forked from M-Labs/artiq
fir: add ParallelFIR and test
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@ -45,24 +45,64 @@ class FIR(Module):
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self.width = width
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self.width = width
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self.i = Signal((width, True))
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self.i = Signal((width, True))
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self.o = Signal((width, True))
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self.o = Signal((width, True))
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self.latency = (len(coefficients) + 1)//2 + 1
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n = len(coefficients)
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self.latency = (n + 1)//2 + 1
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###
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###
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n = len(coefficients)
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# Delay line: increasing delay
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x = [Signal((width, True)) for _ in range(n)]
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x = [Signal((width, True)) for _ in range(n)]
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self.comb += x[0].eq(self.i)
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self.sync += [xi.eq(xj) for xi, xj in zip(x, [self.i] + x)]
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self.sync += [x[i + 1].eq(x[i]) for i in range(n - 1)]
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# Wire up output
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o = []
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o = []
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for i, c in enumerate(coefficients):
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for i, c in enumerate(coefficients):
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# simplify for halfband and symmetric filters
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# simplify for halfband and symmetric filters
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if c == 0 or c in coefficients[:i]:
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if c == 0 or c in coefficients[i + 1:]:
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continue
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continue
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o.append(c*reduce(add, [
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o.append(c*reduce(add, [
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xj for xj, cj in zip(x, coefficients) if cj == c
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xj for xj, cj in zip(x[::-1], coefficients) if cj == c
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]))
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]))
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if shift is None:
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if shift is None:
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shift = width - 1
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shift = width - 1
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self.sync += self.o.eq(reduce(add, o) >> shift)
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self.sync += self.o.eq(reduce(add, o) >> shift)
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class ParallelFIR(Module):
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"""Full-rate parallelized finite impulse response filter.
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:param coefficients: integer taps.
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:param parallelism: number of samples per cycle.
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:param width: bit width of input and output.
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:param shift: scale factor (as power of two).
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"""
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def __init__(self, coefficients, parallelism, width=16, shift=None):
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self.width = width
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self.parallelism = p = parallelism
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n = len(coefficients)
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# input and output: old to young, decreasing delay
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self.i = [Signal((width, True)) for i in range(p)]
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self.o = [Signal((width, True)) for i in range(p)]
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self.latency = (n + 1)//2//parallelism + 2 # minus .5
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###
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# Delay line: young to old, increasing delay
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x = [Signal((width, True)) for _ in range(n + p - 1)]
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self.sync += [xi.eq(xj) for xi, xj in zip(x, self.i[::-1] + x)]
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if shift is None:
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shift = width - 1
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# wire up each output
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for j in range(p):
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o = []
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for i, c in enumerate(coefficients):
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# simplify for halfband and symmetric filters
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if c == 0 or c in coefficients[i + 1:]:
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continue
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o.append(c*reduce(add, [
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xj for xj, cj in zip(x[-1 - j::-1], coefficients) if cj == c
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]))
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self.sync += self.o[j].eq(reduce(add, o) >> shift)
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@ -19,8 +19,8 @@ class Transfer(Module):
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for i in range(self.dut.latency):
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for i in range(self.dut.latency):
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yield
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yield
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for i in range(len(y)):
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for i in range(len(y)):
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y[i] = (yield self.dut.o)
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yield
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yield
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y[i] = (yield self.dut.o)
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def run(self, samples, amplitude=1.):
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def run(self, samples, amplitude=1.):
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w = 2**(self.dut.width - 1) - 1
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w = 2**(self.dut.width - 1) - 1
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@ -63,12 +63,31 @@ class Transfer(Module):
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return fig
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return fig
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class ParallelTransfer(Transfer):
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def drive(self, x):
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for xi in x.reshape(-1, self.dut.parallelism):
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yield [ij.eq(int(xj)) for ij, xj in zip(self.dut.i, xi)]
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yield
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def record(self, y):
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for i in range(self.dut.latency):
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yield
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for yi in y.reshape(-1, self.dut.parallelism):
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yield
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yi[:] = (yield from [(yield o) for o in self.dut.o])
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def _main():
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def _main():
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coeff = fir.halfgen4(.4/2, 8)
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coeff = fir.halfgen4(.4/2, 8)
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coeff_int = [int(round(c * (1 << 16 - 1))) for c in coeff]
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coeff_int = [int(round(c * (1 << 16 - 1))) for c in coeff]
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dut = fir.FIR(coeff_int, width=16)
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if False:
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# print(verilog.convert(dut, ios={dut.i, dut.o}))
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dut = fir.FIR(coeff_int, width=16)
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tb = Transfer(dut)
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# print(verilog.convert(dut, ios={dut.i, dut.o}))
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tb = Transfer(dut)
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else:
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dut = fir.ParallelFIR(coeff_int, parallelism=4, width=16)
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# print(verilog.convert(dut, ios=set(dut.i + dut.o)))
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tb = ParallelTransfer(dut)
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x, y = tb.run(samples=1 << 10, amplitude=.8)
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x, y = tb.run(samples=1 << 10, amplitude=.8)
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tb.analyze(x, y)
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tb.analyze(x, y)
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plt.show()
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plt.show()
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