flow: insert splitters
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5c139511e8
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@ -29,31 +29,32 @@ class Dumper(SimActor):
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super().__init__(dumper_gen(),
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("result", Sink, [("r", BV(32))]))
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def draw(g):
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if len(sys.argv) > 1 and sys.argv[1] == "draw":
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nx.draw(g)
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plt.show()
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def main():
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# Create graph
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g = DataFlowGraph()
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a1 = ComposableSource(g, NumberGen())
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a2 = ComposableSource(g, NumberGen())
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a3 = ComposableSource(g, NumberGen())
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c3 = (a1 + a2)*a3
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g.add_connection(c3.actor_node, Dumper())
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gen1 = ComposableSource(g, NumberGen())
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gen2 = ComposableSource(g, NumberGen())
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ps = gen1 + gen2
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result = ps*gen1 + ps*gen2
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g.add_connection(result.actor_node, Dumper())
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a1.actor_node.actor.name = "gen1"
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a2.actor_node.actor.name = "gen2"
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a3.actor_node.actor.name = "gen3"
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c3.actor_node.name = "result"
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gen1.actor_node.actor.name = "gen1"
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gen2.actor_node.actor.name = "gen2"
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result.actor_node.name = "result"
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# Elaborate
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draw = len(sys.argv) > 1 and sys.argv[1] == "draw"
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print("is_abstract before elaboration: " + str(g.is_abstract()))
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if draw:
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nx.draw(g)
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plt.show()
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draw(g)
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g.elaborate()
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print("is_abstract after elaboration : " + str(g.is_abstract()))
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if draw:
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nx.draw(g)
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plt.show()
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draw(g)
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# Simulate
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c = CompositeActor(g)
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@ -63,7 +63,11 @@ class DataFlowGraph(MultiDiGraph):
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def del_connections(self, source_node, sink_node, data_requirements):
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edges_to_delete = []
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for key, data in self.get_edge_data(source_node, sink_node).items():
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edge_data = self.get_edge_data(source_node, sink_node)
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if edge_data is None:
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# the two nodes are already completely disconnected
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return
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for key, data in edge_data.items():
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if all(k not in data_requirements or data_requirements[k] == v
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for k, v in data.items()):
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edges_to_delete.append(key)
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@ -115,9 +119,9 @@ class DataFlowGraph(MultiDiGraph):
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return any(x.is_abstract() for x in self) \
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or any(d["source_subr"] is not None or d["sink_subr"] is not None
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for u, v, d in self.edges_iter(data=True)) \
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or self._list_divergences()
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or bool(self._list_divergences())
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def _eliminate_subrecords(self):
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def _eliminate_subrecords_and_divergences(self):
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# Insert combinators.
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for (dst_node, dst_endpoint), sources in self._sink_to_sources().items():
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if len(sources) > 1 or sources[0][2] is not None:
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@ -135,10 +139,19 @@ class DataFlowGraph(MultiDiGraph):
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# connect combinator_source -> sink
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self.add_connection(combinator, dst_node, "source", dst_endpoint)
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# Insert splitters.
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# TODO
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def _eliminate_divergences(self):
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pass # TODO
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for (src_node, src_endpoint), sinks in self._source_to_sinks().items():
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if len(sinks) > 1 or sinks[0][2] is not None:
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subrecords = [src_subrecord for dst_node, dst_endpoint, src_subrecord in sinks]
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splitter = ActorNode(plumbing.Splitter, {"subrecords": subrecords})
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# disconnect source -> sink1 ... source -> sinkn
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# connect splitter_source1 -> sink1 ... splitter_sourcen -> sinkn
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for n, (dst_node, dst_endpoint, src_subrecord) in enumerate(sinks):
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self.del_connections(src_node, dst_node,
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{"source": src_endpoint, "sink": dst_endpoint})
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self.add_connection(splitter, dst_node,
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"source{0}".format(n), dst_endpoint)
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# connect source -> splitter_sink
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self.add_connection(src_node, splitter, src_endpoint, "sink")
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def _infer_plumbing_layout(self):
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while True:
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@ -182,17 +195,16 @@ class DataFlowGraph(MultiDiGraph):
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d["sink"] = sink_eps[0]
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# Elaboration turns an abstract DFG into a concrete one.
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# Pass 1: eliminate subrecords by inserting Combinator/Splitter actors
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# Pass 2: eliminate divergences by inserting Distributor actors
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# Pass 3: run optimizer (e.g. share and duplicate actors)
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# Pass 4: instantiate all abstract actors and explicit "None" endpoints
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# Pass 1: eliminate subrecords and divergences
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# by inserting Combinator/Splitter actors
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# Pass 2: run optimizer (e.g. share and duplicate actors)
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# Pass 3: instantiate all abstract actors and explicit "None" endpoints
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def elaborate(self, optimizer=None):
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if self.elaborated:
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return
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self.elaborated = True
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self._eliminate_subrecords()
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self._eliminate_divergences()
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self._eliminate_subrecords_and_divergences()
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if optimizer is not None:
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optimizer(self)
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self._instantiate_actors()
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@ -35,20 +35,39 @@ class Combinator(CombinatorialActor):
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class Splitter(CombinatorialActor):
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def __init__(self, layout, subrecords):
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sink = Record(layout)
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subrecords = [sink.subrecord(*subr) for subr in subrecords]
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subr = []
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for s in subrecords:
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if s is None:
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subr.append(sink)
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else:
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subr.append(sink.subrecord(*s))
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eps = [("source{0}".format(n), Source, r)
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for n, r in enumerate(subrecords)]
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for n, r in enumerate(subr)]
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ep_sink = ("sink", Sink, sink)
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eps.append(ep_sink)
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super().__init__(*eps)
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# TODO def get_fragment(self):
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class Distributor:
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pass # TODO
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def get_fragment(self):
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sources = [self.endpoints[e] for e in self.sources()]
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sink = self.endpoints[self.sinks()[0]]
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already_acked = Signal(BV(len(sources)))
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sync = [
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If(sink.stb,
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already_acked.eq(already_acked | Cat(*[s.ack for s in sources])),
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If(sink.ack, already_acked.eq(0))
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)
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]
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comb = [
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sink.ack.eq(optree("&",
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[s.ack | already_acked[n] for n, s in enumerate(sources)]))
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]
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for n, s in enumerate(sources):
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comb.append(s.stb.eq(sink.stb & ~already_acked[n]))
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return Fragment(comb, sync)
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# Actors whose layout should be inferred from what their single sink is connected to.
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layout_sink = {Buffer, Splitter, Distributor}
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layout_sink = {Buffer, Splitter}
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# Actors whose layout should be inferred from what their single source is connected to.
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layout_source = {Buffer, Combinator}
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# All actors.
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