revert wave_eval4
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@@ -629,84 +629,7 @@ def wave_eval(op, state, sat, st_idx, line_times, sdata, sd=0.0, seed=0):
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return overflows
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return overflows
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@numba.njit
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def wave_eval4(op, state, sat, st_idx, line_times, sdata, sd=0.0, seed=0):
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lut, z_idx, a_idx, b_idx = op
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overflows = int(0)
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_seed = (seed << 4) + (z_idx << 20) + (st_idx << 1)
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a_mem = sat[a_idx, 0]
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b_mem = sat[b_idx, 0]
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z_mem, z_cap, _ = sat[z_idx]
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a_cur = int(0)
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b_cur = int(0)
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z_cur = lut & 1
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if z_cur == 1:
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state[z_mem, st_idx] = TMIN
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a = state[a_mem, st_idx] + line_times[a_idx, 0, z_cur] * rand_gauss(_seed ^ a_mem ^ z_cur, sd) * sdata[0]
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if int(sdata[1]) == a_idx: a += sdata[2+z_cur]
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b = state[b_mem, st_idx] + line_times[b_idx, 0, z_cur] * rand_gauss(_seed ^ b_mem ^ z_cur, sd) * sdata[0]
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if int(sdata[1]) == b_idx: b += sdata[2+z_cur]
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previous_t = TMIN
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current_t = min(a, b)
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inputs = int(0)
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while current_t < TMAX:
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z_val = z_cur & 1
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if b < a:
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b_cur += 1
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b = state[b_mem + b_cur, st_idx]
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b += line_times[b_idx, 0, z_val ^ 1] * rand_gauss(_seed ^ b_mem ^ z_val ^ 1, sd) * sdata[0]
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thresh = line_times[b_idx, 1, z_val] * rand_gauss(_seed ^ b_mem ^ z_val, sd) * sdata[0]
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if int(sdata[1]) == b_idx:
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b += sdata[2+(z_val^1)]
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thresh += sdata[2+z_val]
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inputs ^= 2
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next_t = b
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else:
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a_cur += 1
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a = state[a_mem + a_cur, st_idx]
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a += line_times[a_idx, 0, z_val ^ 1] * rand_gauss(_seed ^ a_mem ^ z_val ^ 1, sd) * sdata[0]
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thresh = line_times[a_idx, 1, z_val] * rand_gauss(_seed ^ a_mem ^ z_val, sd) * sdata[0]
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if int(sdata[1]) == a_idx:
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a += sdata[2+(z_val^1)]
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thresh += sdata[2+z_val]
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inputs ^= 1
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next_t = a
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if (z_cur & 1) != ((lut >> inputs) & 1):
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# we generate a toggle in z_mem, if:
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# ( it is the first toggle in z_mem OR
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# following toggle is earlier OR
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# pulse is wide enough ) AND enough space in z_mem.
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if z_cur == 0 or next_t < current_t or (current_t - previous_t) > thresh:
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if z_cur < (z_cap - 1):
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state[z_mem + z_cur, st_idx] = current_t
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previous_t = current_t
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z_cur += 1
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else:
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overflows += 1
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previous_t = state[z_mem + z_cur - 1, st_idx]
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z_cur -= 1
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else:
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z_cur -= 1
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if z_cur > 0:
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previous_t = state[z_mem + z_cur - 1, st_idx]
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else:
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previous_t = TMIN
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current_t = min(a, b)
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if overflows > 0:
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state[z_mem + z_cur, st_idx] = TMAX_OVL
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else:
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state[z_mem + z_cur, st_idx] = a if a > b else b # propagate overflow flags by storing biggest TMAX from input
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return overflows
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class WaveSimCuda(WaveSim):
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class WaveSimCuda(WaveSim):
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"""A GPU-accelerated waveform-based combinational logic timing simulator.
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"""A GPU-accelerated waveform-based combinational logic timing simulator.
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