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SikongJueluo
424cf6e1d3
Split the monolithic test_cam_basic.py into separate test suites organized by noise configuration (no_noise, write_noise, read_noise), with shared utilities extracted to tests/top/utils.py. - Remove test_cam_basic.py; add no_noise/, write_noise/, read_noise/ test suites with Makefiles that set noise parameters statically - Extract helpers (reset_dut, write_rows, query_once, collect_topk, etc.) into tests/top/utils.py - Update hw/sim/Makefile with per-config test targets and a test-top-all meta-target - Update scripts/run_cam_correctness.py to build per-directory instead of centrally, removing inline parameter overrides - Add __init__.py for result_serializer and topk_tracker module tests - Expand docstrings in test_ref_model_noise.py with architectural context and test rationale
116 lines
4.2 KiB
Python
116 lines
4.2 KiB
Python
# -*- coding: utf-8 -*-
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"""
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CAM 读取噪声（read_noise）集成测试。
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本文件针对 READ_NOISE_EN=1 的编译配置，验证 RTL 的读取噪声行为
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与 Python 参考模型（ref_model）一致。
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=== 测试内容 ===
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read_noise_model_match — 读取噪声模型匹配：
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写入原始哈希，预测含写入噪声（如果 WRITE_NOISE_EN=1）的存储值，
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再用 match_top1_with_read_noise 计算含读取噪声的期望结果，
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与 RTL 实际 Top-1 进行比对。
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=== 架构背景 ===
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CAM 硬件由以下流水线组成：
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Write Noise → Banked Core Storage → Read Noise → Match Engine Pipeline
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↓
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Top-K Tracker → Result Serializer
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本测试覆盖的是 Read Noise → Match Engine 段。
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写入噪声（WRITE_NOISE_EN）通过 Makefile 的 test-with-write-noise 子目标
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启用，测试代码内部已兼容两种配置。
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"""
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from __future__ import annotations
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import cocotb
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import numpy as np
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from cocotb.clock import Clock
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from cocotb.triggers import RisingEdge
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from model.ref_model import (
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generate_write_flip_mask,
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match_top1_with_read_noise,
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random_hashes,
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unpack_score_debug_flat,
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)
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from tests.top.utils import (
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dut_hash_bits,
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dut_lanes,
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dut_num_rows,
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get_param,
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query_once,
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reset_dut,
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write_rows,
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)
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# ═══════════════════════════════════════════════════════════════════════════════
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# 测试：读取噪声模型匹配
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# ── READ_NOISE_EN=1 由 Makefile 保证，测试代码中不再重复门控
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# ═══════════════════════════════════════════════════════════════════════════════
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@cocotb.test()
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async def read_noise_model_match(dut):
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"""读取噪声模型匹配：验证 RTL 的读取噪声行为与 Python 参考模型一致。
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与写入噪声不同，读取噪声发生在查询阶段（每次查询向哈希值注入噪声），
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因此：
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- 如果先有写入噪声，存储行已经被翻转过一次
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- 然后查询时还会再注入一层读取噪声
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- 两层噪声使用不同的种子（写: 0xB504..., 读: 0x6A09...）
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本测试：
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1. 用 Python 模型预计算存储后的哈希（含写入噪声）
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2. 用 match_top1_with_read_noise 预计算含读取噪声的期望结果
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3. 写入原始值到 RTL，查询，比对结果
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"""
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cocotb.start_soon(Clock(dut.clk, 10, unit="ns").start())
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await reset_dut(dut)
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num_rows = dut_num_rows(dut)
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hash_bits = dut_hash_bits(dut)
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lanes = dut_lanes(dut)
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rng = np.random.default_rng(123)
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rows = random_hashes(rng, num_rows, width=hash_bits)
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# If write noise is enabled, apply write flip masks to predict stored rows
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stored_rows = list(rows)
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if get_param(dut, "WRITE_NOISE_EN", 0):
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seed = 0xB504_F32D_B504_F32D
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prng_state = (seed << 64) | seed
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stored_rows = []
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for row in rows:
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flip, prng_state = generate_write_flip_mask(
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prng_state,
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hash_bits,
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get_param(dut, "WRITE_NOISE_BITS", 8),
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get_param(dut, "WRITE_NOISE_RATE_NUM", 1),
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get_param(dut, "WRITE_NOISE_RATE_DEN", 100),
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)
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stored_rows.append(row ^ flip)
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query = rows[min(5, num_rows - 1)]
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await write_rows(dut, rows)
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top1_index, top1_score, score_debug = await query_once(dut, query)
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expected = match_top1_with_read_noise(
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query,
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stored_rows,
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width=hash_bits,
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lanes=lanes,
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noise_bits=get_param(dut, "READ_NOISE_BITS", 8),
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rate_num=get_param(dut, "READ_NOISE_RATE_NUM", 1),
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rate_den=get_param(dut, "READ_NOISE_RATE_DEN", 100),
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seed=0x6A09_E667_F3BC_C909,
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)
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assert top1_index == expected.top1_index
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assert top1_score == expected.top1_score
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if score_debug is not None:
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assert np.array_equal(score_debug, expected.scores)
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