From: Luke Kenneth Casson Leighton Date: Wed, 21 Aug 2019 14:57:18 +0000 (+0100) Subject: pass data around using classes in AddReduce X-Git-Tag: ls180-24jan2020~440 X-Git-Url: https://git.libre-soc.org/?p=ieee754fpu.git;a=commitdiff_plain;h=e297dd6f682d8d149cad6ff45a56fa55da694b3c pass data around using classes in AddReduce --- diff --git a/src/ieee754/part_mul_add/multiply.py b/src/ieee754/part_mul_add/multiply.py index 078507a0..e0fe069d 100644 --- a/src/ieee754/part_mul_add/multiply.py +++ b/src/ieee754/part_mul_add/multiply.py @@ -309,13 +309,34 @@ class AddReduceData: 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 @@ -325,34 +346,40 @@ class FinalAdd(Elaboratable): 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.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.intermediate_terms = [] 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 += self.output.eq(0) + m.d.comb += output.eq(0) elif self.n_inputs == 1: # handle single input - m.d.comb += self.output.eq(self.i.inputs[0]) + m.d.comb += output.eq(self.i.inputs[0]) else: # base case for adding 2 inputs assert self.n_inputs == 2 - adder = PartitionedAdder(len(self.output), - self.i.reg_partition_points) + 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 += self.output.eq(adder.output) + 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 @@ -403,6 +430,9 @@ class AddReduceSingle(Elaboratable): 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. @@ -430,9 +460,16 @@ class AddReduceSingle(Elaboratable): """Elaborate this module.""" m = Module() - for (value, term) in self._intermediate_terms: - m.d.comb += term.eq(value) + # 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) @@ -449,16 +486,10 @@ class AddReduceSingle(Elaboratable): def create_next_terms(self): - # go on to prepare recursive case - intermediate_terms = [] _intermediate_terms = [] def add_intermediate_term(value): - intermediate_term = Signal( - self.output_width, - 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(self.output_width, reset_less=True) @@ -485,7 +516,6 @@ class AddReduceSingle(Elaboratable): else: assert self.n_inputs % FULL_ADDER_INPUT_COUNT == 0 - self.intermediate_terms = intermediate_terms self._intermediate_terms = _intermediate_terms @@ -539,17 +569,17 @@ class AddReduce(Elaboratable): 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: - ilen = len(inputs) next_level = AddReduceSingle(ilen, self.output_width, n_parts, next_levels, partition_points) mods.append(next_level) next_levels = list(AddReduce.next_register_levels(next_levels)) partition_points = next_level.i.reg_partition_points - inputs = next_level.intermediate_terms + inputs = next_level.o.inputs ilen = len(inputs) part_ops = next_level.i.part_ops groups = AddReduceSingle.full_adder_groups(len(inputs)) @@ -573,28 +603,23 @@ class AddReduce(Elaboratable): partition_points = self.partition_points inputs = self.inputs part_ops = self.part_ops - for i in range(len(self.levels)): - mcur = self.levels[i] - inassign = [mcur.i.inputs[i].eq(inputs[i]) - for i in range(len(inputs))] - copy_part_ops = [mcur.i.part_ops[i].eq(part_ops[i]) - for i in range(len(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 += copy_part_ops - m.d.sync += inassign - m.d.sync += mcur.i.reg_partition_points.eq(partition_points) + m.d.sync += mcur.i.eq(i) else: - m.d.comb += copy_part_ops - m.d.comb += inassign - m.d.comb += mcur.i.reg_partition_points.eq(partition_points) - partition_points = mcur.i.reg_partition_points - inputs = mcur.intermediate_terms - part_ops = mcur.i.part_ops + 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.i.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 @@ -1122,8 +1147,8 @@ class Mul8_16_32_64(Elaboratable): expanded_part_pts, self.part_ops) - out_part_ops = add_reduce.levels[-1].i.part_ops - out_part_pts = add_reduce.levels[-1].i.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)