def _test_quantitatively(sdfg): graph = sdfg.nodes()[0] A = np.random.rand(N.get()).astype(np.float64) B = np.random.rand(N.get()).astype(np.float64) C1 = np.random.rand(N.get()).astype(np.float64) C2 = np.random.rand(N.get()).astype(np.float64) D1 = np.random.rand(N.get()).astype(np.float64) D2 = np.random.rand(N.get()).astype(np.float64) csdfg = sdfg.compile() csdfg(A=A, B=B, C=C1, D=D1, N=N) del csdfg subgraph = SubgraphView(graph, [node for node in graph.nodes()]) me = MultiExpansion(subgraph) assert me.can_be_applied(sdfg, subgraph) == True me.apply(sdfg) sf = SubgraphFusion(subgraph) assert sf.can_be_applied(sdfg, subgraph) == True sf.apply(sdfg) csdfg = sdfg.compile() csdfg(A=A, B=B, C=C2, D=D2, N=N) assert np.allclose(C1, C2) assert np.allclose(D1, D2)
def test_quantitatively(sdfg): graph = sdfg.nodes()[0] A = np.random.rand(N.get()).astype(np.float64) B = np.random.rand(N.get()).astype(np.float64) C1 = np.random.rand(N.get()).astype(np.float64) C2 = np.random.rand(N.get()).astype(np.float64) D1 = np.random.rand(N.get()).astype(np.float64) D2 = np.random.rand(N.get()).astype(np.float64) csdfg = sdfg.compile() csdfg(A=A, B=B, C=C1, D=D1, N=N) subgraph = SubgraphView(graph, [node for node in graph.nodes()]) expansion = MultiExpansion() fusion = SubgraphFusion() assert expansion.match(sdfg, subgraph) == True expansion.apply(sdfg, subgraph) assert fusion.match(sdfg, subgraph) == True fusion.apply(sdfg, subgraph) csdfg = sdfg.compile() csdfg(A=A, B=B, C=C2, D=D2, N=N) assert np.allclose(C1, C2) assert np.allclose(D1, D2)
def test_p1(): N.set(20) M.set(30) O.set(50) P.set(40) Q.set(42) R.set(25) sdfg = subgraph_fusion_parallel.to_sdfg() sdfg.simplify() state = sdfg.nodes()[0] A = np.random.rand(N.get()).astype(np.float64) B = np.random.rand(M.get()).astype(np.float64) C = np.random.rand(O.get()).astype(np.float64) D = np.random.rand(M.get()).astype(np.float64) E = np.random.rand(N.get()).astype(np.float64) F = np.random.rand(P.get()).astype(np.float64) G = np.random.rand(M.get()).astype(np.float64) H = np.random.rand(P.get()).astype(np.float64) I = np.random.rand(N.get()).astype(np.float64) J = np.random.rand(R.get()).astype(np.float64) X = np.random.rand(N.get()).astype(np.float64) Y = np.random.rand(M.get()).astype(np.float64) Z = np.random.rand(P.get()).astype(np.float64) csdfg = sdfg.compile() csdfg(A=A, B=B, C=C, D=D, E=E, F=F, G=G, H=H, I=I, J=J, X=X, Y=Y, Z=Z,\ N=N, M=M, O=O, P=P, R=R,Q=Q) del csdfg subgraph = SubgraphView(state, [node for node in state.nodes()]) expansion = MultiExpansion() expansion.setup_match(subgraph) fusion = SubgraphFusion() fusion.setup_match(subgraph) me = MultiExpansion() me.setup_match(subgraph) assert me.can_be_applied(sdfg, subgraph) me.apply(sdfg) sf = SubgraphFusion() sf.setup_match(subgraph) assert sf.can_be_applied(sdfg, subgraph) sf.apply(sdfg) csdfg = sdfg.compile() csdfg(A=A, B=B, C=C, D=D, E=E, F=F, G=G, H=H, I=I, J=J, X=X, Y=Y, Z=Z,\ N=N, M=M, O=O, P=P, R=R,Q=Q) print("PASS")
def can_be_applied(self, sdfg: SDFG, subgraph: SubgraphView) -> bool: graph = subgraph.graph if self.allow_expansion == True: subgraph_fusion = SubgraphFusion() subgraph_fusion.setup_match(subgraph) if subgraph_fusion.can_be_applied(sdfg, subgraph): # try w/o copy first return True expansion = MultiExpansion() expansion.setup_match(subgraph) expansion.permutation_only = not self.expansion_split if expansion.can_be_applied(sdfg, subgraph): # deepcopy graph_indices = [ i for (i, n) in enumerate(graph.nodes()) if n in subgraph ] sdfg_copy = copy.deepcopy(sdfg) graph_copy = sdfg_copy.nodes()[sdfg.nodes().index(graph)] subgraph_copy = SubgraphView( graph_copy, [graph_copy.nodes()[i] for i in graph_indices]) expansion.sdfg_id = sdfg_copy.sdfg_id ##sdfg_copy.apply_transformations(MultiExpansion, states=[graph]) #expansion = MultiExpansion() #expansion.setup_match(subgraph_copy) expansion.apply(sdfg_copy) subgraph_fusion = SubgraphFusion() subgraph_fusion.setup_match(subgraph_copy) if subgraph_fusion.can_be_applied(sdfg_copy, subgraph_copy): return True stencil_tiling = StencilTiling() stencil_tiling.setup_match(subgraph_copy) if self.allow_tiling and stencil_tiling.can_be_applied( sdfg_copy, subgraph_copy): return True else: subgraph_fusion = SubgraphFusion() subgraph_fusion.setup_match(subgraph) if subgraph_fusion.can_be_applied(sdfg, subgraph): return True if self.allow_tiling == True: stencil_tiling = StencilTiling() stencil_tiling.setup_match(subgraph) if stencil_tiling.can_be_applied(sdfg, subgraph): return True return False
def apply(self, sdfg): subgraph = self.subgraph_view(sdfg) graph = subgraph.graph scope_dict = graph.scope_dict() map_entries = helpers.get_outermost_scope_maps(sdfg, graph, subgraph, scope_dict) first_entry = next(iter(map_entries)) if self.allow_expansion: expansion = MultiExpansion() expansion.setup_match(subgraph, self.sdfg_id, self.state_id) expansion.permutation_only = not self.expansion_split if expansion.can_be_applied(sdfg, subgraph): expansion.apply(sdfg) sf = SubgraphFusion() sf.setup_match(subgraph, self.sdfg_id, self.state_id) if sf.can_be_applied(sdfg, self.subgraph_view(sdfg)): # set SubgraphFusion properties sf.debug = self.debug sf.transient_allocation = self.transient_allocation sf.schedule_innermaps = self.schedule_innermaps sf.apply(sdfg) self._global_map_entry = sf._global_map_entry return elif self.allow_tiling == True: st = StencilTiling() st.setup_match(subgraph, self.sdfg_id, self.state_id) if st.can_be_applied(sdfg, self.subgraph_view(sdfg)): # set StencilTiling properties st.debug = self.debug st.unroll_loops = self.stencil_unroll_loops st.strides = self.stencil_strides st.apply(sdfg) # StencilTiling: update nodes new_entries = st._outer_entries subgraph = helpers.subgraph_from_maps(sdfg, graph, new_entries) sf = SubgraphFusion() sf.setup_match(subgraph, self.sdfg_id, self.state_id) # set SubgraphFusion properties sf.debug = self.debug sf.transient_allocation = self.transient_allocation sf.schedule_innermaps = self.schedule_innermaps sf.apply(sdfg) self._global_map_entry = sf._global_map_entry return warnings.warn("CompositeFusion::Apply did not perform as expected")
def test_p1(): N.set(20) M.set(30) O.set(50) P.set(40) Q.set(42) R.set(25) sdfg = program.to_sdfg() sdfg.apply_strict_transformations() state = sdfg.nodes()[0] A = np.random.rand(N.get()).astype(np.float64) B = np.random.rand(M.get()).astype(np.float64) C = np.random.rand(O.get()).astype(np.float64) D = np.random.rand(M.get()).astype(np.float64) E = np.random.rand(N.get()).astype(np.float64) F = np.random.rand(P.get()).astype(np.float64) G = np.random.rand(M.get()).astype(np.float64) H = np.random.rand(P.get()).astype(np.float64) I = np.random.rand(N.get()).astype(np.float64) J = np.random.rand(R.get()).astype(np.float64) X = np.random.rand(N.get()).astype(np.float64) Y = np.random.rand(M.get()).astype(np.float64) Z = np.random.rand(P.get()).astype(np.float64) csdfg = sdfg.compile() csdfg(A=A, B=B, C=C, D=D, E=E, F=F, G=G, H=H, I=I, J=J, X=X, Y=Y, Z=Z,\ N=N, M=M, O=O, P=P, R=R,Q=Q) del csdfg subgraph = SubgraphView(state, [node for node in state.nodes()]) expansion = MultiExpansion(subgraph) fusion = SubgraphFusion(subgraph) assert MultiExpansion.can_be_applied(sdfg, subgraph) expansion.apply(sdfg) assert SubgraphFusion.can_be_applied(sdfg, subgraph) fusion.apply(sdfg) csdfg = sdfg.compile() csdfg(A=A, B=B, C=C, D=D, E=E, F=F, G=G, H=H, I=I, J=J, X=X, Y=Y, Z=Z,\ N=N, M=M, O=O, P=P, R=R,Q=Q) print("PASS")