class AddReduceData:
- def __init__(self, ppoints, output_width, n_parts):
+ def __init__(self, ppoints, n_inputs, output_width, n_parts):
self.part_ops = [Signal(2, name=f"part_ops_{i}")
for i in range(n_parts)]
self.inputs = [Signal(output_width, name=f"inputs[{i}]")
- for i in range(len(self.inputs))]
- self.reg_partition_points = partition_points.like()
+ for i in range(n_inputs)]
+ self.reg_partition_points = ppoints.like()
- def eq(self, rhs):
- return [self.reg_partition_points.eq(rhs.reg_partition_points)] + \
- [self.inputs[i].eq(rhs.inputs[i])
+ def eq_from(self, reg_partition_points, inputs, part_ops):
+ return [self.reg_partition_points.eq(reg_partition_points)] + \
+ [self.inputs[i].eq(inputs[i])
for i in range(len(self.inputs))] + \
- [self.part_ops[i].eq(rhs.part_ops[i])
+ [self.part_ops[i].eq(part_ops[i])
for i in range(len(self.part_ops))]
+ def eq(self, rhs):
+ return self.eq_from(rhs.reg_partition_points, rhs.inputs, rhs.part_ops)
+
+
+class FinalReduceData:
+
+ def __init__(self, ppoints, output_width, n_parts):
+ self.part_ops = [Signal(2, name=f"part_ops_{i}")
+ for i in range(n_parts)]
+ self.output = Signal(output_width)
+ self.reg_partition_points = ppoints.like()
+
+ def eq_from(self, reg_partition_points, output, part_ops):
+ return [self.reg_partition_points.eq(reg_partition_points)] + \
+ [self.output.eq(output)] + \
+ [self.part_ops[i].eq(part_ops[i])
+ for i in range(len(self.part_ops))]
+
+ def eq(self, rhs):
+ return self.eq_from(rhs.reg_partition_points, rhs.output, rhs.part_ops)
+
+
+class FinalAdd(Elaboratable):
+ """ Final stage of add reduce
+ """
+
+ def __init__(self, n_inputs, output_width, n_parts, register_levels,
+ partition_points):
+ self.i = AddReduceData(partition_points, n_inputs,
+ output_width, n_parts)
+ self.o = FinalReduceData(partition_points, output_width, n_parts)
+ self.output_width = output_width
+ self.n_inputs = n_inputs
+ self.n_parts = n_parts
+ self.register_levels = list(register_levels)
+ self.partition_points = PartitionPoints(partition_points)
+ if not self.partition_points.fits_in_width(output_width):
+ raise ValueError("partition_points doesn't fit in output_width")
+
+ def elaborate(self, platform):
+ """Elaborate this module."""
+ m = Module()
+
+ output_width = self.output_width
+ output = Signal(output_width)
+ if self.n_inputs == 0:
+ # use 0 as the default output value
+ m.d.comb += output.eq(0)
+ elif self.n_inputs == 1:
+ # handle single input
+ m.d.comb += output.eq(self.i.inputs[0])
+ else:
+ # base case for adding 2 inputs
+ assert self.n_inputs == 2
+ adder = PartitionedAdder(output_width, self.i.reg_partition_points)
+ m.submodules.final_adder = adder
+ m.d.comb += adder.a.eq(self.i.inputs[0])
+ m.d.comb += adder.b.eq(self.i.inputs[1])
+ m.d.comb += output.eq(adder.output)
+
+ # create output
+ m.d.comb += self.o.eq_from(self.i.reg_partition_points, output,
+ self.i.part_ops)
+
+ return m
+
class AddReduceSingle(Elaboratable):
"""Add list of numbers together.
supported, except for by ``Signal.eq``.
"""
- def __init__(self, inputs, output_width, register_levels, partition_points,
- part_ops):
+ def __init__(self, n_inputs, output_width, n_parts, register_levels,
+ partition_points):
"""Create an ``AddReduce``.
:param inputs: input ``Signal``s to be summed.
pipeline registers.
:param partition_points: the input partition points.
"""
- self.part_ops = part_ops
- self.out_part_ops = [Signal(2, name=f"out_part_ops_{i}")
- for i in range(len(part_ops))]
- self.inputs = list(inputs)
- self._resized_inputs = [
- Signal(output_width, name=f"resized_inputs[{i}]")
- for i in range(len(self.inputs))]
+ self.n_inputs = n_inputs
+ self.n_parts = n_parts
+ self.output_width = output_width
+ self.i = AddReduceData(partition_points, n_inputs,
+ output_width, n_parts)
self.register_levels = list(register_levels)
- self.output = Signal(output_width)
self.partition_points = PartitionPoints(partition_points)
if not self.partition_points.fits_in_width(output_width):
raise ValueError("partition_points doesn't fit in output_width")
- self._reg_partition_points = self.partition_points.like()
- max_level = AddReduceSingle.get_max_level(len(self.inputs))
+ max_level = AddReduceSingle.get_max_level(n_inputs)
for level in self.register_levels:
if level > max_level:
raise ValueError(
# because we need to know what they are (in order to set up the
# interconnects back in AddReduce), but cannot do the m.d.comb +=
# etc because this is not in elaboratable.
- self.groups = AddReduceSingle.full_adder_groups(len(self.inputs))
+ self.groups = AddReduceSingle.full_adder_groups(n_inputs)
self._intermediate_terms = []
if len(self.groups) != 0:
self.create_next_terms()
+ self.o = AddReduceData(partition_points, len(self._intermediate_terms),
+ output_width, n_parts)
+
@staticmethod
def get_max_level(input_count):
"""Get the maximum level.
"""Elaborate this module."""
m = Module()
- # resize inputs to correct bit-width and optionally add in
- # pipeline registers
- resized_input_assignments = [self._resized_inputs[i].eq(self.inputs[i])
- for i in range(len(self.inputs))]
- copy_part_ops = [self.out_part_ops[i].eq(self.part_ops[i])
- for i in range(len(self.part_ops))]
- if 0 in self.register_levels:
- m.d.sync += copy_part_ops
- m.d.sync += resized_input_assignments
- m.d.sync += self._reg_partition_points.eq(self.partition_points)
- else:
- m.d.comb += copy_part_ops
- m.d.comb += resized_input_assignments
- m.d.comb += self._reg_partition_points.eq(self.partition_points)
-
- for (value, term) in self._intermediate_terms:
- m.d.comb += term.eq(value)
-
- # if there are no full adders to create, then we handle the base cases
- # and return, otherwise we go on to the recursive case
- if len(self.groups) == 0:
- if len(self.inputs) == 0:
- # use 0 as the default output value
- m.d.comb += self.output.eq(0)
- elif len(self.inputs) == 1:
- # handle single input
- m.d.comb += self.output.eq(self._resized_inputs[0])
- else:
- # base case for adding 2 inputs
- assert len(self.inputs) == 2
- adder = PartitionedAdder(len(self.output),
- self._reg_partition_points)
- m.submodules.final_adder = adder
- m.d.comb += adder.a.eq(self._resized_inputs[0])
- m.d.comb += adder.b.eq(self._resized_inputs[1])
- m.d.comb += self.output.eq(adder.output)
- return m
-
- mask = self._reg_partition_points.as_mask(len(self.output))
+ # copy the intermediate terms to the output
+ for i, value in enumerate(self._intermediate_terms):
+ m.d.comb += self.o.inputs[i].eq(value)
+
+ # copy reg part points and part ops to output
+ m.d.comb += self.o.reg_partition_points.eq(self.i.reg_partition_points)
+ m.d.comb += [self.o.part_ops[i].eq(self.i.part_ops[i])
+ for i in range(len(self.i.part_ops))]
+
+ # set up the partition mask (for the adders)
+ mask = self.i.reg_partition_points.as_mask(self.output_width)
m.d.comb += self.part_mask.eq(mask)
# add and link the intermediate term modules
for i, (iidx, adder_i) in enumerate(self.adders):
setattr(m.submodules, f"adder_{i}", adder_i)
- m.d.comb += adder_i.in0.eq(self._resized_inputs[iidx])
- m.d.comb += adder_i.in1.eq(self._resized_inputs[iidx + 1])
- m.d.comb += adder_i.in2.eq(self._resized_inputs[iidx + 2])
+ m.d.comb += adder_i.in0.eq(self.i.inputs[iidx])
+ m.d.comb += adder_i.in1.eq(self.i.inputs[iidx + 1])
+ m.d.comb += adder_i.in2.eq(self.i.inputs[iidx + 2])
m.d.comb += adder_i.mask.eq(self.part_mask)
return m
def create_next_terms(self):
- # go on to prepare recursive case
- intermediate_terms = []
_intermediate_terms = []
def add_intermediate_term(value):
- intermediate_term = Signal(
- len(self.output),
- name=f"intermediate_terms[{len(intermediate_terms)}]")
- _intermediate_terms.append((value, intermediate_term))
- intermediate_terms.append(intermediate_term)
+ _intermediate_terms.append(value)
# store mask in intermediary (simplifies graph)
- self.part_mask = Signal(len(self.output), reset_less=True)
+ self.part_mask = Signal(self.output_width, reset_less=True)
# create full adders for this recursive level.
# this shrinks N terms to 2 * (N // 3) plus the remainder
self.adders = []
for i in self.groups:
- adder_i = MaskedFullAdder(len(self.output))
+ adder_i = MaskedFullAdder(self.output_width)
self.adders.append((i, adder_i))
# add both the sum and the masked-carry to the next level.
# 3 inputs have now been reduced to 2...
add_intermediate_term(adder_i.sum)
add_intermediate_term(adder_i.mcarry)
# handle the remaining inputs.
- if len(self.inputs) % FULL_ADDER_INPUT_COUNT == 1:
- add_intermediate_term(self._resized_inputs[-1])
- elif len(self.inputs) % FULL_ADDER_INPUT_COUNT == 2:
+ if self.n_inputs % FULL_ADDER_INPUT_COUNT == 1:
+ add_intermediate_term(self.i.inputs[-1])
+ elif self.n_inputs % FULL_ADDER_INPUT_COUNT == 2:
# Just pass the terms to the next layer, since we wouldn't gain
# anything by using a half adder since there would still be 2 terms
# and just passing the terms to the next layer saves gates.
- add_intermediate_term(self._resized_inputs[-2])
- add_intermediate_term(self._resized_inputs[-1])
+ add_intermediate_term(self.i.inputs[-2])
+ add_intermediate_term(self.i.inputs[-1])
else:
- assert len(self.inputs) % FULL_ADDER_INPUT_COUNT == 0
+ assert self.n_inputs % FULL_ADDER_INPUT_COUNT == 0
- self.intermediate_terms = intermediate_terms
self._intermediate_terms = _intermediate_terms
mods = []
next_levels = self.register_levels
partition_points = self.partition_points
- inputs = self.inputs
part_ops = self.part_ops
+ n_parts = len(part_ops)
+ inputs = self.inputs
+ ilen = len(inputs)
while True:
- next_level = AddReduceSingle(inputs, self.output_width, next_levels,
- partition_points, part_ops)
+ next_level = AddReduceSingle(ilen, self.output_width, n_parts,
+ next_levels, partition_points)
mods.append(next_level)
- if len(next_level.groups) == 0:
- break
next_levels = list(AddReduce.next_register_levels(next_levels))
- partition_points = next_level._reg_partition_points
- inputs = next_level.intermediate_terms
- part_ops = next_level.out_part_ops
+ partition_points = next_level.i.reg_partition_points
+ inputs = next_level.o.inputs
+ ilen = len(inputs)
+ part_ops = next_level.i.part_ops
+ groups = AddReduceSingle.full_adder_groups(len(inputs))
+ if len(groups) == 0:
+ break
+
+ if ilen != 0:
+ next_level = FinalAdd(ilen, self.output_width, n_parts,
+ next_levels, partition_points)
+ mods.append(next_level)
self.levels = mods
for i, next_level in enumerate(self.levels):
setattr(m.submodules, "next_level%d" % i, next_level)
+ partition_points = self.partition_points
+ inputs = self.inputs
+ part_ops = self.part_ops
+ n_parts = len(part_ops)
+ n_inputs = len(inputs)
+ output_width = self.output_width
+ i = AddReduceData(partition_points, n_inputs, output_width, n_parts)
+ m.d.comb += i.eq_from(partition_points, inputs, part_ops)
+ for idx in range(len(self.levels)):
+ mcur = self.levels[idx]
+ if 0 in mcur.register_levels:
+ m.d.sync += mcur.i.eq(i)
+ else:
+ m.d.comb += mcur.i.eq(i)
+ i = mcur.o # for next loop
+
# output comes from last module
- m.d.comb += self.output.eq(next_level.output)
- copy_part_ops = [self.out_part_ops[i].eq(next_level.out_part_ops[i])
- for i in range(len(self.part_ops))]
+ m.d.comb += self.output.eq(i.output)
+ copy_part_ops = [self.out_part_ops[idx].eq(i.part_ops[idx])
+ for idx in range(len(self.part_ops))]
m.d.comb += copy_part_ops
return m
expanded_part_pts,
self.part_ops)
- out_part_ops = add_reduce.levels[-1].out_part_ops
- out_part_pts = add_reduce.levels[-1]._reg_partition_points
+ out_part_ops = add_reduce.out_part_ops
+ out_part_pts = add_reduce.levels[-1].o.reg_partition_points
m.submodules.add_reduce = add_reduce
m.d.comb += self._intermediate_output.eq(add_reduce.output)