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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,115 @@ | ||
| /* | ||
| * Copyright (c) 2021, NVIDIA CORPORATION. | ||
| * | ||
| * Licensed under the Apache License, Version 2.0 (the "License"); | ||
| * you may not use this file except in compliance with the License. | ||
| * You may obtain a copy of the License at | ||
| * | ||
| * http://www.apache.org/licenses/LICENSE-2.0 | ||
| * | ||
| * 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. | ||
| */ | ||
|
|
||
| #include <cudf/copying.hpp> | ||
| #include <cudf/detail/aggregation/aggregation.hpp> | ||
| #include <cudf/groupby.hpp> | ||
| #include <cudf/sorting.hpp> | ||
| #include <cudf/table/table.hpp> | ||
| #include <cudf_test/column_wrapper.hpp> | ||
| #include <fixture/benchmark_fixture.hpp> | ||
| #include <synchronization/synchronization.hpp> | ||
|
|
||
| #include <memory> | ||
| #include <random> | ||
|
|
||
| class Groupby : public cudf::benchmark { | ||
| }; | ||
|
|
||
| // TODO: put it in a struct so `uniform` can be remade with different min, max | ||
| template <typename T> | ||
| T random_int(T min, T max) | ||
| { | ||
| static unsigned seed = 13377331; | ||
| static std::mt19937 engine{seed}; | ||
| static std::uniform_int_distribution<T> uniform{min, max}; | ||
|
|
||
| return uniform(engine); | ||
| } | ||
|
|
||
| void BM_basic_no_requests(benchmark::State& state) | ||
| { | ||
| using wrapper = cudf::test::fixed_width_column_wrapper<int64_t>; | ||
|
|
||
| const cudf::size_type column_size{(cudf::size_type)state.range(0)}; | ||
|
|
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| auto data_it = cudf::detail::make_counting_transform_iterator( | ||
| 0, [=](cudf::size_type row) { return random_int(0, 100); }); | ||
|
|
||
| wrapper keys(data_it, data_it + column_size); | ||
| wrapper vals(data_it, data_it + column_size); | ||
|
|
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| std::vector<cudf::groupby::aggregation_request> requests; | ||
|
|
||
| for (auto _ : state) { | ||
| cuda_event_timer timer(state, true); | ||
| cudf::groupby::groupby gb_obj(cudf::table_view({keys})); | ||
| auto result = gb_obj.aggregate(requests); | ||
| } | ||
| } | ||
|
|
||
| BENCHMARK_DEFINE_F(Groupby, BasicNoRequest)(::benchmark::State& state) | ||
| { | ||
| BM_basic_no_requests(state); | ||
| } | ||
|
|
||
| BENCHMARK_REGISTER_F(Groupby, BasicNoRequest) | ||
| ->UseManualTime() | ||
| ->Unit(benchmark::kMillisecond) | ||
| ->Arg(10000) | ||
| ->Arg(1000000) | ||
| ->Arg(10000000) | ||
| ->Arg(100000000); | ||
|
|
||
| void BM_pre_sorted_no_requests(benchmark::State& state) | ||
| { | ||
| using wrapper = cudf::test::fixed_width_column_wrapper<int64_t>; | ||
|
|
||
| const cudf::size_type column_size{(cudf::size_type)state.range(0)}; | ||
|
|
||
| auto data_it = cudf::detail::make_counting_transform_iterator( | ||
| 0, [=](cudf::size_type row) { return random_int(0, 100); }); | ||
| auto valid_it = cudf::detail::make_counting_transform_iterator( | ||
| 0, [=](cudf::size_type row) { return random_int(0, 100) < 90; }); | ||
|
|
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| wrapper keys(data_it, data_it + column_size); | ||
| wrapper vals(data_it, data_it + column_size, valid_it); | ||
|
|
||
| auto keys_table = cudf::table_view({keys}); | ||
| auto sort_order = cudf::sorted_order(keys_table); | ||
| auto sorted_keys = cudf::gather(keys_table, *sort_order); | ||
| // No need to sort values using sort_order because they were generated randomly | ||
|
|
||
| std::vector<cudf::groupby::aggregation_request> requests; | ||
|
|
||
| for (auto _ : state) { | ||
| cuda_event_timer timer(state, true); | ||
| cudf::groupby::groupby gb_obj(*sorted_keys, cudf::null_policy::EXCLUDE, cudf::sorted::YES); | ||
| auto result = gb_obj.aggregate(requests); | ||
| } | ||
| } | ||
|
|
||
| BENCHMARK_DEFINE_F(Groupby, PreSortedNoRequests)(::benchmark::State& state) | ||
| { | ||
| BM_pre_sorted_no_requests(state); | ||
| } | ||
|
|
||
| BENCHMARK_REGISTER_F(Groupby, PreSortedNoRequests) | ||
| ->UseManualTime() | ||
| ->Unit(benchmark::kMillisecond) | ||
| ->Arg(1000000) | ||
| ->Arg(10000000) | ||
| ->Arg(100000000); |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,121 @@ | ||
| # | ||
| # Copyright (c) 2021, NVIDIA CORPORATION. | ||
| # | ||
| import argparse | ||
| import os | ||
| import sys | ||
| import xml.etree.ElementTree as ET | ||
| from xml.dom import minidom | ||
|
|
||
| parser = argparse.ArgumentParser() | ||
| parser.add_argument( | ||
| "log_file", type=str, default=".ninja_log", help=".ninja_log file" | ||
| ) | ||
| parser.add_argument( | ||
| "--fmt", | ||
| type=str, | ||
| default="csv", | ||
| choices=["csv", "xml", "html"], | ||
| help="output format (to stdout)", | ||
| ) | ||
| parser.add_argument( | ||
| "--msg", | ||
| type=str, | ||
| default=None, | ||
| help="optional message to include in html output", | ||
| ) | ||
| args = parser.parse_args() | ||
|
|
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| log_file = args.log_file | ||
| log_path = os.path.dirname(os.path.abspath(log_file)) | ||
|
|
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| output_fmt = args.fmt | ||
|
|
||
| # build a map of the log entries | ||
| entries = {} | ||
| with open(log_file, "r") as log: | ||
| for line in log: | ||
| entry = line.split() | ||
| if len(entry) > 4: | ||
| elapsed = int(entry[1]) - int(entry[0]) | ||
| obj_file = entry[3] | ||
| file_size = ( | ||
| os.path.getsize(os.path.join(log_path, obj_file)) | ||
| if os.path.exists(obj_file) | ||
| else 0 | ||
| ) | ||
| entries[entry[3]] = (elapsed, file_size) | ||
|
|
||
| # check file could be loaded | ||
| if len(entries) == 0: | ||
| print("Could not parse", log_file) | ||
| exit() | ||
|
|
||
| # sort the keys by build time (descending order) | ||
| keys = list(entries.keys()) | ||
| sl = sorted(keys, key=lambda k: entries[k][0], reverse=True) | ||
|
|
||
| if output_fmt == "xml": | ||
| # output results in XML format | ||
| root = ET.Element("testsuites") | ||
| testsuite = ET.Element( | ||
| "testsuite", | ||
| attrib={ | ||
| "name": "build-time", | ||
| "tests": str(len(keys)), | ||
| "failures": str(0), | ||
| "errors": str(0), | ||
| }, | ||
| ) | ||
| root.append(testsuite) | ||
| for key in sl: | ||
| entry = entries[key] | ||
| elapsed = float(entry[0]) / 1000 | ||
| item = ET.Element( | ||
| "testcase", | ||
| attrib={ | ||
| "classname": "BuildTime", | ||
| "name": key, | ||
| "time": str(elapsed), | ||
| }, | ||
| ) | ||
| testsuite.append(item) | ||
|
|
||
| tree = ET.ElementTree(root) | ||
| xmlstr = minidom.parseString(ET.tostring(root)).toprettyxml(indent=" ") | ||
| print(xmlstr) | ||
|
|
||
| elif output_fmt == "html": | ||
| # output results in HTML format | ||
| print("<html><head><title>Sorted Ninja Build Times</title>") | ||
| print("<style>", "table, th, td { border:1px solid black; }", "</style>") | ||
| print("</head><body>") | ||
| if args.msg is not None: | ||
| print("<p>", args.msg, "</p>") | ||
| print("<table>") | ||
| print( | ||
| "<tr><th>File</th>", | ||
| "<th align='right'>Compile time (ms)</th>", | ||
| "<th align='right'>Size (bytes)</th><tr>", | ||
| sep="", | ||
| ) | ||
| for key in sl: | ||
| result = entries[key] | ||
| print( | ||
| "<tr><td>", | ||
| key, | ||
| "</td><td align='right'>", | ||
| result[0], | ||
| "</td><td align='right'>", | ||
| result[1], | ||
| "</td></tr>", | ||
| sep="", | ||
| ) | ||
| print("</table></body></html>") | ||
|
|
||
| else: | ||
| # output results in CSV format | ||
| print("time,size,file") | ||
| for key in sl: | ||
| result = entries[key] | ||
| print(result[0], result[1], key, sep=",") |
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