test: add vector-driven Verilator testbench with Python model cross-check

Add gen_verilator_vectors.py to convert test_vectors.json into hex files
for $readmemh, and tb_ldpc_vectors.sv to drive 20 test vectors through
the RTL decoder and verify bit-exact matching against the Python model.

All 11 converged vectors pass with exact decoded word, convergence flag,
and zero syndrome weight. All 9 non-converged vectors match the Python
model's decoded word, iteration count, and syndrome weight exactly.

Three RTL bugs fixed in ldpc_decoder_core.sv during testing:
- Magnitude overflow: -32 (6'b100000) negation overflowed 5-bit field
  to 0; now clamped to max magnitude 31
- Converged flag persistence: moved clearing from IDLE to INIT so host
  can read results after decode completes
- msg_cn2vn zeroing: bypass stale array reads on first iteration
  (iter_cnt==0) to avoid Verilator scheduling issues with large 3D
  array initialization

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
cah
2026-02-25 19:50:09 -07:00
parent 1520f4da5b
commit ab9ef9ca30
7 changed files with 1700 additions and 6 deletions

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#!/usr/bin/env python3
"""
Generate hex files for Verilator $readmemh from Python model test vectors.
Reads data/test_vectors.json and produces:
tb/vectors/llr_words.hex - LLR data packed as 32-bit hex words
tb/vectors/expected.hex - Expected decode results
tb/vectors/num_vectors.txt - Vector count
LLR packing format (matches wishbone_interface.sv):
Each 32-bit word holds 5 LLRs, 6 bits each, in two's complement.
Word[i] bits [5:0] = LLR[5*i+0]
Word[i] bits [11:6] = LLR[5*i+1]
Word[i] bits [17:12] = LLR[5*i+2]
Word[i] bits [23:18] = LLR[5*i+3]
Word[i] bits [29:24] = LLR[5*i+4]
52 words cover 260 LLRs (256 used, last 4 are zero-padded).
Expected output format (per vector, 4 lines):
Line 0: decoded_word (32-bit hex, info bits packed LSB-first)
Line 1: converged (00000000 or 00000001)
Line 2: iterations (32-bit hex)
Line 3: syndrome_weight (32-bit hex)
"""
import json
import os
import sys
# Paths relative to this script's directory
SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
PROJECT_DIR = os.path.dirname(SCRIPT_DIR)
INPUT_FILE = os.path.join(PROJECT_DIR, 'data', 'test_vectors.json')
OUTPUT_DIR = os.path.join(PROJECT_DIR, 'tb', 'vectors')
Q_BITS = 6
LLRS_PER_WORD = 5
N_LLR = 256
N_WORDS = (N_LLR + LLRS_PER_WORD - 1) // LLRS_PER_WORD # 52
K = 32
LINES_PER_EXPECTED = 4 # decoded_word, converged, iterations, syndrome_weight
def signed_to_twos_complement(val, bits=Q_BITS):
"""Convert signed integer to two's complement unsigned representation."""
if val < 0:
return val + (1 << bits)
return val & ((1 << bits) - 1)
def pack_llr_words(llr_quantized):
"""
Pack 256 signed LLRs into 52 uint32 words.
Each word contains 5 LLRs, 6 bits each:
bits[5:0] = LLR[5*word + 0]
bits[11:6] = LLR[5*word + 1]
bits[17:12] = LLR[5*word + 2]
bits[23:18] = LLR[5*word + 3]
bits[29:24] = LLR[5*word + 4]
"""
# Pad to 260 entries (52 * 5)
padded = list(llr_quantized) + [0] * (N_WORDS * LLRS_PER_WORD - N_LLR)
words = []
for w in range(N_WORDS):
word = 0
for p in range(LLRS_PER_WORD):
llr_idx = w * LLRS_PER_WORD + p
tc = signed_to_twos_complement(padded[llr_idx])
word |= (tc & 0x3F) << (p * Q_BITS)
words.append(word)
return words
def bits_to_uint32(bits):
"""Convert a list of 32 binary values to a single uint32 (bit 0 = LSB)."""
val = 0
for i, b in enumerate(bits):
if b:
val |= (1 << i)
return val
def main():
# Load test vectors
print(f'Reading {INPUT_FILE}...')
with open(INPUT_FILE) as f:
vectors = json.load(f)
num_vectors = len(vectors)
converged_count = sum(1 for v in vectors if v['converged'])
print(f' Loaded {num_vectors} vectors ({converged_count} converged, '
f'{num_vectors - converged_count} non-converged)')
# Create output directory
os.makedirs(OUTPUT_DIR, exist_ok=True)
# =========================================================================
# Generate llr_words.hex
# =========================================================================
# Format: one 32-bit hex word per line, 52 words per vector
# Total lines = 52 * num_vectors
llr_lines = []
for vec in vectors:
llr_words = pack_llr_words(vec['llr_quantized'])
assert len(llr_words) == N_WORDS
for word in llr_words:
llr_lines.append(f'{word:08X}')
llr_path = os.path.join(OUTPUT_DIR, 'llr_words.hex')
with open(llr_path, 'w') as f:
f.write('\n'.join(llr_lines) + '\n')
print(f' Wrote {llr_path} ({len(llr_lines)} lines, {N_WORDS} words/vector)')
# =========================================================================
# Generate expected.hex
# =========================================================================
# Format: 4 lines per vector (all 32-bit hex)
# Line 0: decoded_word (info bits packed LSB-first)
# Line 1: converged (00000000 or 00000001)
# Line 2: iterations
# Line 3: syndrome_weight
expected_lines = []
for vec in vectors:
decoded_word = bits_to_uint32(vec['decoded_bits'])
converged = 1 if vec['converged'] else 0
iterations = vec['iterations']
syndrome_weight = vec['syndrome_weight']
expected_lines.append(f'{decoded_word:08X}')
expected_lines.append(f'{converged:08X}')
expected_lines.append(f'{iterations:08X}')
expected_lines.append(f'{syndrome_weight:08X}')
expected_path = os.path.join(OUTPUT_DIR, 'expected.hex')
with open(expected_path, 'w') as f:
f.write('\n'.join(expected_lines) + '\n')
print(f' Wrote {expected_path} ({len(expected_lines)} lines, '
f'{LINES_PER_EXPECTED} lines/vector)')
# =========================================================================
# Generate num_vectors.txt
# =========================================================================
num_path = os.path.join(OUTPUT_DIR, 'num_vectors.txt')
with open(num_path, 'w') as f:
f.write(f'{num_vectors}\n')
print(f' Wrote {num_path} ({num_vectors})')
# =========================================================================
# Verify LLR packing roundtrip
# =========================================================================
print('\nVerifying LLR packing roundtrip...')
for vec in vectors:
llr_q = vec['llr_quantized']
words = pack_llr_words(llr_q)
for w_idx, word in enumerate(words):
for p in range(LLRS_PER_WORD):
llr_idx = w_idx * LLRS_PER_WORD + p
if llr_idx >= N_LLR:
break
tc_val = (word >> (p * Q_BITS)) & 0x3F
# Convert back to signed
if tc_val >= 32:
signed_val = tc_val - 64
else:
signed_val = tc_val
expected = llr_q[llr_idx]
assert signed_val == expected, (
f'Vec {vec["index"]}, LLR[{llr_idx}]: '
f'packed={signed_val}, expected={expected}'
)
print(' LLR packing roundtrip OK for all vectors')
# Print summary of expected results
print('\nExpected results summary:')
for vec in vectors:
decoded_word = bits_to_uint32(vec['decoded_bits'])
print(f' Vec {vec["index"]:2d}: decoded=0x{decoded_word:08X}, '
f'converged={vec["converged"]}, '
f'iter={vec["iterations"]}, '
f'syn_wt={vec["syndrome_weight"]}')
print('\nDone.')
if __name__ == '__main__':
main()