ID=self.grid.ID.shape[2],
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NZ_ID=self.grid.ID.shape[3]),
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options=self.compiler_opts)
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kernels_pml_magnetic = SourceModule(kernelmagneticfunc.substitute(
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REAL=cudafloattype,
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N_updatecoeffsH=self.grid.updatecoeffsH.size,
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NY_MATCOEFFS=self.grid.updatecoeffsH.shape[1],
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NX_FIELDS=self.grid.nx + 1,
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NY_FIELDS=self.grid.ny + 1,
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NZ_FIELDS=self.grid.nz + 1,
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NX_ID=self.gridG.ID.shape[1],
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NY_ID=self.grid.ID.shape[2],
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NZ_ID=self.grid.ID.shape[3]),
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options=self.compiler_opts)
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self.copy_mat_coeffs()
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kernels_pml_electric = self.source_module(kernelelectricfunc.substitute(
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REAL=config.sim_config.dtypes['C_float_or_double'],
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N_updatecoeffsE=self.grid.updatecoeffsE.size,
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NY_MATCOEFFS=self.grid.updatecoeffsE.shape[1],
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NX_FIELDS=self.grid.nx + 1,
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NY_FIELDS=self.grid.ny + 1,
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NZ_FIELDS=self.grid.nz + 1,
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NX_ID=self.grid.ID.shape[1],
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NY_ID=self.grid.ID.shape[2],
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NZ_ID=self.grid.ID.shape[3]),
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options=config.sim_config.cuda['nvcc_opts'])
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kernels_pml_magnetic = self.source_module(kernelmagneticfunc.substitute(
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REAL=config.sim_config.dtypes['C_float_or_double'],
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N_updatecoeffsH=self.grid.updatecoeffsH.size,
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NY_MATCOEFFS=self.grid.updatecoeffsH.shape[1],
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NX_FIELDS=self.grid.nx + 1,
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NY_FIELDS=self.grid.ny + 1,
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NZ_FIELDS=self.grid.nz + 1,
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NX_ID=self.grid.ID.shape[1],
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NY_ID=self.grid.ID.shape[2],
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NZ_ID=self.grid.ID.shape[3]),
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options=config.sim_config.cuda['nvcc_opts'])
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self.copy_mat_coeffs(kernels_pml_electric, kernels_pml_magnetic)
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# Set block per grid, initialise arrays on GPU, and get kernel functions
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for pml in self.grid.pmls:
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pml.gpu_initialise_arrays()
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pml.gpu_get_update_funcs(kernels_pml_electric, kernels_pml_magnetic)
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pml.gpu_set_blocks_per_grid(self.grid)
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pml.initialise_field_arrays_gpu()
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pml.get_update_funcs(kernels_pml_electric, kernels_pml_magnetic)
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pml.set_blocks_per_grid(self.grid)
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def set_rx_kernel(self):
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"""Receivers - initialise arrays on GPU, prepare kernel and get kernel
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function.
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"""
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if self.grid.rxs:
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rxcoords_gpu, rxs_gpu = gpu_initialise_rx_arrays(self.grid)
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kernel_store_outputs = SourceModule(kernel_template_store_outputs.substitute(
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REAL=cudafloattype,
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NY_RXCOORDS=3,
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NX_RXS=6,
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NY_RXS=self.grid.iterations,
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NZ_RXS=len(self.grid.rxs),
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NX_FIELDS=self.grid.nx + 1,
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NY_FIELDS=self.grid.ny + 1,
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NZ_FIELDS=self.grid.nz + 1),
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options=self.compiler_opts)
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self.store_outputs = kernel_store_outputs.get_function("store_outputs")
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self.rxcoords_gpu, self.rxs_gpu = initialise_rx_arrays_gpu(self.grid)
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kernel_store_outputs = self.source_module(kernel_template_store_outputs.substitute(
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REAL=config.sim_config.dtypes['C_float_or_double'],
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NY_RXCOORDS=3,
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NX_RXS=6,
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NY_RXS=self.grid.iterations,
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NZ_RXS=len(self.grid.rxs),
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NX_FIELDS=self.grid.nx + 1,
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NY_FIELDS=self.grid.ny + 1,
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NZ_FIELDS=self.grid.nz + 1),
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options=config.sim_config.cuda['nvcc_opts'])
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self.store_outputs_gpu = kernel_store_outputs.get_function("store_outputs")
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def set_src_kernels(self):
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"""Sources - initialise arrays on GPU, prepare kernel and get kernel
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function.
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"""
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if self.grid.voltagesources + self.grid.hertziandipoles + self.grid.magneticdipoles:
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kernels_sources = SourceModule(kernels_template_sources.substitute(
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REAL=cudafloattype,
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N_updatecoeffsE=self.grid.updatecoeffsE.size,
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N_updatecoeffsH=self.grid.updatecoeffsH.size,
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NY_MATCOEFFS=self.grid.updatecoeffsE.shape[1],
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NY_SRCINFO=4,
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NY_SRCWAVES=self.grid.iterations,
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NX_FIELDS=self.grid.nx + 1,
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NY_FIELDS=self.grid.ny + 1,
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NZ_FIELDS=self.grid.nz + 1,
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NX_ID=self.grid.ID.shape[1],
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NY_ID=self.grid.ID.shape[2],
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NZ_ID=self.grid.ID.shape[3]),
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options=self.compiler_opts)
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self.copy_mat_coeffs()
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kernels_sources = self.source_module(kernel_template_sources.substitute(
|
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REAL=config.sim_config.dtypes['C_float_or_double'],
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N_updatecoeffsE=self.grid.updatecoeffsE.size,
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N_updatecoeffsH=self.grid.updatecoeffsH.size,
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NY_MATCOEFFS=self.grid.updatecoeffsE.shape[1],
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NY_SRCINFO=4,
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NY_SRCWAVES=self.grid.iterations,
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NX_FIELDS=self.grid.nx + 1,
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NY_FIELDS=self.grid.ny + 1,
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NZ_FIELDS=self.grid.nz + 1,
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NX_ID=self.grid.ID.shape[1],
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NY_ID=self.grid.ID.shape[2],
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NZ_ID=self.grid.ID.shape[3]),
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options=config.sim_config.cuda['nvcc_opts'])
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self.copy_mat_coeffs(kernels_sources, kernels_sources)
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if self.grid.hertziandipoles:
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self.srcinfo1_hertzian_gpu, self.srcinfo2_hertzian_gpu, self.srcwaves_hertzian_gpu = gpu_initialise_src_arrays(self.grid.hertziandipoles, self.grid)
|
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self.srcinfo1_hertzian_gpu, self.srcinfo2_hertzian_gpu, self.srcwaves_hertzian_gpu = initialise_src_arrays_gpu(self.grid.hertziandipoles, self.grid)
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self.update_hertzian_dipole_gpu = kernels_sources.get_function("update_hertzian_dipole")
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if self.grid.magneticdipoles:
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self.srcinfo1_magnetic_gpu, self.srcinfo2_magnetic_gpu, self.srcwaves_magnetic_gpu = gpu_initialise_src_arrays(self.grid.magneticdipoles, self.grid)
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self.srcinfo1_magnetic_gpu, self.srcinfo2_magnetic_gpu, self.srcwaves_magnetic_gpu = initialise_src_arrays_gpu(self.grid.magneticdipoles, self.grid)
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self.update_magnetic_dipole_gpu = kernels_sources.get_function("update_magnetic_dipole")
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if self.grid.voltagesources:
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self.srcinfo1_voltage_gpu, self.srcinfo2_voltage_gpu, self.srcwaves_voltage_gpu = gpu_initialise_src_arrays(self.grid.voltagesources, self.grid)
|
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self.srcinfo1_voltage_gpu, self.srcinfo2_voltage_gpu, self.srcwaves_voltage_gpu = initialise_src_arrays_gpu(self.grid.voltagesources, self.grid)
|
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self.update_voltage_source_gpu = kernels_sources.get_function("update_voltage_source")
|
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|
||||
def set_snapshot_kernel(self):
|
||||
@@ -418,42 +415,46 @@ class CUDAUpdates:
|
||||
function.
|
||||
"""
|
||||
if self.grid.snapshots:
|
||||
self.snapEx_gpu, self.snapEy_gpu, self.snapEz_gpu, self.snapHx_gpu, self.snapHy_gpu, self.snapHz_gpu = gpu_initialise_snapshot_array(self.grid)
|
||||
kernel_store_snapshot = SourceModule(kernel_template_store_snapshot.substitute(
|
||||
REAL=cudafloattype,
|
||||
NX_SNAPS=Snapshot.nx_max,
|
||||
NY_SNAPS=Snapshot.ny_max,
|
||||
NZ_SNAPS=Snapshot.nz_max,
|
||||
NX_FIELDS=self.grid.nx + 1,
|
||||
NY_FIELDS=self.grid.ny + 1,
|
||||
NZ_FIELDS=self.grid.nz + 1),
|
||||
options=self.compiler_opts)
|
||||
self.snapEx_gpu, self.snapEy_gpu, self.snapEz_gpu, self.snapHx_gpu, self.snapHy_gpu, self.snapHz_gpu = initialise_snapshot_array_gpu(self.grid)
|
||||
kernel_store_snapshot = self.source_module(kernel_template_store_snapshot.substitute(
|
||||
REAL=config.sim_config.dtypes['C_float_or_double'],
|
||||
NX_SNAPS=Snapshot.nx_max,
|
||||
NY_SNAPS=Snapshot.ny_max,
|
||||
NZ_SNAPS=Snapshot.nz_max,
|
||||
NX_FIELDS=self.grid.nx + 1,
|
||||
NY_FIELDS=self.grid.ny + 1,
|
||||
NZ_FIELDS=self.grid.nz + 1),
|
||||
options=config.sim_config.cuda['nvcc_opts'])
|
||||
self.store_snapshot_gpu = kernel_store_snapshot.get_function("store_snapshot")
|
||||
|
||||
def copy_mat_coeffs(self):
|
||||
def copy_mat_coeffs(self, kernelE, kernelH):
|
||||
"""Copy material coefficient arrays to constant memory of GPU
|
||||
(must be <64KB).
|
||||
|
||||
Args:
|
||||
kernelE (kernel): electric field kernel.
|
||||
kernelH (kernel): magnetic field kernel.
|
||||
"""
|
||||
updatecoeffsE = kernels_sources.get_global('updatecoeffsE')[0]
|
||||
updatecoeffsH = kernels_sources.get_global('updatecoeffsH')[0]
|
||||
updatecoeffsE = kernelE.get_global('updatecoeffsE')[0]
|
||||
updatecoeffsH = kernelH.get_global('updatecoeffsH')[0]
|
||||
self.drv.memcpy_htod(updatecoeffsE, self.grid.updatecoeffsE)
|
||||
self.drv.memcpy_htod(updatecoeffsH, self.grid.updatecoeffsH)
|
||||
|
||||
def store_outputs(self):
|
||||
"""Store field component values for every receiver and transmission line."""
|
||||
"""Store field component values for every receiver."""
|
||||
if self.grid.rxs:
|
||||
self.store_outputs(np.int32(len(self.grid.rxs)),
|
||||
np.int32(self.grid.iteration),
|
||||
self.rxcoords_gpu.gpudata,
|
||||
self.rxs_gpu.gpudata,
|
||||
self.grid.Ex_gpu.gpudata,
|
||||
self.grid.Ey_gpu.gpudata,
|
||||
self.grid.Ez_gpu.gpudata,
|
||||
self.grid.Hx_gpu.gpudata,
|
||||
self.grid.Hy_gpu.gpudata,
|
||||
self.grid.Hz_gpu.gpudata,
|
||||
block=(1, 1, 1),
|
||||
grid=(round32(len(self.grid.rxs)), 1, 1))
|
||||
self.store_outputs_gpu(np.int32(len(self.grid.rxs)),
|
||||
np.int32(self.grid.iteration),
|
||||
self.rxcoords_gpu.gpudata,
|
||||
self.rxs_gpu.gpudata,
|
||||
self.grid.Ex_gpu.gpudata,
|
||||
self.grid.Ey_gpu.gpudata,
|
||||
self.grid.Ez_gpu.gpudata,
|
||||
self.grid.Hx_gpu.gpudata,
|
||||
self.grid.Hy_gpu.gpudata,
|
||||
self.grid.Hz_gpu.gpudata,
|
||||
block=(1, 1, 1),
|
||||
grid=(round32(len(self.grid.rxs)), 1, 1))
|
||||
|
||||
def store_snapshots(self, iteration):
|
||||
"""Store any snapshots.
|
||||
@@ -501,32 +502,32 @@ class CUDAUpdates:
|
||||
|
||||
def update_magnetic(self):
|
||||
"""Update magnetic field components."""
|
||||
self.update_magnetic(np.int32(self.grid.nx),
|
||||
np.int32(self.grid.ny),
|
||||
np.int32(self.grid.nz),
|
||||
self.grid.ID_gpu,
|
||||
self.grid.Hx_gpu,
|
||||
self.grid.Hy_gpu,
|
||||
self.grid.Hz_gpu,
|
||||
self.grid.Ex_gpu,
|
||||
self.grid.Ey_gpu,
|
||||
self.grid.Ez_gpu,
|
||||
block=self.grid.tpb,
|
||||
grid=self.grid.bpg)
|
||||
self.update_magnetic_gpu(np.int32(self.grid.nx),
|
||||
np.int32(self.grid.ny),
|
||||
np.int32(self.grid.nz),
|
||||
self.grid.ID_gpu,
|
||||
self.grid.Hx_gpu,
|
||||
self.grid.Hy_gpu,
|
||||
self.grid.Hz_gpu,
|
||||
self.grid.Ex_gpu,
|
||||
self.grid.Ey_gpu,
|
||||
self.grid.Ez_gpu,
|
||||
block=self.grid.tpb,
|
||||
grid=self.grid.bpg)
|
||||
|
||||
def update_magnetic_pml(self):
|
||||
"""Update magnetic field components with the PML correction."""
|
||||
for pml in self.grid.pmls:
|
||||
pml.gpu_update_magnetic(self.grid)
|
||||
pml.update_magnetic(self.grid)
|
||||
|
||||
def update_magnetic_sources(self):
|
||||
"""Update magnetic field components from sources."""
|
||||
if self.grid.magneticdipoles:
|
||||
self.update_magnetic_dipole_gpu(np.int32(len(self.grid.magneticdipoles)),
|
||||
np.int32(self.grid.iteration),
|
||||
config.dtypes['float_or_double'](self.grid.dx),
|
||||
config.dtypes['float_or_double'](self.grid.dy),
|
||||
config.dtypes['float_or_double'](self.grid.dz),
|
||||
config.sim_config.dtypes['float_or_double'](self.grid.dx),
|
||||
config.sim_config.dtypes['float_or_double'](self.grid.dy),
|
||||
config.sim_config.dtypes['float_or_double'](self.grid.dz),
|
||||
self.srcinfo1_magnetic_gpu.gpudata,
|
||||
self.srcinfo2_magnetic_gpu.gpudata,
|
||||
self.srcwaves_magnetic_gpu.gpudata,
|
||||
@@ -541,18 +542,18 @@ class CUDAUpdates:
|
||||
"""Update electric field components."""
|
||||
# All materials are non-dispersive so do standard update.
|
||||
if config.model_configs[self.grid.model_num].materials['maxpoles'] == 0:
|
||||
self.update_electric(np.int32(self.grid.nx),
|
||||
np.int32(self.grid.ny),
|
||||
np.int32(self.grid.nz),
|
||||
self.grid.ID_gpu,
|
||||
self.grid.Ex_gpu,
|
||||
self.grid.Ey_gpu,
|
||||
self.grid.Ez_gpu,
|
||||
self.grid.Hx_gpu,
|
||||
self.grid.Hy_gpu,
|
||||
self.grid.Hz_gpu,
|
||||
block=self.grid.tpb,
|
||||
grid=self.grid.bpg)
|
||||
self.update_electric_gpu(np.int32(self.grid.nx),
|
||||
np.int32(self.grid.ny),
|
||||
np.int32(self.grid.nz),
|
||||
self.grid.ID_gpu,
|
||||
self.grid.Ex_gpu,
|
||||
self.grid.Ey_gpu,
|
||||
self.grid.Ez_gpu,
|
||||
self.grid.Hx_gpu,
|
||||
self.grid.Hy_gpu,
|
||||
self.grid.Hz_gpu,
|
||||
block=self.grid.tpb,
|
||||
grid=self.grid.bpg)
|
||||
|
||||
# If there are any dispersive materials do 1st part of dispersive update
|
||||
# (it is split into two parts as it requires present and updated electric field values).
|
||||
@@ -578,7 +579,7 @@ class CUDAUpdates:
|
||||
def update_electric_pml(self):
|
||||
"""Update electric field components with the PML correction."""
|
||||
for pml in self.grid.pmls:
|
||||
pml.gpu_update_electric(self.grid)
|
||||
pml.update_electric(self.grid)
|
||||
|
||||
def update_electric_sources(self):
|
||||
"""Update electric field components from sources -
|
||||
@@ -587,9 +588,9 @@ class CUDAUpdates:
|
||||
if self.grid.voltagesources:
|
||||
self.update_voltage_source_gpu(np.int32(len(self.grid.voltagesources)),
|
||||
np.int32(self.grid.iteration),
|
||||
config.dtypes['float_or_double'](self.grid.dx),
|
||||
config.dtypes['float_or_double'](self.grid.dy),
|
||||
config.dtypes['float_or_double'](self.grid.dz),
|
||||
config.sim_config.dtypes['float_or_double'](self.grid.dx),
|
||||
config.sim_config.dtypes['float_or_double'](self.grid.dy),
|
||||
config.sim_config.dtypes['float_or_double'](self.grid.dz),
|
||||
self.srcinfo1_voltage_gpu.gpudata,
|
||||
self.srcinfo2_voltage_gpu.gpudata,
|
||||
self.srcwaves_voltage_gpu.gpudata,
|
||||
@@ -603,9 +604,9 @@ class CUDAUpdates:
|
||||
if self.grid.hertziandipoles:
|
||||
self.update_hertzian_dipole_gpu(np.int32(len(self.grid.hertziandipoles)),
|
||||
np.int32(self.grid.iteration),
|
||||
config.dtypes['float_or_double'](self.grid.dx),
|
||||
config.dtypes['float_or_double'](self.grid.dy),
|
||||
config.dtypes['float_or_double'](self.grid.dz),
|
||||
config.sim_config.dtypes['float_or_double'](self.grid.dx),
|
||||
config.sim_config.dtypes['float_or_double'](self.grid.dy),
|
||||
config.sim_config.dtypes['float_or_double'](self.grid.dz),
|
||||
self.srcinfo1_hertzian_gpu.gpudata,
|
||||
self.srcinfo2_hertzian_gpu.gpudata,
|
||||
self.srcwaves_hertzian_gpu.gpudata,
|
||||
@@ -660,21 +661,20 @@ class CUDAUpdates:
|
||||
"""Copy data from GPU back to CPU to save to file(s)."""
|
||||
# Copy output from receivers array back to correct receiver objects
|
||||
if self.grid.rxs:
|
||||
gpu_get_rx_array(self.rxs_gpu.get(),
|
||||
get_rx_array_gpu(self.rxs_gpu.get(),
|
||||
self.rxcoords_gpu.get(),
|
||||
self.grid)
|
||||
|
||||
# Copy data from any snapshots back to correct snapshot objects
|
||||
if self.grid.snapshots and not self.grid.snapsgpu2cpu:
|
||||
for i, snap in enumerate(self.grid.snapshots):
|
||||
gpu_get_snapshot_array(self.snapEx_gpu.get(),
|
||||
get_snapshot_array_gpu(self.snapEx_gpu.get(),
|
||||
self.snapEy_gpu.get(),
|
||||
self.snapEz_gpu.get(),
|
||||
self.snapHx_gpu.get(),
|
||||
self.snapHy_gpu.get(),
|
||||
self.snapHz_gpu.get(),
|
||||
i,
|
||||
snap)
|
||||
i, snap)
|
||||
|
||||
def cleanup(self):
|
||||
"""Cleanup GPU context."""
|
||||
|
||||
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