Add fast operator evaluation for tensor-product discretizations#362
Draft
a-alveyblanc wants to merge 65 commits intoinducer:mainfrom
Draft
Add fast operator evaluation for tensor-product discretizations#362a-alveyblanc wants to merge 65 commits intoinducer:mainfrom
a-alveyblanc wants to merge 65 commits intoinducer:mainfrom
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…product-operators
Owner
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Should this be marked draft given that there are pending TODOs? |
…product-operators
inducer
reviewed
Nov 25, 2024
grudge/bilinear_forms.py
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| # {{{ BilinearForm base class | ||
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| @dataclass | ||
| class _BilinearForm: |
grudge/transform/mappers.py
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| new_args = [] | ||
| new_access_descrs = [] | ||
| for iarg, arg in enumerate(expr.args): | ||
| # we assume that the 0th argument will be the one with this tag |
Owner
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- So check that?
- Generally, beef up the matching. (maybe come up with some tools,
matchstatement)
grudge/transform/mappers.py
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| included in the original einsum), and properly reshapes to and from | ||
| tensor-product form to apply the 1D mass operator. | ||
| """ | ||
| def map_einsum(self, expr, *args, **kwargs): |
grudge/transform/mappers.py
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| return expr.copy(args=tuple(new_args)) | ||
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| class InverseMassDistributor(CopyMapperWithExtraArgs): |
Owner
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- Split into two mappers (with the inner only handling what's allowed as part of distribution)
- Bonus points for generalizing to simplex
grudge/transform/mappers.py
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| return expr.copy(args=tuple(new_args)) | ||
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| class RedundantMassTimesMassInverseRemover(CopyMapperWithExtraArgs): |
grudge/transform/mappers.py
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| return expr.copy(args=tuple(new_args)) | ||
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| class RedundantMassTimesMassInverseRemover(CopyMapperWithExtraArgs): |
inducer
reviewed
Dec 16, 2024
grudge/op.py
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| in_element_group: InterpolatoryElementGroupBase): | ||
| in_element_group: InterpolatoryElementGroupBase) -> ArrayOrContainer: | ||
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| @keyed_memoize_in( |
Owner
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Let's have @keyed_memoize_in_first_arg.
grudge/op.py
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| else: | ||
| quadrature_rule = in_grp.quadrature_rule() | ||
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| if isinstance(in_grp, SimplexElementGroupBase): |
Owner
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Maybe the TP and full versions want to be separate functions?
grudge/op.py
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| def _strong_scalar_grad(dcoll, dd_in, vec): | ||
| assert isinstance(dd_in.domain_tag, VolumeDomainTag) | ||
| def _reference_stiffness_transpose_matrices( |
Owner
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Unify with above via basis_getter?
grudge/op.py
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| discr = dcoll.discr_from_dd(dd_in) | ||
| actx = vec.array_context | ||
| if in_grp == out_grp: |
Owner
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Suggested change
| if in_grp == out_grp: | |
| if isinstance(in_grp, Quadrature) |
?
Suggested change
| if in_grp == out_grp: | |
| if not isinstance(in_grp, Interpolatory) |
?
grudge/op.py
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| out_grp.shape | ||
| ) | ||
| else: | ||
| quadrature_rule = in_grp.quadrature_rule() |
Owner
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Check that quadrature_rule provides sufficient exactness.
grudge/op.py
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| return get_reference_stiffness_transpose_matrices(out_grp, in_grp) | ||
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| def reference_mass_matrix(actx: ArrayContext, |
grudge/op.py
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| """ | ||
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| per_group_grads = [] | ||
| for out_grp, in_grp, vec_i, ijm_i in zip( |
inducer
reviewed
Jan 8, 2025
| use_tensor_product_fast_eval=use_tensor_product_fast_eval | ||
| ) | ||
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| if input_group == output_group: |
Owner
There was a problem hiding this comment.
if isinstance(input_group, Interpolatory):
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Supersedes #313, #354
Adds:
Non-essential transformations will be added in a later PR. This is to keep this (already large) PR manageable.The plan is to break this PR up into a sequence of smaller PRs to ease the review process. Keeping this up until that starts happening.TODOs:
op.pyto use generic bilinear form evaluationcc @MTCam