mirror of
https://github.com/NVIDIA/nvbench.git
synced 2026-05-13 01:35:40 +00:00
4a22923721
Move NVBench JSON result parsing into cuda.bench.results with explicit BenchmarkResult, BenchmarkResultDevice, BenchmarkResultSummary, SubBenchmarkResult, and SubBenchmarkState types. Remove the result reader from the top-level cuda.bench namespace and require construction through BenchmarkResult.from_json() or BenchmarkResult.empty(). Preserve bulk sample/frequency parsing and estimator helpers while making summaries rich objects that retain tag/name/hint/hide/description metadata. Add nvbench-json-summary to render NVBench JSON output as an NVBench-style markdown summary table, including axis formatting, device sections, hidden summary filtering, and summary hint formatting. Update packaging, type stubs, and tests for the new namespace, renamed classes, Python 3.10-compatible annotations, and summary-table generation.
222 lines
8.8 KiB
Python
222 lines
8.8 KiB
Python
# Copyright 2026 NVIDIA Corporation
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 with the LLVM exception
|
|
# (the "License"); you may not use this file except in compliance with
|
|
# the License.
|
|
#
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://llvm.org/foundation/relicensing/LICENSE.txt
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
|
|
import importlib.util
|
|
import json
|
|
from pathlib import Path
|
|
|
|
|
|
def load_nvbench_json_summary():
|
|
module_path = (
|
|
Path(__file__).resolve().parents[1] / "scripts" / "nvbench_json_summary.py"
|
|
)
|
|
spec = importlib.util.spec_from_file_location("nvbench_json_summary", module_path)
|
|
assert spec is not None
|
|
assert spec.loader is not None
|
|
module = importlib.util.module_from_spec(spec)
|
|
spec.loader.exec_module(module)
|
|
return module
|
|
|
|
|
|
nvbench_json_summary = load_nvbench_json_summary()
|
|
|
|
|
|
def write_result_json(path):
|
|
path.write_text(
|
|
json.dumps(
|
|
{
|
|
"devices": [
|
|
{
|
|
"id": 0,
|
|
"name": "Test GPU",
|
|
}
|
|
],
|
|
"benchmarks": [
|
|
{
|
|
"name": "copy",
|
|
"devices": [0],
|
|
"axes": [
|
|
{
|
|
"name": "BlockSize",
|
|
"type": "int64",
|
|
"flags": "pow2",
|
|
"values": [
|
|
{
|
|
"input_string": "8",
|
|
"description": "2^8 = 256",
|
|
"value": 256,
|
|
}
|
|
],
|
|
}
|
|
],
|
|
"states": [
|
|
{
|
|
"name": "Device=0 BlockSize=2^8",
|
|
"device": 0,
|
|
"type_config_index": 0,
|
|
"axis_values": [
|
|
{
|
|
"name": "BlockSize",
|
|
"type": "int64",
|
|
"value": "256",
|
|
}
|
|
],
|
|
"summaries": [
|
|
{
|
|
"tag": "nv/cold/time/gpu/sample_size",
|
|
"name": "Samples",
|
|
"hint": "sample_size",
|
|
"data": [
|
|
{
|
|
"name": "value",
|
|
"type": "int64",
|
|
"value": "12",
|
|
}
|
|
],
|
|
},
|
|
{
|
|
"tag": "nv/cold/time/gpu/mean",
|
|
"name": "GPU Time",
|
|
"hint": "duration",
|
|
"data": [
|
|
{
|
|
"name": "value",
|
|
"type": "float64",
|
|
"value": "1.25e-6",
|
|
}
|
|
],
|
|
},
|
|
{
|
|
"tag": "nv/cold/time/gpu/stdev/relative",
|
|
"name": "Noise",
|
|
"hint": "percentage",
|
|
"data": [
|
|
{
|
|
"name": "value",
|
|
"type": "float64",
|
|
"value": "0.015",
|
|
}
|
|
],
|
|
},
|
|
{
|
|
"tag": "nv/cold/bw/global/bytes_per_second",
|
|
"name": "GlobalMem BW",
|
|
"hint": "byte_rate",
|
|
"data": [
|
|
{
|
|
"name": "value",
|
|
"type": "float64",
|
|
"value": "2.5e9",
|
|
}
|
|
],
|
|
},
|
|
{
|
|
"tag": "nv/cold/bw/global/utilization",
|
|
"name": "BWUtil",
|
|
"hint": "percentage",
|
|
"data": [
|
|
{
|
|
"name": "value",
|
|
"type": "float64",
|
|
"value": "0.625",
|
|
}
|
|
],
|
|
},
|
|
{
|
|
"tag": "nv/cold/time/gpu/min",
|
|
"name": "Min GPU Time",
|
|
"hint": "duration",
|
|
"hide": "Hidden by default.",
|
|
"data": [
|
|
{
|
|
"name": "value",
|
|
"type": "float64",
|
|
"value": "1.0e-6",
|
|
}
|
|
],
|
|
},
|
|
],
|
|
"is_skipped": False,
|
|
}
|
|
],
|
|
}
|
|
],
|
|
}
|
|
),
|
|
encoding="utf-8",
|
|
)
|
|
|
|
|
|
def test_json_summary_formats_nvbench_style_markdown(tmp_path):
|
|
json_path = tmp_path / "result.json"
|
|
write_result_json(json_path)
|
|
|
|
result = nvbench_json_summary.BenchmarkResult.from_json(json_path)
|
|
report = nvbench_json_summary.format_result(result)
|
|
|
|
assert "# Benchmark Results" in report
|
|
assert "## copy" in report
|
|
assert "### [0] Test GPU" in report
|
|
assert (
|
|
"| BlockSize | Samples | GPU Time | Noise | GlobalMem BW | BWUtil |" in report
|
|
)
|
|
assert (
|
|
"| 2^8 = 256 | 12x | 1.250 us | 1.50% | 2.500 GB/s | 62.50% |" in report
|
|
)
|
|
assert "Min GPU Time" not in report
|
|
|
|
|
|
def test_json_summary_formats_axis_values_like_markdown_printer():
|
|
axes_by_name = {
|
|
"BlockSize": {
|
|
"name": "BlockSize",
|
|
"type": "int64",
|
|
"flags": "pow2",
|
|
},
|
|
"NumBlocks": {
|
|
"name": "NumBlocks",
|
|
"type": "int64",
|
|
"flags": "",
|
|
},
|
|
"Duration": {
|
|
"name": "Duration",
|
|
"type": "float64",
|
|
"flags": "",
|
|
},
|
|
}
|
|
|
|
assert nvbench_json_summary.format_axis_value(
|
|
{"name": "BlockSize", "type": "int64", "value": "256"}, axes_by_name
|
|
) == ("BlockSize", "2^8 = 256")
|
|
assert nvbench_json_summary.format_axis_value(
|
|
{"name": "NumBlocks", "type": "int64", "value": "64"}, axes_by_name
|
|
) == ("NumBlocks", "64")
|
|
assert nvbench_json_summary.format_axis_value(
|
|
{"name": "Duration", "type": "float64", "value": "0.123456789"},
|
|
axes_by_name,
|
|
) == ("Duration", "0.12346")
|
|
|
|
|
|
def test_json_summary_cli_writes_output_file(tmp_path):
|
|
json_path = tmp_path / "result.json"
|
|
output_path = tmp_path / "summary.md"
|
|
write_result_json(json_path)
|
|
|
|
rc = nvbench_json_summary.main([str(json_path), "--output", str(output_path)])
|
|
|
|
assert rc == 0
|
|
assert "GlobalMem BW" in output_path.read_text(encoding="utf-8")
|