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