src/soc/minerva/units/predict.py

   1 from nmigen import Elaboratable, Module, Signal
   2
   3
   4 __all__ = ["BranchPredictor"]
   5
   6
   7 class BranchPredictor(Elaboratable):
   8     def __init__(self):
   9         self.d_branch = Signal()
  10         self.d_jump = Signal()
  11         self.d_offset = Signal((32, True))
  12         self.d_pc = Signal(32)
  13         self.d_rs1_re = Signal()
  14
  15         self.d_branch_taken = Signal()
  16         self.d_branch_target = Signal(32)
  17         self.d_fetch_misaligned = Signal()
  18
  19     def elaborate(self, platform):
  20         m = Module()
  21
  22         with m.If(self.d_branch):
  23             # Backward conditional branches are predicted as taken.
  24             # Forward conditional branches are predicted as not taken.
  25             m.d.comb += self.d_branch_taken.eq(self.d_offset[-1])
  26         with m.Else():
  27             # Direct jumps are predicted as taken.
  28             # Other branch types (ie. indirect jumps, exceptions) are not predicted.
  29             m.d.comb += self.d_branch_taken.eq(self.d_jump & ~self.d_rs1_re)
  30
  31         m.d.comb += [
  32             self.d_branch_target.eq(self.d_pc + self.d_offset),
  33             self.d_fetch_misaligned.eq(self.d_branch_target[:2].bool())
  34         ]
  35
  36         return m