Merge branch 'master' of i10git.cs.fau.de:software/pystencils

pystencils/astnodes.py

@@ -65,7 +65,6 @@ class Conditional(Node):
                  false_block: Optional['Block'] = None) -> None:
         super(Conditional, self).__init__(parent=None)
 
-        assert condition_expr.is_Boolean or condition_expr.is_Relational
         self.condition_expr = condition_expr
 
         def handle_child(c):
@@ -227,6 +226,20 @@ class KernelFunction(Node):
         return '{0} {1}({2})'.format(type(self).__name__, self.function_name, params)
 
 
+class SkipIteration(Node):
+    @property
+    def args(self):
+        return []
+
+    @property
+    def symbols_defined(self):
+        return set()
+
+    @property
+    def undefined_symbols(self):
+        return set()
+
+
 class Block(Node):
     def __init__(self, nodes: List[Node]):
         super(Block, self).__init__()
@@ -628,3 +641,8 @@ class TemporaryMemoryFree(Node):
     @property
     def args(self):
         return []
+
+
+def early_out(condition):
+    from pystencils.cpu.vectorization import vec_all
+    return Conditional(vec_all(condition), Block([SkipIteration()]))

pystencils/backends/cbackend.py

@@ -4,6 +4,7 @@ from sympy.core import S
 from typing import Set
 from sympy.printing.ccode import C89CodePrinter
 
+from pystencils.cpu.vectorization import vec_any, vec_all
 from pystencils.fast_approximation import fast_division, fast_sqrt, fast_inv_sqrt
 
 try:
@@ -97,8 +98,7 @@ class PrintNode(CustomCodeNode):
 # noinspection PyPep8Naming
 class CBackend:
 
-    def __init__(self, sympy_printer=None,
-                 signature_only=False, vector_instruction_set=None, dialect='c'):
+    def __init__(self, sympy_printer=None, signature_only=False, vector_instruction_set=None, dialect='c'):
         if sympy_printer is None:
             if vector_instruction_set is not None:
                 self.sympy_printer = VectorizedCustomSympyPrinter(vector_instruction_set, dialect)
@@ -194,10 +194,19 @@ class CBackend:
         align = 64
         return "free(%s - %d);" % (self.sympy_printer.doprint(node.symbol.name), node.offset(align))
 
+    def _print_SkipIteration(self, _):
+        if self._dialect == 'cuda':
+            return "return;"
+        else:
+            return "continue;"
+
     def _print_CustomCodeNode(self, node):
         return node.get_code(self._dialect, self._vector_instruction_set)
 
     def _print_Conditional(self, node):
+        cond_type = get_type_of_expression(node.condition_expr)
+        if isinstance(cond_type, VectorType):
+            raise ValueError("Problem with Conditional inside vectorized loop - use vec_any or vec_all")
         condition_expr = self.sympy_printer.doprint(node.condition_expr)
         true_block = self._print_Block(node.true_block)
         result = "if (%s)\n%s " % (condition_expr, true_block)
@@ -274,6 +283,8 @@ class CustomSympyPrinter(CCodePrinter):
                 return "__fsqrt_rn(%s)" % tuple(self._print(a) for a in expr.args)
             else:
                 return "({})".format(self._print(sp.sqrt(expr.args[0])))
+        elif isinstance(expr, vec_any) or isinstance(expr, vec_all):
+            return self._print(expr.args[0])
         elif isinstance(expr, fast_inv_sqrt):
             if self._dialect == "cuda":
                 return "__frsqrt_rn(%s)" % tuple(self._print(a) for a in expr.args)
@@ -328,7 +339,8 @@ class VectorizedCustomSympyPrinter(CustomSympyPrinter):
         elif expr.func == fast_division:
             result = self._scalarFallback('_print_Function', expr)
             if not result:
-                return self.instruction_set['/'].format(self._print(expr.args[0]), self._print(expr.args[1]))
+                result = self.instruction_set['/'].format(self._print(expr.args[0]), self._print(expr.args[1]))
+            return result
         elif expr.func == fast_sqrt:
             return "({})".format(self._print(sp.sqrt(expr.args[0])))
         elif expr.func == fast_inv_sqrt:
@@ -338,6 +350,19 @@ class VectorizedCustomSympyPrinter(CustomSympyPrinter):
                     return self.instruction_set['rsqrt'].format(self._print(expr.args[0]))
                 else:
                     return "({})".format(self._print(1 / sp.sqrt(expr.args[0])))
+        elif isinstance(expr, vec_any):
+            expr_type = get_type_of_expression(expr.args[0])
+            if type(expr_type) is not VectorType:
+                return self._print(expr.args[0])
+            else:
+                return self.instruction_set['any'].format(self._print(expr.args[0]))
+        elif isinstance(expr, vec_all):
+            expr_type = get_type_of_expression(expr.args[0])
+            if type(expr_type) is not VectorType:
+                return self._print(expr.args[0])
+            else:
+                return self.instruction_set['all'].format(self._print(expr.args[0]))
+
         return super(VectorizedCustomSympyPrinter, self)._print_Function(expr)
 
     def _print_And(self, expr):

pystencils/backends/simd_instruction_sets.py

@@ -98,11 +98,15 @@ def get_vector_instruction_set(data_type='double', instruction_set='avx'):
     result['bool'] = "__m%dd" % (bit_width,)
 
     result['headers'] = headers[instruction_set]
+    result['any'] = "%s_movemask_%s({0}) > 0" % (pre, suf)
+    result['all'] = "%s_movemask_%s({0}) == 0xF" % (pre, suf)
 
     if instruction_set == 'avx512':
         size = 8 if data_type == 'double' else 16
         result['&'] = '_kand_mask%d({0}, {1})' % (size,)
         result['|'] = '_kor_mask%d({0}, {1})' % (size,)
+        result['any'] = '!_ktestz_mask%d_u8({0}, {0})' % (size, )
+        result['all'] = '_kortestc_mask%d_u8({0}, {0})' % (size, )
         result['blendv'] = '%s_mask_blend_%s({2}, {0}, {1})' % (pre, suf)
         result['rsqrt'] = "_mm512_rsqrt14_%s({0})" % (suf,)
         result['bool'] = "__mmask%d" % (size,)

pystencils/cpu/vectorization.py

@@ -12,6 +12,16 @@ from pystencils.transformations import cut_loop, filtered_tree_iteration, replac
 from pystencils.field import Field
 
 
+# noinspection PyPep8Naming
+class vec_any(sp.Function):
+    nargs = (1, )
+
+
+# noinspection PyPep8Naming
+class vec_all(sp.Function):
+    nargs = (1, )
+
+
 def vectorize(kernel_ast: ast.KernelFunction, instruction_set: str = 'avx',
               assume_aligned: bool = False, nontemporal: Union[bool, Container[Union[str, Field]]] = False,
               assume_inner_stride_one: bool = False, assume_sufficient_line_padding: bool = True):
@@ -119,7 +129,7 @@ def vectorize_inner_loops_and_adapt_load_stores(ast_node, vector_width, assume_a
 def insert_vector_casts(ast_node):
     """Inserts necessary casts from scalar values to vector values."""
 
-    handled_functions = (sp.Add, sp.Mul, fast_division, fast_sqrt, fast_inv_sqrt)
+    handled_functions = (sp.Add, sp.Mul, fast_division, fast_sqrt, fast_inv_sqrt, vec_any, vec_all)
 
     def visit_expr(expr):
 
@@ -182,6 +192,11 @@ def insert_vector_casts(ast_node):
                     lhs_type = assignment.lhs.args[1]
                     if type(lhs_type) is VectorType and type(rhs_type) is not VectorType:
                         assignment.rhs = cast_func(assignment.rhs, lhs_type)
+            elif isinstance(arg, ast.Conditional):
+                arg.condition_expr = fast_subs(arg.condition_expr, substitution_dict,
+                                               skip=lambda e: isinstance(e, ast.ResolvedFieldAccess))
+                arg.condition_expr = visit_expr(arg.condition_expr)
+                visit_node(arg, substitution_dict)
             else:
                 visit_node(arg, substitution_dict)
 

pystencils/data_types.py

 import ctypes
 import sympy as sp
 import numpy as np
+
 try:
     import llvmlite.ir as ir
 except ImportError as e:
@@ -311,6 +312,8 @@ def collate_types(types):
 @memorycache(maxsize=2048)
 def get_type_of_expression(expr):
     from pystencils.astnodes import ResolvedFieldAccess
+    from pystencils.cpu.vectorization import vec_all, vec_any
+
     expr = sp.sympify(expr)
     if isinstance(expr, sp.Integer):
         return create_type("int")
@@ -324,6 +327,8 @@ def get_type_of_expression(expr):
         raise ValueError("All symbols inside this expression have to be typed! ", str(expr))
     elif isinstance(expr, cast_func):
         return expr.args[1]
+    elif isinstance(expr, vec_any) or isinstance(expr, vec_all):
+        return create_type("bool")
     elif hasattr(expr, 'func') and expr.func == sp.Piecewise:
         collated_result_type = collate_types(tuple(get_type_of_expression(a[0]) for a in expr.args))
         collated_condition_type = collate_types(tuple(get_type_of_expression(a[1]) for a in expr.args))

pystencils/fd/finitedifferences.py

@@ -322,7 +322,7 @@ def discretize_center(term, symbols_to_field_dict, dx, dim=3):
         for d in range(dim):
             up, down = __up_down_offsets(d, dim)
             substitutions.update({g[d][i]: (field[up](i) - field[down](i)) / dx / 2 for i in range(len(symbols))})
-    return term.subs(substitutions)
+    return fast_subs(term, substitutions)
 
 
 def discretize_staggered(term, symbols_to_field_dict, coordinate, coordinate_offset, dx, dim=3):

pystencils/kernelcreation.py

@@ -6,7 +6,8 @@ from pystencils.astnodes import LoopOverCoordinate, Conditional, Block, SympyAss
 from pystencils.cpu.vectorization import vectorize
 from pystencils.simp.assignment_collection import AssignmentCollection
 from pystencils.gpucuda.indexing import indexing_creator_from_params
-from pystencils.transformations import remove_conditionals_in_staggered_kernel, loop_blocking
+from pystencils.transformations import remove_conditionals_in_staggered_kernel, loop_blocking, \
+    move_constants_before_loop
 
 
 def create_kernel(assignments, target='cpu', data_type="double", iteration_slice=None, ghost_layers=None,
@@ -248,6 +249,7 @@ def create_staggered_kernel(staggered_field, expressions, subexpressions=(), tar
 
     if target == 'cpu':
         remove_conditionals_in_staggered_kernel(ast)
+        move_constants_before_loop(ast)
         if blocking:
             loop_blocking(ast, blocking)
         if cpu_vectorize_info is True:

pystencils/placeholder_function.py

+import sympy as sp
+from typing import List
+from pystencils.assignment import Assignment
+from pystencils.astnodes import Node
+from pystencils.transformations import generic_visit
+
+
+class PlaceholderFunction:
+    pass
+
+
+def to_placeholder_function(expr, name):
+    """Replaces an expression by a sympy function.
+
+    - replacing an expression with just a symbol would lead to problem when calculating derivatives
+    - placeholder functions get rid of this problem
+
+    Examples:
+        >>> x, t = sp.symbols("x, t")
+        >>> temperature = x**2 + t**4 # some 'complicated' dependency
+        >>> temperature_placeholder = to_placeholder_function(temperature, 'T')
+        >>> diffusivity = temperature_placeholder + 42 * t
+        >>> sp.diff(diffusivity, t)  # returns a symbol instead of the computed derivative
+        _dT_dt + 42
+        >>> result, subexpr = remove_placeholder_functions(diffusivity)
+        >>> result
+        T + 42*t
+        >>> subexpr
+        [Assignment(T, t**4 + x**2), Assignment(_dT_dt, 4*t**3), Assignment(_dT_dx, 2*x)]
+
+    """
+    symbols = list(expr.atoms(sp.Symbol))
+    symbols.sort(key=lambda e: e.name)
+    derivative_symbols = [sp.Symbol("_d{}_d{}".format(name, s.name)) for s in symbols]
+    derivatives = [sp.diff(expr, s) for s in symbols]
+
+    assignments = [Assignment(sp.Symbol(name), expr)]
+    assignments += [Assignment(symbol, derivative)
+                    for symbol, derivative in zip(derivative_symbols, derivatives)
+                    if not derivative.is_constant()]
+
+    def fdiff(_, index):
+        result = derivatives[index - 1]
+        return result if result.is_constant() else derivative_symbols[index - 1]
+
+    func = type(name, (sp.Function, PlaceholderFunction),
+                {'fdiff': fdiff,
+                 'value': sp.Symbol(name),
+                 'subexpressions': assignments,
+                 'nargs': len(symbols)})
+    return func(*symbols)
+
+
+def remove_placeholder_functions(expr):
+    subexpressions = []
+
+    def visit(e):
+        if isinstance(e, Node):
+            return e
+        elif isinstance(e, PlaceholderFunction):
+            for se in e.subexpressions:
+                if se.lhs not in {a.lhs for a in subexpressions}:
+                    subexpressions.append(se)
+            return e.value
+        else:
+            new_args = [visit(a) for a in e.args]
+            return e.func(*new_args) if new_args else e
+
+    return generic_visit(expr, visit), subexpressions
+
+
+def prepend_placeholder_functions(assignments: List[Assignment]):
+    result, subexpressions = remove_placeholder_functions(assignments)
+    return subexpressions + result

pystencils/transformations.py

@@ -7,7 +7,6 @@ import hashlib
 import sympy as sp
 from sympy.logic.boolalg import Boolean
 from sympy.tensor import IndexedBase
-
 from pystencils.simp.assignment_collection import AssignmentCollection
 from pystencils.assignment import Assignment
 from pystencils.field import Field, FieldType
@@ -514,6 +513,13 @@ def resolve_field_accesses(ast_node, read_only_field_names=set(),
             assert type(enclosing_block) is ast.Block
             sub_ast.lhs = visit_sympy_expr(sub_ast.lhs, enclosing_block, sub_ast)
             sub_ast.rhs = visit_sympy_expr(sub_ast.rhs, enclosing_block, sub_ast)
+        elif isinstance(sub_ast, ast.Conditional):
+            enclosing_block = sub_ast.parent
+            assert type(enclosing_block) is ast.Block
+            sub_ast.condition_expr = visit_sympy_expr(sub_ast.condition_expr, enclosing_block, sub_ast)
+            visit_node(sub_ast.true_block)
+            if sub_ast.false_block:
+                visit_node(sub_ast.false_block)
         else:
             for i, a in enumerate(sub_ast.args):
                 visit_node(a)
@@ -545,7 +551,7 @@ def move_constants_before_loop(ast_node):
                 last_block_child = prev_element
 
             if isinstance(element, ast.Conditional):
-                critical_symbols = element.condition_expr.atoms(sp.Symbol)
+                break
             else:
                 critical_symbols = element.symbols_defined
             if node.undefined_symbols.intersection(critical_symbols):
@@ -1000,6 +1006,9 @@ def typing_from_sympy_inspection(eqs, default_type="double"):
         elif isinstance(eq, ast.Node) and not isinstance(eq, ast.SympyAssignment):
             continue
         else:
+            from pystencils.cpu.vectorization import vec_all, vec_any
+            if isinstance(eq.rhs, vec_all) or isinstance(eq.rhs, vec_any):
+                result[eq.lhs.name] = "bool"
             # problematic case here is when rhs is a symbol: then it is impossible to decide here without
             # further information what type the left hand side is - default fallback is the dict value then
             if isinstance(eq.rhs, Boolean) and not isinstance(eq.rhs, sp.Symbol):

pystencils_tests/test_conditional_vec.py

+import pystencils as ps
+import sympy as sp
+import numpy as np
+from pystencils.astnodes import Conditional, Block
+from pystencils.cpu.vectorization import vec_all, vec_any
+
+
+def test_vec_any():
+    data_arr = np.zeros((15, 15))
+
+    data_arr[3:9, 2:7] = 1.0
+    data = ps.fields("data: double[2D]", data=data_arr)
+
+    c = [
+        ps.Assignment(sp.Symbol("t1"), vec_any(data.center() > 0.0)),
+        Conditional(vec_any(data.center() > 0.0), Block([
+            ps.Assignment(data.center(), 2.0)
+        ]))
+    ]
+    ast = ps.create_kernel(c, target='cpu',
+                           cpu_vectorize_info={'instruction_set': 'avx'})
+    kernel = ast.compile()
+    kernel(data=data_arr)
+    np.testing.assert_equal(data_arr[3:9, 0:8], 2.0)
+
+
+def test_vec_all():
+    data_arr = np.zeros((15, 15))
+
+    data_arr[3:9, 2:7] = 1.0
+    data = ps.fields("data: double[2D]", data=data_arr)
+
+    c = [
+        Conditional(vec_all(data.center() > 0.0), Block([
+            ps.Assignment(data.center(), 2.0)
+        ]))
+    ]
+    ast = ps.create_kernel(c, target='cpu',
+                           cpu_vectorize_info={'instruction_set': 'avx'})
+    kernel = ast.compile()
+    before = data_arr.copy()
+    kernel(data=data_arr)
+    np.testing.assert_equal(data_arr, before)