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Commit 9b776821 authored by Yaman Umuroglu's avatar Yaman Umuroglu
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[FIFO] adapt FIFO sizing to new attributes

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src/finn/transformation/fpgadataflow/derive_characteristic.py
+ 51
− 33
View file @ 9b776821
......@@ -71,7 +71,7 @@ class DeriveCharacteristic(NodeLocalTransformation):
assert inst.get_nodeattr("rtlsim_so") != "", (
"rtlsim not ready for " + node.name
)
if inst.get_nodeattr("io_characteristic_period") > 0:
if inst.get_nodeattr("io_chrc_period") > 0:
warnings.warn(
"Skipping node %s: already has FIFO characteristic" % node.name
)
......@@ -133,18 +133,25 @@ class DeriveCharacteristic(NodeLocalTransformation):
pass
# extra dicts to keep track of cycle-by-cycle transaction behavior
txns_in = {key: [] for (key, value) in io_dict["inputs"].items()}
txns_out = {key: [] for (key, value) in io_dict["outputs"].items()}
# note that we restrict key names to filter out weight streams etc
txns_in = {
key: [] for (key, value) in io_dict["inputs"].items() if "in" in key
}
txns_out = {
key: []
for (key, value) in io_dict["outputs"].items()
if "out" in key
}
def monitor_txns(sim_obj):
for inp in io_dict["inputs"]:
for inp in txns_in:
in_ready = _read_signal(sim, inp + sname + "TREADY") == 1
in_valid = _read_signal(sim, inp + sname + "TVALID") == 1
if in_ready and in_valid:
txns_in[inp].append(1)
else:
txns_in[inp].append(0)
for outp in io_dict["outputs"]:
for outp in txns_out:
if (
_read_signal(sim, outp + sname + "TREADY") == 1
and _read_signal(sim, outp + sname + "TVALID") == 1
......@@ -163,17 +170,7 @@ class DeriveCharacteristic(NodeLocalTransformation):
hook_preclk=monitor_txns,
)
assert total_cycle_count <= self.period
# restrict to single input-output stream only for now
txns_in = txns_in["in0"]
txns_out = txns_out[
"out" if node.op_type != "DuplicateStreams_Batch" else "out0"
]
if len(txns_in) < self.period:
pad_in = self.period - len(txns_in)
txns_in += [0 for x in range(pad_in)]
if len(txns_out) < self.period:
pad_out = self.period - len(txns_out)
txns_out += [0 for x in range(pad_out)]
inst.set_nodeattr("io_chrc_period", self.period)
def accumulate_char_fxn(chrc):
p = len(chrc)
......@@ -183,14 +180,36 @@ class DeriveCharacteristic(NodeLocalTransformation):
ret.append(chrc[0])
else:
ret.append(ret[-1] + chrc[t % p])
return ret
return np.asarray(ret, dtype=np.int32)
all_txns_in = np.empty((len(txns_in.keys()), 2 * self.period))
all_txns_out = np.empty((len(txns_out.keys()), 2 * self.period))
all_pad_in = []
all_pad_out = []
for in_idx, in_strm_nm in enumerate(txns_in.keys()):
txn_in = txns_in[in_strm_nm]
if len(txn_in) < self.period:
pad_in = self.period - len(txn_in)
txn_in += [0 for x in range(pad_in)]
txn_in = accumulate_char_fxn(txn_in)
all_txns_in[in_idx, :] = txn_in
all_pad_in.append(pad_in)
for out_idx, out_strm_nm in enumerate(txns_out.keys()):
txn_out = txns_out[out_strm_nm]
if len(txn_out) < self.period:
pad_out = self.period - len(txn_out)
txn_out += [0 for x in range(pad_out)]
txn_out = accumulate_char_fxn(txn_out)
all_txns_out[out_idx, :] = txn_out
all_pad_out.append(pad_out)
# TODO specialize here for DuplicateStreams and AddStreams
inst.set_nodeattr("io_chrc_in", all_txns_in)
inst.set_nodeattr("io_chrc_out", all_txns_out)
inst.set_nodeattr("io_chrc_pads_in", all_pad_in)
inst.set_nodeattr("io_chrc_pads_out", all_pad_out)
txns_in = accumulate_char_fxn(txns_in)
txns_out = accumulate_char_fxn(txns_out)
io_characteristic = txns_in + txns_out
inst.set_nodeattr("io_characteristic", io_characteristic)
inst.set_nodeattr("io_characteristic_period", self.period)
inst.set_nodeattr("io_characteristic_pads", [pad_in, pad_out])
except KeyError:
# exception if op_type is not supported
raise Exception(
......@@ -230,7 +249,7 @@ class DeriveCharacteristic(NodeLocalTransformation):
comp_branch_first = registry.getCustomOp(comp_branch_first)
# for DuplicateStreams, use comp_branch_first's input characterization
# for AddStreams, use comp_branch_last's output characterization
period = comp_branch_first.get_nodeattr("io_characteristic_period")
period = comp_branch_first.get_nodeattr("io_chrc_period")
comp_branch_first_f = comp_branch_first.get_nodeattr("io_characteristic")[
: 2 * period
]
......@@ -239,9 +258,9 @@ class DeriveCharacteristic(NodeLocalTransformation):
]
ds_node_inst = registry.getCustomOp(ds_node)
addstrm_node_inst = registry.getCustomOp(addstrm_node)
ds_node_inst.set_nodeattr("io_characteristic_period", period)
ds_node_inst.set_nodeattr("io_chrc_period", period)
ds_node_inst.set_nodeattr("io_characteristic", comp_branch_first_f * 2)
addstrm_node_inst.set_nodeattr("io_characteristic_period", period)
addstrm_node_inst.set_nodeattr("io_chrc_period", period)
addstrm_node_inst.set_nodeattr("io_characteristic", comp_branch_last_f * 2)
warnings.warn(
f"Set {ds_node.name} chrc. from {comp_branch_first.onnx_node.name}"
......@@ -272,15 +291,15 @@ class DeriveFIFOSizes(NodeLocalTransformation):
# lookup op_type in registry of CustomOps
prod = registry.getCustomOp(node)
assert op_type != "StreamingFIFO", "Found existing FIFOs"
period = prod.get_nodeattr("io_characteristic_period")
prod_chrc = prod.get_nodeattr("io_characteristic")
period = prod.get_nodeattr("io_chrc_period")
prod_chrc = prod.get_nodeattr("io_chrc_out")[0]
assert (
len(prod_chrc) == 4 * period
len(prod_chrc) == 2 * period
), "Found unexpected characterization attribute"
if prod.get_nodeattr("outFIFODepth") > 2:
# FIFO depth already set, can skip this node
return (node, False)
prod_chrc = np.asarray(prod_chrc).reshape(2, -1)[1]
# find consumers
model = self.ref_input_model
out_fifo_depths = []
......@@ -292,8 +311,7 @@ class DeriveFIFOSizes(NodeLocalTransformation):
out_fifo_depths.append(2)
continue
cons = registry.getCustomOp(cons_node)
cons_chrc = cons.get_nodeattr("io_characteristic")
cons_chrc = np.asarray(cons_chrc).reshape(2, -1)[0]
cons_chrc = cons.get_nodeattr("io_chrc_in")[0]
# find minimum phase shift satisfying the constraint
pshift_min = period - 1
for pshift_cand in range(period):
......@@ -304,7 +322,7 @@ class DeriveFIFOSizes(NodeLocalTransformation):
break
prod_chrc_part = prod_chrc[pshift_min : (pshift_min + period)]
cons_chrc_part = cons_chrc[:period]
fifo_depth = (prod_chrc_part - cons_chrc_part).max()
fifo_depth = int((prod_chrc_part - cons_chrc_part).max())
out_fifo_depths.append(fifo_depth)
# set output FIFO depth for this (producing) node
# InsertFIFO looks at the max of (outFIFODepth, inFIFODepth)
......
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