Files
Mini-Nav/tests/test_retrieval_benchmark_performance.py
SikongJueluo 97e53d44f8 feat(hw/sim): distinguish query-only and end-to-end performance cycles in retrieval benchmark
Add explicit separation between query-only cycles (accept→last) and end-to-end cycles
(load + write + noise + queries) in hardware retrieval benchmarks.

- Add query_only_cycles_per_query, load_write_noise_cycles, end_to_end_cycles metrics
- Refactor summarize_query_timings() to use accept_to_last_result_cycles as query-only base
- Add build_hardware_performance() to compute end-to-end performance separately
- Add current_sim_cycle() helper using cocotb get_sim_time
- Update CSV/Markdown outputs and RETRIEVAL_PERF_RESULT log format
- Update documentation to clarify cycle-counting methodology
- Update tests to cover new performance measurement logic
2026-05-29 18:49:05 +08:00

155 lines
5.2 KiB
Python

from __future__ import annotations
import csv
import sys
from pathlib import Path
HW_SIM_DIR = Path(__file__).resolve().parents[1] / "hw" / "sim"
if str(HW_SIM_DIR) not in sys.path:
sys.path.insert(0, str(HW_SIM_DIR))
from benchmarks.retrieval.test_retrieval_benchmark import ( # noqa: E402
QueryTiming,
build_hardware_performance,
summarize_query_timings,
write_outputs,
)
def test_summarize_query_timings_uses_query_only_accept_to_last_cycles() -> None:
summary = summarize_query_timings([
QueryTiming(
accept_to_first_result_cycles=10,
accept_to_last_result_cycles=14,
total_query_cycles=14,
),
QueryTiming(
accept_to_first_result_cycles=12,
accept_to_last_result_cycles=18,
total_query_cycles=18,
),
])
assert summary == {
"num_queries": 2,
"query_only_total_cycles": 32,
"query_only_cycles_per_query": 16.0,
"query_only_min_cycles": 14,
"query_only_max_cycles": 18,
"query_only_queries_per_cycle": 2 / 32,
"mean_accept_to_first_result_cycles": 11.0,
"mean_accept_to_last_result_cycles": 16.0,
"total_query_cycles": 32,
"mean_total_query_cycles": 16.0,
"min_total_query_cycles": 14,
"max_total_query_cycles": 18,
"cycles_per_query": 16.0,
"queries_per_cycle": 2 / 32,
}
def test_build_hardware_performance_separates_query_and_end_to_end_cycles() -> None:
performance = build_hardware_performance(
[
QueryTiming(
accept_to_first_result_cycles=10,
accept_to_last_result_cycles=14,
total_query_cycles=14,
),
QueryTiming(
accept_to_first_result_cycles=12,
accept_to_last_result_cycles=18,
total_query_cycles=18,
),
],
load_write_noise_cycles=100,
end_to_end_cycles=140,
)
assert performance["query_only_total_cycles"] == 32
assert performance["query_only_cycles_per_query"] == 16.0
assert performance["query_only_queries_per_cycle"] == 2 / 32
assert performance["load_write_noise_cycles"] == 100
assert performance["end_to_end_cycles"] == 140
assert performance["end_to_end_cycles_per_query"] == 70.0
assert performance["end_to_end_queries_per_cycle"] == 2 / 140
assert performance["cycles_per_query"] == performance["query_only_cycles_per_query"]
assert performance["queries_per_cycle"] == performance["query_only_queries_per_cycle"]
def test_write_outputs_includes_hardware_performance_fields(tmp_path: Path) -> None:
result = {
"run_id": "test-run",
"mode": "no_noise",
"status": "pass",
"params": {
"num_rows": 512,
"hash_bits": 512,
"lanes": 8,
"topk_k": 5,
"write_noise_en": 0,
"write_noise_rate_num": 0,
"write_noise_rate_den": 100,
},
"dataset": {
"num_classes": 10,
"positives_per_class": 0,
"queries_per_class": 0,
"num_queries": 2,
"seed": 0,
},
"metrics": {
"1": {
"macro_precision": 1.0,
"retrieval_recall": 0.5,
"macro_f1": 2 / 3,
"recall@k": 1.0,
"exact_match_rate": 1.0,
}
},
"performance": {
"num_queries": 2,
"query_only_total_cycles": 32,
"query_only_cycles_per_query": 16.0,
"query_only_min_cycles": 14,
"query_only_max_cycles": 18,
"query_only_queries_per_cycle": 2 / 32,
"mean_accept_to_first_result_cycles": 11.0,
"mean_accept_to_last_result_cycles": 16.0,
"load_write_noise_cycles": 100,
"end_to_end_cycles": 140,
"end_to_end_cycles_per_query": 70.0,
"end_to_end_queries_per_cycle": 2 / 140,
"total_query_cycles": 32,
"mean_total_query_cycles": 16.0,
"min_total_query_cycles": 14,
"max_total_query_cycles": 18,
"cycles_per_query": 16.0,
"queries_per_cycle": 2 / 32,
},
}
write_outputs(tmp_path, result)
with (tmp_path / "metrics.csv").open(newline="", encoding="utf-8") as f:
row = next(csv.DictReader(f))
assert row["query_only_cycles_per_query"] == "16.0"
assert row["query_only_total_cycles"] == "32"
assert row["query_only_queries_per_cycle"] == str(2 / 32)
assert row["load_write_noise_cycles"] == "100"
assert row["end_to_end_cycles"] == "140"
assert row["end_to_end_queries_per_cycle"] == str(2 / 140)
assert row["cycles_per_query"] == "16.0"
assert row["mean_accept_to_first_result_cycles"] == "11.0"
assert row["mean_accept_to_last_result_cycles"] == "16.0"
assert row["queries_per_cycle"] == str(2 / 32)
summary = (tmp_path / "summary.md").read_text(encoding="utf-8")
assert "## Hardware performance" in summary
assert "query-only cycles/query" in summary
assert "load/write/noise cycles" in summary
assert "end-to-end cycles/query" in summary
assert "accept_to_last_result_cycles" in summary