rtio-nmigen/rtio/sed/output_network.py

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from nmigen import *
from nmigen.utils import *
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from rtio.sed import layouts
__all__ = ["latency", "OutputNetwork"]
# Based on: https://github.com/Bekbolatov/SortingNetworks/blob/master/src/main/js/gr.js
def boms_get_partner(n, l, p):
if p == 1:
return n ^ (1 << (l - 1))
scale = 1 << (l - p)
box = 1 << p
sn = n//scale - n//scale//box*box
if sn == 0 or sn == (box - 1):
return n
if (sn % 2) == 0:
return n - scale
return n + scale
def boms_steps_pairs(lane_count):
d = log2_int(lane_count)
steps = []
for l in range(1, d+1):
for p in range(1, l+1):
pairs = []
for n in range(2**d):
partner = boms_get_partner(n, l, p)
if partner != n:
if partner > n:
pair = (n, partner)
else:
pair = (partner, n)
if pair not in pairs:
pairs.append(pair)
steps.append(pairs)
return steps
def latency(lane_count):
d = log2_int(lane_count)
return sum(l for l in range(1, d+1))
def cmp_wrap(a, b):
return Mux((a[-2] == a[-1]) & (b[-2] == b[-1]) & (a[-1] != b[-1]), a[-1], a < b)
class OutputNetwork(Elaboratable):
def __init__(self, lane_count, seqn_width, layout_payload):
m = Module()
self.m = m
self.input = [Record(layouts.output_network_node(seqn_width, layout_payload))
for _ in range(lane_count)]
self.output = None
step_input = self.input
for step in boms_steps_pairs(lane_count):
step_output = []
for i in range(lane_count):
rec = Record(layouts.output_network_node(seqn_width, layout_payload),
reset_less=True)
rec.valid.reset_less = False
step_output.append(rec)
for node1, node2 in step:
nondata_difference = Signal()
for field, _ in layout_payload:
if field != "data":
f1 = getattr(step_input[node1].payload, field)
f2 = getattr(step_input[node2].payload, field)
with m.If(f1 != f2):
m.d.comb += nondata_difference.eq(1)
k1 = Cat(step_input[node1].payload.channel, ~step_input[node1].valid)
k2 = Cat(step_input[node2].payload.channel, ~step_input[node2].valid)
with m.If(k1 == k2):
with m.If(cmp_wrap(step_input[node1].seqn, step_input[node2].seqn)):
m.d.sync += step_output[node1].eq(step_input[node2])
m.d.sync += step_output[node2].eq(step_input[node1])
with m.Else():
m.d.sync += step_output[node1].eq(step_input[node1])
m.d.sync += step_output[node2].eq(step_input[node2])
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m.d.sync += step_output[node1].replace_occured.eq(1)
m.d.sync += step_output[node1].nondata_replace_occured.eq(nondata_difference)
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m.d.sync += step_output[node2].valid.eq(0)
with m.Elif(k1 < k2):
m.d.sync += step_output[node1].eq(step_input[node1])
m.d.sync += step_output[node2].eq(step_input[node2])
with m.Else():
m.d.sync += step_output[node1].eq(step_input[node2])
m.d.sync += step_output[node2].eq(step_input[node1])
unchanged = list(range(lane_count))
for node1, node2 in step:
unchanged.remove(node1)
unchanged.remove(node2)
for node in unchanged:
m.d.sync += step_output[node].eq(step_input[node])
self.output = step_output
step_input = step_output
def elaborate(self, platform):
return self.m