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@ -27,10 +27,12 @@ electromagnetic simulations on parallel compute hardware (mainly GPUs).
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* numpy
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* pyopencl
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* jinja2
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* [fdfd_tools](https://mpxd.net/gogs/jan/fdfd_tools)
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Optional (used for examples):
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* dill (for file output)
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* [gridlock](https://mpxd.net/gogs/jan/gridlock)
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* [masque](https://mpxd.net/gogs/jan/masque)
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* [fdfd_tools](https://mpxd.net/gogs/jan/fdfd_tools)
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To get the code, just clone this repository:
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```bash
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@ -1,11 +1,11 @@
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/*
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* Update E-field, including any PMLs.
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*
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*
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* Template parameters:
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* common_header: Rendered contents of common.cl
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* pmls: [('x', 'n'), ('z', 'p'),...] list of pml axes and polarities
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* pml_thickness: Number of cells (integer)
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*
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*
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* OpenCL args:
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* E, H, dt, eps, [p{01}e{np}, Psi_{xyz}{np}_E]
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*/
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@ -1,12 +1,12 @@
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/*
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* Update H-field, including any PMLs.
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* Also precalculate values for poynting vector if necessary.
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*
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*
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* Template parameters:
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* common_header: Rendered contents of common.cl
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* pmls: [('x', 'n'), ('z', 'p'),...] list of pml axes and polarities
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* pml_thickness: Number of cells (integer)
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* do_poynting: Whether to precalculate poynting vector components (boolean)
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* do_poynting: Whether to precalculate poynting vector components (boolean)
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*
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* OpenCL args:
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* E, H, dt, [p{01}h{np}, Psi_{xyz}{np}_H], [oS]
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@ -1,11 +1,11 @@
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/*
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* Update E-field, including any PMLs.
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*
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*
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* Template parameters:
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* common_header: Rendered contents of common.cl
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* pmls: [('x', 'n'), ('z', 'p'),...] list of pml axes and polarities
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* pml_thickness: Number of cells (integer)
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*
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*
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* OpenCL args:
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* E, H, dt, S, oS
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*/
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@ -17,12 +17,12 @@
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/*
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* Calculate S from oS (pre-calculated components)
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*/
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*/
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__global ftype *Sx = S + XX;
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__global ftype *Sy = S + YY;
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__global ftype *Sz = S + ZZ;
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// Use unscaled S components from H locations
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// Use unscaled S components from H locations
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__global ftype *oSxy = oS + 0 * field_size;
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__global ftype *oSyz = oS + 1 * field_size;
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__global ftype *oSzx = oS + 2 * field_size;
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@ -25,6 +25,35 @@ jinja_env = jinja2.Environment(loader=jinja2.PackageLoader(__name__, 'kernels'))
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class Simulation(object):
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"""
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Constructs and holds the basic FDTD operations and related fields
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After constructing this object, call the (update_E, update_H, update_S) members
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to perform FDTD updates on the stored (E, H, S) fields:
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sim = Simulation(grid.grids, do_poynting=True, pml_thickness=8)
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with open('sources.c', 'w') as f:
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f.write('{}'.format(sim.sources))
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for t in range(max_t):
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sim.update_E([]).wait()
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# Find the linear index for the center point, for Ey
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ind = numpy.ravel_multi_index(tuple(grid.shape//2), dims=grid.shape, order='C') + \
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numpy.prod(grid.shape) * 1
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# Perturb the field (i.e., add a soft current source)
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sim.E[ind] += numpy.sin(omega * t * sim.dt)
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event = sim.update_H([])
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if sim.update_S:
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event = sim.update_S([event])
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event.wait()
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with lzma.open('saved_simulation', 'wb') as f:
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dill.dump(fdfd_tools.unvec(sim.E.get(), grid.shape), f)
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Code in the form
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event2 = sim.update_H([event0, event1])
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indicates that the update_H operation should be prepared immediately, but wait for
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event0 and event1 to occur (i.e. previous operations to finish) before starting execution.
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event2 can then be used to prepare further operations to be run after update_H.
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"""
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E = None # type: List[pyopencl.array.Array]
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H = None # type: List[pyopencl.array.Array]
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@ -37,9 +66,9 @@ class Simulation(object):
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context = None # type: pyopencl.Context
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queue = None # type: pyopencl.CommandQueue
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update_E = None # type: Callable[[],pyopencl.Event]
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update_H = None # type: Callable[[],pyopencl.Event]
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update_S = None # type: Callable[[],pyopencl.Event]
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update_E = None # type: Callable[[List[pyopencl.Event]], pyopencl.Event]
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update_H = None # type: Callable[[List[pyopencl.Event]], pyopencl.Event]
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update_S = None # type: Callable[[List[pyopencl.Event]], pyopencl.Event]
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sources = None # type: Dict[str, str]
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def __init__(self,
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@ -50,8 +79,8 @@ class Simulation(object):
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context: pyopencl.Context = None,
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queue: pyopencl.CommandQueue = None,
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float_type: numpy.float32 or numpy.float64 = numpy.float32,
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pml_thickness: int = 10,
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pmls: List[List[str]] = None,
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pml_thickness: int = 10,
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do_poynting: bool = True):
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"""
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Initialize the simulation.
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@ -64,6 +93,21 @@ class Simulation(object):
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:param context: pyOpenCL context. If not given, pyopencl.create_some_context(False) is called.
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:param queue: pyOpenCL command queue. If not given, pyopencl.CommandQueue(context) is called.
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:param float_type: numpy.float32 or numpy.float64. Default numpy.float32.
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:param pmls: List of [axis, direction] pairs which specify simluation boundaries to be
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'coated' with a PML (absorbing layer). Axis should be one of 'x', 'y', 'z', and
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direction should be one of 'n', 'p' (i.e., negative, positive).
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Default is to apply PMLs to all six boundaries.
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:param pml_thickness: Thickness of any PMLs, in number of grid cells. Default 10.
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:param do_poynting: If true, enables calculation of the poynting vector, S.
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Poynting vector calculation adds the following computational burdens:
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* During update_H, ~6 extra additions/cell are performed in order to spatially
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average E and temporally average H. These quantities are multiplied
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(6 multiplications/cell) and then stored (6 writes/cell, cache-friendly).
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* update_S performs a discrete cross product using the precalculated products
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from update_H. This is not nice to the cache and similar to e.g. update_E
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in complexity.
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* GPU memory requirements are approximately doubled, since S and the intermediate
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products must be stored.
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"""
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if len(epsilon) != 3:
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