def apply(self, sdfg): def gnode(nname): return graph.nodes()[self.subgraph[nname]] graph = sdfg.nodes()[self.state_id] in_array = gnode(RedundantArray._in_array) out_array = gnode(RedundantArray._out_array) for e in graph.in_edges(in_array): # Modify all incoming edges to point to out_array path = graph.memlet_path(e) for pe in path: if pe.data.data == in_array.data: pe.data.data = out_array.data # Redirect edge to out_array graph.remove_edge(e) graph.add_edge(e.src, e.src_conn, out_array, e.dst_conn, e.data) # Finally, remove in_array node graph.remove_node(in_array) # TODO: Should the array be removed from the SDFG? # del sdfg.arrays[in_array] if Config.get_bool("debugprint"): RedundantArray._arrays_removed += 1
def apply(self, sdfg): def gnode(nname): return graph.nodes()[self.subgraph[nname]] graph = sdfg.nodes()[self.state_id] in_array = gnode(RedundantSecondArray._in_array) out_array = gnode(RedundantSecondArray._out_array) # We assume the following pattern: A -- e1 --> B -- e2 --> others # 1. Get edge e1 and extract subsets for arrays A and B e1 = graph.edges_between(in_array, out_array)[0] a_subset, b1_subset = _validate_subsets(e1, sdfg.arrays) # 2. Iterate over the e2 edges and traverse the memlet tree for e2 in graph.out_edges(out_array): path = graph.memlet_tree(e2) for e3 in path: # 2-a. Extract subsets for array B and others b3_subset, other_subset = _validate_subsets( e3, sdfg.arrays, src_name=out_array.data) # 2-b. Modify memlet to match array A. Example: # A -- (0, a:b)/(c:c+b) --> B -- (c+d)/None --> others # A -- (0, a+d)/None --> others e3.data.data = in_array.data # (c+d) - (c:c+b) = (d) b3_subset.offset(b1_subset, negative=True) # (0, a:b)(d) = (0, a+d) (or offset for indices) if isinstance(a_subset, subsets.Indices): tmp = copy.deepcopy(a_subset) tmp.offset(b3_subset, negative=False) e3.data.subset = tmp else: e3.data.subset = a_subset.compose(b3_subset) e3.data.other_subset = other_subset # 2-c. Remove edge and add new one graph.remove_edge(e2) graph.add_edge(in_array, e2.src_conn, e2.dst, e2.dst_conn, e2.data) # Finally, remove out_array node graph.remove_node(out_array) # TODO: Should the array be removed from the SDFG? # del sdfg.arrays[out_array] if Config.get_bool("debugprint"): RedundantSecondArray._arrays_removed += 1
def _make_view(self, sdfg: SDFG, graph: SDFGState, in_array: nodes.AccessNode, out_array: nodes.AccessNode, e1: graph.MultiConnectorEdge[mm.Memlet], b_subset: subsets.Subset, b_dims_to_pop: typing.List[int]): in_desc = sdfg.arrays[in_array.data] out_desc = sdfg.arrays[out_array.data] # NOTE: We do not want to create another view, if the immediate # ancestors of in_array are views as well. We just remove it. in_ancestors_desc = [ e.src.desc(sdfg) if isinstance(e.src, nodes.AccessNode) else None for e in graph.in_edges(in_array) ] if all([ desc and isinstance(desc, data.View) for desc in in_ancestors_desc ]): for e in graph.in_edges(in_array): a_subset, _ = _validate_subsets(e, sdfg.arrays) graph.add_edge( e.src, e.src_conn, out_array, None, mm.Memlet(out_array.data, subset=b_subset, other_subset=a_subset, wcr=e1.data.wcr, wcr_nonatomic=e1.data.wcr_nonatomic)) graph.remove_edge(e) graph.remove_edge(e1) graph.remove_node(in_array) if in_array.data in sdfg.arrays: del sdfg.arrays[in_array.data] return view_strides = in_desc.strides if (b_dims_to_pop and len(b_dims_to_pop) == len(out_desc.shape) - len(in_desc.shape)): view_strides = [ s for i, s in enumerate(out_desc.strides) if i not in b_dims_to_pop ] sdfg.arrays[in_array.data] = data.View( in_desc.dtype, in_desc.shape, True, in_desc.allow_conflicts, out_desc.storage, out_desc.location, view_strides, in_desc.offset, out_desc.may_alias, dtypes.AllocationLifetime.Scope, in_desc.alignment, in_desc.debuginfo, in_desc.total_size)
def apply(self, sdfg): def gnode(nname): return graph.nodes()[self.subgraph[nname]] graph = sdfg.nodes()[self.state_id] in_array = self.in_array(sdfg) out_array = self.out_array(sdfg) in_desc = sdfg.arrays[in_array.data] out_desc = sdfg.arrays[out_array.data] # If arrays are not of the same shape, modify first array to reshape # instead of removing it if len(in_desc.shape) != len(out_desc.shape) or any( i != o for i, o in zip(in_desc.shape, out_desc.shape)): sdfg.arrays[in_array.data] = data.View( in_desc.dtype, in_desc.shape, True, in_desc.allow_conflicts, out_desc.storage, out_desc.location, in_desc.strides, in_desc.offset, out_desc.may_alias, out_desc.lifetime, in_desc.alignment, in_desc.debuginfo, in_desc.total_size) return for e in graph.in_edges(in_array): # Modify all incoming edges to point to out_array path = graph.memlet_path(e) for pe in path: if pe.data.data == in_array.data: pe.data.data = out_array.data # Redirect edge to out_array graph.remove_edge(e) graph.add_edge(e.src, e.src_conn, out_array, e.dst_conn, e.data) # Finally, remove in_array node graph.remove_node(in_array) if in_array.data in sdfg.arrays: del sdfg.arrays[in_array.data]
def redirect_edge(graph, edge, new_src=None, new_src_conn=None, new_dst=None, new_dst_conn=None, new_data=None): data = new_data if new_data else edge.data if new_src and new_dst: ret = graph.add_edge(new_src, new_src_conn, new_dst, new_dst_conn, data) graph.remove_edge(edge) elif new_src: ret = graph.add_edge(new_src, new_src_conn, edge.dst, edge.dst_conn, data) graph.remove_edge(edge) elif new_dst: ret = graph.add_edge(edge.src, edge.src_conn, new_dst, new_dst_conn, data) graph.remove_edge(edge) else: pass return ret
def apply(self, sdfg): def gnode(nname): return graph.nodes()[self.subgraph[nname]] graph = sdfg.nodes()[self.state_id] in_array = gnode(RedundantSecondArray._in_array) out_array = gnode(RedundantSecondArray._out_array) in_desc = sdfg.arrays[in_array.data] out_desc = sdfg.arrays[out_array.data] # We assume the following pattern: A -- e1 --> B -- e2 --> others # 1. Get edge e1 and extract subsets for arrays A and B e1 = graph.edges_between(in_array, out_array)[0] a_subset, b1_subset = _validate_subsets(e1, sdfg.arrays) # Find extraneous A or B subset dimensions a_dims_to_pop = [] b_dims_to_pop = [] aset = a_subset popped = [] if a_subset and b1_subset and a_subset.dims() != b1_subset.dims(): a_size = a_subset.size_exact() b_size = b1_subset.size_exact() if a_subset.dims() > b1_subset.dims(): a_dims_to_pop = find_dims_to_pop(a_size, b_size) aset, popped = pop_dims(a_subset, a_dims_to_pop) else: b_dims_to_pop = find_dims_to_pop(b_size, a_size) # If the src subset does not cover the removed array, create a view. if a_subset and any(m != a for m, a in zip(a_subset.size(), out_desc.shape)): # NOTE: We do not want to create another view, if the immediate # successors of out_array are views as well. We just remove it. out_successors_desc = [ e.dst.desc(sdfg) if isinstance(e.dst, nodes.AccessNode) else None for e in graph.out_edges(out_array) ] if all([ desc and isinstance(desc, data.View) for desc in out_successors_desc ]): for e in graph.out_edges(out_array): _, b_subset = _validate_subsets(e, sdfg.arrays) graph.add_edge( in_array, None, e.dst, e.dst_conn, mm.Memlet(in_array.data, subset=a_subset, other_subset=b_subset, wcr=e1.data.wcr, wcr_nonatomic=e1.data.wcr_nonatomic)) graph.remove_edge(e) graph.remove_edge(e1) graph.remove_node(out_array) if out_array.data in sdfg.arrays: del sdfg.arrays[out_array.data] return view_strides = out_desc.strides if (a_dims_to_pop and len(a_dims_to_pop) == len(in_desc.shape) - len(out_desc.shape)): view_strides = [ s for i, s in enumerate(in_desc.strides) if i not in a_dims_to_pop ] sdfg.arrays[out_array.data] = data.View( out_desc.dtype, out_desc.shape, True, out_desc.allow_conflicts, in_desc.storage, in_desc.location, view_strides, out_desc.offset, in_desc.may_alias, dtypes.AllocationLifetime.Scope, out_desc.alignment, out_desc.debuginfo, out_desc.total_size) return # 2. Iterate over the e2 edges and traverse the memlet tree for e2 in graph.out_edges(out_array): path = graph.memlet_tree(e2) wcr = e1.data.wcr wcr_nonatomic = e1.data.wcr_nonatomic for e3 in path: # 2-a. Extract subsets for array B and others b3_subset, other_subset = _validate_subsets( e3, sdfg.arrays, src_name=out_array.data) # 2-b. Modify memlet to match array A. Example: # A -- (0, a:b)/(c:c+b) --> B -- (c+d)/None --> others # A -- (0, a+d)/None --> others e3.data.data = in_array.data # (c+d) - (c:c+b) = (d) b3_subset.offset(b1_subset, negative=True) # (0, a:b)(d) = (0, a+d) (or offset for indices) if b3_subset and b_dims_to_pop: bset, _ = pop_dims(b3_subset, b_dims_to_pop) else: bset = b3_subset e3.data.subset = compose_and_push_back(aset, bset, a_dims_to_pop, popped) # NOTE: This fixes the following case: # A ----> A[subset] ----> ... -----> Tasklet # Tasklet is not data, so it doesn't have an other subset. if isinstance(e3.dst, nodes.AccessNode): e3.data.other_subset = other_subset else: e3.data.other_subset = None wcr = wcr or e3.data.wcr wcr_nonatomic = wcr_nonatomic or e3.data.wcr_nonatomic e3.data.wcr = wcr e3.data.wcr_nonatomic = wcr_nonatomic # 2-c. Remove edge and add new one graph.remove_edge(e2) e2.data.wcr = wcr e2.data.wcr_nonatomic = wcr_nonatomic graph.add_edge(in_array, e2.src_conn, e2.dst, e2.dst_conn, e2.data) # Finally, remove out_array node graph.remove_node(out_array) if out_array.data in sdfg.arrays: try: sdfg.remove_data(out_array.data) except ValueError: # Already in use (e.g., with Views) pass
def apply(self, sdfg): graph = sdfg.nodes()[self.state_id] in_array = self.in_array(sdfg) out_array = self.out_array(sdfg) in_desc = sdfg.arrays[in_array.data] out_desc = sdfg.arrays[out_array.data] # 1. Get edge e1 and extract subsets for arrays A and B e1 = graph.edges_between(in_array, out_array)[0] a1_subset, b_subset = _validate_subsets(e1, sdfg.arrays) # View connected to a view: simple case if (isinstance(in_desc, data.View) and isinstance(out_desc, data.View)): for e in graph.in_edges(in_array): new_memlet = copy.deepcopy(e.data) e.dst_subset = b_subset graph.add_edge(e.src, e.src_conn, out_array, e.dst_conn, new_memlet) graph.remove_node(in_array) if in_array.data in sdfg.arrays: del sdfg.arrays[in_array.data] return # Find extraneous A or B subset dimensions a_dims_to_pop = [] b_dims_to_pop = [] bset = b_subset popped = [] if a1_subset and b_subset and a1_subset.dims() != b_subset.dims(): a_size = a1_subset.size_exact() b_size = b_subset.size_exact() if a1_subset.dims() > b_subset.dims(): a_dims_to_pop = find_dims_to_pop(a_size, b_size) else: b_dims_to_pop = find_dims_to_pop(b_size, a_size) bset, popped = pop_dims(b_subset, b_dims_to_pop) from dace.libraries.standard import Reduce reduction = False for e in graph.in_edges(in_array): if isinstance(e.src, Reduce): reduction = True # If: # 1. A reduce node is involved; # 2. The memlet does not cover the removed array; or # 3. Dimensions are mismatching (all dimensions are popped); # create a view. if reduction or len(a_dims_to_pop) == len(in_desc.shape) or any( m != a for m, a in zip(a1_subset.size(), in_desc.shape)): self._make_view(sdfg, graph, in_array, out_array, e1, b_subset, b_dims_to_pop) return # Validate that subsets are composable. If not, make a view try: for e2 in graph.in_edges(in_array): path = graph.memlet_tree(e2) wcr = e1.data.wcr wcr_nonatomic = e1.data.wcr_nonatomic for e3 in path: # 2-a. Extract subsets for array B and others other_subset, a3_subset = _validate_subsets( e3, sdfg.arrays, dst_name=in_array.data) # 2-b. Modify memlet to match array B. dname = out_array.data src_is_data = False a3_subset.offset(a1_subset, negative=True) if a3_subset and a_dims_to_pop: aset, _ = pop_dims(a3_subset, a_dims_to_pop) else: aset = a3_subset compose_and_push_back(bset, aset, b_dims_to_pop, popped) except (ValueError, NotImplementedError): self._make_view(sdfg, graph, in_array, out_array, e1, b_subset, b_dims_to_pop) return # 2. Iterate over the e2 edges and traverse the memlet tree for e2 in graph.in_edges(in_array): path = graph.memlet_tree(e2) wcr = e1.data.wcr wcr_nonatomic = e1.data.wcr_nonatomic for e3 in path: # 2-a. Extract subsets for array B and others other_subset, a3_subset = _validate_subsets( e3, sdfg.arrays, dst_name=in_array.data) # 2-b. Modify memlet to match array B. dname = out_array.data src_is_data = False a3_subset.offset(a1_subset, negative=True) if a3_subset and a_dims_to_pop: aset, _ = pop_dims(a3_subset, a_dims_to_pop) else: aset = a3_subset dst_subset = compose_and_push_back(bset, aset, b_dims_to_pop, popped) # NOTE: This fixes the following case: # Tasklet ----> A[subset] ----> ... -----> A # Tasklet is not data, so it doesn't have an other subset. if isinstance(e3.src, nodes.AccessNode): if e3.src.data == out_array.data: dname = e3.src.data src_is_data = True src_subset = other_subset else: src_subset = None subset = src_subset if src_is_data else dst_subset other_subset = dst_subset if src_is_data else src_subset e3.data.data = dname e3.data.subset = subset e3.data.other_subset = other_subset wcr = wcr or e3.data.wcr wcr_nonatomic = wcr_nonatomic or e3.data.wcr_nonatomic e3.data.wcr = wcr e3.data.wcr_nonatomic = wcr_nonatomic # 2-c. Remove edge and add new one graph.remove_edge(e2) e2.data.wcr = wcr e2.data.wcr_nonatomic = wcr_nonatomic graph.add_edge(e2.src, e2.src_conn, out_array, e2.dst_conn, e2.data) # Finally, remove in_array node graph.remove_node(in_array) try: if in_array.data in sdfg.arrays: sdfg.remove_data(in_array.data) except ValueError: # Already in use (e.g., with Views) pass
def apply(self, sdfg): graph = sdfg.nodes()[self.state_id] in_array = self.in_array(sdfg) out_array = self.out_array(sdfg) in_desc = sdfg.arrays[in_array.data] out_desc = sdfg.arrays[out_array.data] # 1. Get edge e1 and extract subsets for arrays A and B e1 = graph.edges_between(in_array, out_array)[0] a1_subset, b_subset = _validate_subsets(e1, sdfg.arrays) # Find extraneous A or B subset dimensions a_dims_to_pop = [] b_dims_to_pop = [] bset = b_subset popped = [] if a1_subset and b_subset and a1_subset.dims() != b_subset.dims(): a_size = a1_subset.size_exact() b_size = b_subset.size_exact() if a1_subset.dims() > b_subset.dims(): a_dims_to_pop = find_dims_to_pop(a_size, b_size) else: b_dims_to_pop = find_dims_to_pop(b_size, a_size) bset, popped = pop_dims(b_subset, b_dims_to_pop) from dace.libraries.standard import Reduce reduction = False for e in graph.in_edges(in_array): if isinstance(e.src, Reduce): reduction = True # If the memlet does not cover the removed array, create a view. if reduction or any(m != a for m, a in zip(a1_subset.size(), in_desc.shape)): # NOTE: We do not want to create another view, if the immediate # ancestors of in_array are views as well. We just remove it. in_ancestors_desc = [ e.src.desc(sdfg) if isinstance(e.src, nodes.AccessNode) else None for e in graph.in_edges(in_array) ] if all([ desc and isinstance(desc, data.View) for desc in in_ancestors_desc ]): for e in graph.in_edges(in_array): a_subset, _ = _validate_subsets(e, sdfg.arrays) graph.add_edge( e.src, e.src_conn, out_array, None, mm.Memlet(out_array.data, subset=b_subset, other_subset=a_subset, wcr=e1.data.wcr, wcr_nonatomic=e1.data.wcr.nonatomic)) graph.remove_edge(e) graph.remove_edge(e1) graph.remove_node(in_array) if in_array.data in sdfg.arrays: del sdfg.arrays[in_array.data] return view_strides = in_desc.strides if (b_dims_to_pop and len(b_dims_to_pop) == len(out_desc.shape) - len(in_desc.shape)): view_strides = [ s for i, s in enumerate(out_desc.strides) if i not in b_dims_to_pop ] sdfg.arrays[in_array.data] = data.View( in_desc.dtype, in_desc.shape, True, in_desc.allow_conflicts, out_desc.storage, out_desc.location, view_strides, in_desc.offset, out_desc.may_alias, dtypes.AllocationLifetime.Scope, in_desc.alignment, in_desc.debuginfo, in_desc.total_size) return # 2. Iterate over the e2 edges and traverse the memlet tree for e2 in graph.in_edges(in_array): path = graph.memlet_tree(e2) wcr = e1.data.wcr wcr_nonatomic = e1.data.wcr_nonatomic for e3 in path: # 2-a. Extract subsets for array B and others other_subset, a3_subset = _validate_subsets( e3, sdfg.arrays, dst_name=in_array.data) # 2-b. Modify memlet to match array B. dname = out_array.data src_is_data = False a3_subset.offset(a1_subset, negative=True) if a3_subset and a_dims_to_pop: aset, _ = pop_dims(a3_subset, a_dims_to_pop) else: aset = a3_subset dst_subset = compose_and_push_back(bset, aset, b_dims_to_pop, popped) # NOTE: This fixes the following case: # Tasklet ----> A[subset] ----> ... -----> A # Tasklet is not data, so it doesn't have an other subset. if isinstance(e3.src, nodes.AccessNode): if e3.src.data == out_array.data: dname = e3.src.data src_is_data = True src_subset = other_subset else: src_subset = None subset = src_subset if src_is_data else dst_subset other_subset = dst_subset if src_is_data else src_subset e3.data.data = dname e3.data.subset = subset e3.data.other_subset = other_subset wcr = wcr or e3.data.wcr wcr_nonatomic = wcr_nonatomic or e3.data.wcr_nonatomic e3.data.wcr = wcr e3.data.wcr_nonatomic = wcr_nonatomic # 2-c. Remove edge and add new one graph.remove_edge(e2) e2.data.wcr = wcr e2.data.wcr_nonatomic = wcr_nonatomic graph.add_edge(e2.src, e2.src_conn, out_array, e2.dst_conn, e2.data) # Finally, remove in_array node graph.remove_node(in_array) if in_array.data in sdfg.arrays: del sdfg.arrays[in_array.data]