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Commit f0d2fde6 authored by Richard Angersbach's avatar Richard Angersbach
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Encapsulate mapping of binop strings to actual operands and now also use for...

Encapsulate mapping of binop strings to actual operands and now also use for considering initial value of passed reduction pointer value
parent 4c726aa6
1 merge request!438Reduction Support
Pipeline #72642 failed with stages
in 4 minutes and 30 seconds
......@@ -14,6 +14,7 @@ from ...sympyextensions import (
integer_functions,
ConditionalFieldAccess,
)
from ...sympyextensions.binop_mapping import binop_str_to_expr
from ...sympyextensions.typed_sympy import TypedSymbol, CastFunc, DynamicType
from ...sympyextensions.pointers import AddressOf, mem_acc
from ...sympyextensions.reduction import ReducedAssignment
......@@ -173,19 +174,7 @@ class FreezeExpressions:
assert isinstance(lhs, PsExpression)
assert isinstance(rhs, PsExpression)
match expr.op:
case "+=":
op = add
case "-=":
op = sub
case "*=":
op = mul
case "/=":
op = truediv
case _:
raise FreezeError(f"Unsupported augmented assignment: {expr.op}.")
return PsAssignment(lhs, op(lhs.clone(), rhs))
return PsAssignment(lhs, binop_str_to_expr(expr.op[0], lhs.clone(), rhs))
def map_ReducedAssignment(self, expr: ReducedAssignment):
lhs = self.visit(expr.lhs)
......@@ -204,27 +193,25 @@ class FreezeExpressions:
new_lhs_symb = PsSymbol(f"{orig_lhs_symb.name}_local", dtype)
new_lhs = PsSymbolExpr(new_lhs_symb)
# match for reduction operation and set neutral init_val and new rhs (similar to augmented assignment)
# get new rhs from augmented assignment
new_rhs: PsExpression = binop_str_to_expr(expr.op, new_lhs.clone(), rhs)
# match for reduction operation and set neutral init_val
new_rhs: PsExpression
init_val: PsExpression
match expr.op:
case "+":
init_val = PsConstantExpr(PsConstant(0, dtype))
new_rhs = add(new_lhs.clone(), rhs)
case "-":
init_val = PsConstantExpr(PsConstant(0, dtype))
new_rhs = sub(new_lhs.clone(), rhs)
case "*":
init_val = PsConstantExpr(PsConstant(1, dtype))
new_rhs = mul(new_lhs.clone(), rhs)
case "min":
init_val = PsCall(PsMathFunction(NumericLimitsFunctions.Max), [])
init_val.dtype = dtype
new_rhs = PsCall(PsMathFunction(MathFunctions.Min), [new_lhs.clone(), rhs])
case "max":
init_val = PsCall(PsMathFunction(NumericLimitsFunctions.Min), [])
init_val.dtype = dtype
new_rhs = PsCall(PsMathFunction(MathFunctions.Max), [new_lhs.clone(), rhs])
case _:
raise FreezeError(f"Unsupported reduced assignment: {expr.op}.")
......
......@@ -7,7 +7,8 @@ from .config import CreateKernelConfig, OpenMpConfig, VectorizationConfig, AUTO
from .kernel import Kernel, GpuKernel, GpuThreadsRange
from .properties import PsSymbolProperty, FieldShape, FieldStride, FieldBasePtr, ReductionPointerVariable
from .parameters import Parameter
from ..backend.ast.expressions import PsSymbolExpr, PsMemAcc, PsConstantExpr
from ..backend.ast.expressions import PsSymbolExpr, PsMemAcc, PsConstantExpr, PsExpression
from ..sympyextensions.binop_mapping import binop_str_to_expr
from ..types import create_numeric_type, PsIntegerType, PsScalarType
......@@ -159,9 +160,9 @@ class DefaultKernelCreationDriver:
# Write back result to reduction target variable
for red_ptr, prop in self._ctx.reduction_pointer_symbols.items():
ptr_access = PsMemAcc(PsSymbolExpr(red_ptr), PsConstantExpr(PsConstant(0, self._ctx.index_dtype)))
kernel_ast.statements += [PsAssignment(
PsMemAcc(PsSymbolExpr(red_ptr), PsConstantExpr(PsConstant(0, self._ctx.index_dtype))),
PsSymbolExpr(prop.local_symbol))]
ptr_access, binop_str_to_expr(prop.op, ptr_access, PsSymbolExpr(prop.local_symbol)))]
# Target-Specific optimizations
if self._cfg.target.is_cpu():
......
from operator import truediv, mul, sub, add
from src.pystencils.backend.ast.expressions import PsCall, PsExpression
from src.pystencils.backend.exceptions import FreezeError
from src.pystencils.backend.functions import MathFunctions, PsMathFunction
_available_operator_interface: set[str] = {'+', '-', '*', '/'}
def binop_str_to_expr(op: str, op1, op2) -> PsExpression:
if op in _available_operator_interface:
match op:
case "+":
operator = add
case "-":
operator = sub
case "*":
operator = mul
case "/":
operator = truediv
case _:
raise FreezeError(f"Found unsupported operation type for compound assignments: {op}.")
return operator(op1, op2)
else:
match op:
case "min":
return PsCall(PsMathFunction(MathFunctions.Min), [op1, op2])
case "max":
return PsCall(PsMathFunction(MathFunctions.Max), [op1, op2])
case _:
raise FreezeError(f"Found unsupported operation type for compound assignments: {op}.")
......@@ -6,21 +6,22 @@ import cupy as cp
import pystencils as ps
from pystencils.sympyextensions import reduced_assign
INIT=2
SIZE=15
INIT_W = 5
INIT_ARR = 2
SIZE = 15
SOLUTION = {
"+": INIT * SIZE,
"-": INIT * -SIZE,
"*": INIT**SIZE,
"min": INIT,
"max": INIT
"+": INIT_W + INIT_ARR * SIZE,
"-": INIT_W - INIT_ARR * -SIZE,
"*": INIT_W * INIT_ARR ** SIZE,
"min": min(INIT_W, INIT_ARR),
"max": max(INIT_W, INIT_ARR),
}
@pytest.mark.parametrize('dtype', ["float64"])
@pytest.mark.parametrize("op", ["+", "-", "*", "min", "max"])
@pytest.mark.parametrize("op", ["+", "-", "*"]) #, "min", "max"]) # TODO: min/max broken due to error in BasePrinter
def test_reduction(dtype, op):
gpu_avail = True
gpu_avail = False
x = ps.fields(f'x: {dtype}[1d]')
w = sp.Symbol("w")
......@@ -32,13 +33,13 @@ def test_reduction(dtype, op):
config = ps.CreateKernelConfig(target=ps.Target.GPU) if gpu_avail else ps.CreateKernelConfig(cpu_openmp=True)
ast_reduction = ps.create_kernel([reduction_assignment], config, default_dtype=dtype)
#code_reduction = ps.get_code_str(ast_reduction)
# code_reduction = ps.get_code_str(ast_reduction)
kernel_reduction = ast_reduction.compile()
ps.show_code(ast_reduction)
array = np.full((SIZE,), INIT, dtype=dtype)
reduction_array = np.zeros(1, dtype=dtype)
array = np.full((SIZE,), INIT_ARR, dtype=dtype)
reduction_array = np.full((1,), INIT_W, dtype=dtype)
if gpu_avail:
array_gpu = cp.asarray(array)
......@@ -48,4 +49,4 @@ def test_reduction(dtype, op):
assert np.allclose(reduction_array_gpu.get(), SOLUTION[op])
else:
kernel_reduction(x=array, w=reduction_array)
assert np.allclose(reduction_array, SOLUTION[op])
\ No newline at end of file
assert np.allclose(reduction_array, SOLUTION[op])
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