From fb99632c00d8c395cac06ecce97ca36a03fbecf9 Mon Sep 17 00:00:00 2001
From: Martin Bauer <martin.bauer@fau.de>
Date: Thu, 17 May 2018 12:16:09 +0200
Subject: [PATCH] Added non-constant field-sizes vectorization support to outer
interface
---
cpu/vectorization.py | 15 ++++++++++-----
datahandling/datahandling_interface.py | 4 ++--
2 files changed, 12 insertions(+), 7 deletions(-)
diff --git a/cpu/vectorization.py b/cpu/vectorization.py
index 96486b3ea..ecc4ebc1a 100644
--- a/cpu/vectorization.py
+++ b/cpu/vectorization.py
@@ -1,20 +1,19 @@
import sympy as sp
import warnings
-
from typing import Union, Container
-
from pystencils.backends.simd_instruction_sets import get_vector_instruction_set
from pystencils.integer_functions import modulo_floor
from pystencils.sympyextensions import fast_subs
from pystencils.data_types import TypedSymbol, VectorType, get_type_of_expression, vector_memory_access, cast_func, \
collate_types, PointerType
import pystencils.astnodes as ast
-from pystencils.transformations import cut_loop, filtered_tree_iteration
+from pystencils.transformations import cut_loop, filtered_tree_iteration, replace_inner_stride_with_one
from pystencils.field import Field
def vectorize(kernel_ast: ast.KernelFunction, instruction_set: str = 'avx',
- assume_aligned: bool = False, nontemporal: Union[bool, Container[Union[str, Field]]] = False):
+ assume_aligned: bool = False, nontemporal: Union[bool, Container[Union[str, Field]]] = False,
+ assume_inner_stride_one: bool = False):
"""Explicit vectorization using SIMD vectorization via intrinsics.
Args:
@@ -27,7 +26,10 @@ def vectorize(kernel_ast: ast.KernelFunction, instruction_set: str = 'avx',
instructions have to be used.
nontemporal: a container of fields or field names for which nontemporal (streaming) stores are used.
If true, nontemporal access instructions are used for all fields.
-
+ assume_inner_stride_one: kernels with non-constant inner loop bound and strides can not be vectorized since
+ the inner loop stride is a runtime variable and thus might not be always 1.
+ If this parameter is set to true, the the inner stride is assumed to be always one.
+ This has to be ensured at runtime!
"""
all_fields = kernel_ast.fields_accessed
if nontemporal is None or nontemporal is False:
@@ -35,6 +37,9 @@ def vectorize(kernel_ast: ast.KernelFunction, instruction_set: str = 'avx',
elif nontemporal is True:
nontemporal = all_fields
+ if assume_inner_stride_one:
+ replace_inner_stride_with_one(kernel_ast)
+
field_float_dtypes = set(f.dtype for f in all_fields if f.dtype.is_float())
if len(field_float_dtypes) != 1:
raise NotImplementedError("Cannot vectorize kernels that contain accesses "
diff --git a/datahandling/datahandling_interface.py b/datahandling/datahandling_interface.py
index f8c21ed01..f8c67c9b0 100644
--- a/datahandling/datahandling_interface.py
+++ b/datahandling/datahandling_interface.py
@@ -34,7 +34,7 @@ class DataHandling(ABC):
@abstractmethod
def add_array(self, name: str, values_per_cell: int = 1, dtype=np.float64,
latex_name: Optional[str]=None, ghost_layers: Optional[int] = None, layout: Optional[str] = None,
- cpu: bool = True, gpu: Optional[bool] = None) -> Field:
+ cpu: bool = True, gpu: Optional[bool] = None, alignment=False) -> Field:
"""Adds a (possibly distributed) array to the handling that can be accessed using the given name.
For each array a symbolic field is available via the 'fields' dictionary
@@ -52,7 +52,7 @@ class DataHandling(ABC):
this is only important if values_per_cell > 1
cpu: allocate field on the CPU
gpu: allocate field on the GPU, if None, a GPU field is allocated if default_target is 'gpu'
-
+ alignment: either False for no alignment, or the number of bytes to align to
Returns:
pystencils field, that can be used to formulate symbolic kernels
"""
--
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