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Abhigyan AcherjeeAbhigyan Acherjee
Abhigyan Acherjee
authored and
Abhigyan Acherjee
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Added benchmark plots, amended RooFitBinned benchmarks, and added bash script
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4 files changed

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4 files changed

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lines changed

‎root/roofit/roofit/CMakeLists.txt

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@@ -19,6 +19,8 @@ if(cuda)
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endif()
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file(COPY ${CMAKE_CURRENT_SOURCE_DIR}/benchRooFitBackends_make_plot.py DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/)
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file(COPY ${CMAKE_CURRENT_SOURCE_DIR}/compare_benchmarks.py DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/)
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file(COPY ${CMAKE_CURRENT_SOURCE_DIR}/run_benchmarks.sh DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/)
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RB_ADD_GBENCHMARK(benchCodeSquashAD
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benchCodeSquashAD.cxx

‎root/roofit/roofit/RooFitBinnedBenchmarks.cxx

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@@ -26,10 +26,48 @@ namespace {
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const std::vector<int> nBinsVector {5, 10, 15};
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const int nBinsForChannelScan = 10;
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const int nChannelsForBinScan = 1;
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const std::vector<int> nCPUVector {1, 2, 3};
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//const std::vector<int> nCPUVector {1, 2, 3};
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const std::vector<int> nCPUVector {1};
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////default evaluation backend
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//constexpr auto evalBackend = RooFit::EvalBackend::Value::Legacy;
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std::string evalBackend="cpu";
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//RooFit::EvalBackend::Value evalBackend = RooFit::EvalBackend::Value::Legacy;
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constexpr auto evalBackend = RooFit::EvalBackend::Value::Cpu;
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// Function to parse enum from string
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// RooFit::EvalBackend::Value parseEvalBackend(const std::string& str)
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// {
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// if (str == "Cpu")
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// {
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// return RooFit::EvalBackend::Value::Cpu;
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// }
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// else if (str == "Codegen")
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// {
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// return RooFit::EvalBackend::Value::Codegen;
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// }
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// else if (str == "CodegenNoGrad")
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// {
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// return RooFit::EvalBackend::Value::CodegenNoGrad;
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// }
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// else if (str == "Legacy")
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// {
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// return RooFit::EvalBackend::Value::Legacy;
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// }
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// else {
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// throw std::invalid_argument("Invalid evalBackend value");
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// }
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// }
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// // Command-line flag to set evalBackend
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// void CustomArguments(benchmark::internal::Benchmark* b)
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// {
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// // Define a command-line argument to specify evalBackend
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// static std::vector<std::string> evalBackendValues = {"Cpu", "Codegen","CodegenNoGrad","Legacy"}; // Add more values if needed
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// for (const auto& value : evalBackendValues)
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// {
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// b->Arg(value);
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// }
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// }
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auto const timeUnit = benchmark::kMillisecond;
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void setupRooMsgService() {
@@ -274,4 +312,27 @@ BENCHMARK(BM_RooFit_BinnedTestMinos)
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//####################################################################
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//############## RUN #################################################
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BENCHMARK_MAIN();
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////BENCHMARK_MAIN();
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int main(int argc, char** argv)
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{
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benchmark::Initialize(&argc, argv);
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for (int i = 1; i < argc; ++i)
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{
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if (std::string(argv[i]) == "-b")
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{
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if (i + 1 < argc)
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{
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// Set the evalBackend value from the next command-line argument
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evalBackend = argv[i+1];//parseEvalBackend(argv[i + 1]);
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}
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else
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{
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std::cerr << "Missing value for --evalBackend argument" << std::endl;
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return 1;
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}
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}
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}
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benchmark::RunSpecifiedBenchmarks();
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}

‎root/roofit/roofit/compare_benchmarks.py

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import pandas as pd
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import csv
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import matplotlib.pyplot as plt
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import numpy as np
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def parse_and_writer(csv_file_path,name):
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with open(csv_file_path, 'r', newline='') as csvfile:
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reader = csv.reader(csvfile)
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for _ in range(8):
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next(reader)
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filtered_csv_file_path=""+name+".csv"
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with open(filtered_csv_file_path, 'w', newline='') as filtered_csvfile:
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writer = csv.writer(filtered_csvfile)
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for row in reader:
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writer.writerow(row)
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parse_and_writer("./out_codegen.csv","codegen")
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parse_and_writer("./out_codegen_ngrad.csv","codegen_ngrad")
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parse_and_writer("./out_cpu.csv","cpu")
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parse_and_writer("./out_legacy.csv","legacy")
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codegen_df=pd.read_csv("codegen.csv")
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codegen_nograd_df=pd.read_csv("codegen_ngrad.csv")
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legacy_df=pd.read_csv("legacy.csv")
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cpu_df=pd.read_csv("cpu.csv")
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# Plotting
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plt.figure(figsize=(10, 6))
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x = np.arange(len(codegen_df['name'].unique()))
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for i, benchmark in enumerate(codegen_df['name'].unique()):
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codegen_time = codegen_df.loc[codegen_df['name'] == benchmark, 'real_time']
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codegen_nograd_time = codegen_nograd_df.loc[codegen_nograd_df['name'] == benchmark, 'real_time']
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cpu_time = cpu_df.loc[cpu_df['name'] == benchmark, 'real_time']
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legacy_time = legacy_df.loc[legacy_df['name'] == benchmark, 'real_time']
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plt.bar(x[i]-0.10, codegen_time, width=0.15, align='center', label='codegen',color='lightblue')
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plt.bar(x[i], codegen_nograd_time, width=0.15, align='edge', label='codegen_nograd',color='navy')
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plt.bar(x[i]+0.15, cpu_time, width=0.15, align='edge', label='cpu',color='cyan')
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plt.bar(x[i]+0.30, legacy_time, width=0.15, align='edge', label='legacy',color='gray')
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# Customize legend
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legend_labels = ['codegen', 'codegen_nograd', 'cpu','legacy']
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legend_colors = ['lightblue', 'navy', 'cyan','gray']
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legend_handles = [plt.Rectangle((0,0),1,1, color=color) for color in legend_colors]
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plt.legend(legend_handles, legend_labels)
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plt.yscale('log')
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plt.xlabel('Benchmark')
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plt.ylabel('Time (milliseconds)')
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plt.title('Comparison of Benchmarks for Different Evaluation Backends')
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plt.xticks(x, rotation=90)
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plt.tight_layout()
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plt.savefig('comparision_plot.jpg')
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plt.show()

‎root/roofit/roofit/run_benchmarks.sh

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#!/bin/bash
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# Function to run a benchmark script and wait until the CSV file is generated
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# to make it executable chmod +x run_benchmarks.sh
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#then run it using ./run_benchmarks.sh
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#!/bin/bash
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# Function to run the benchmark command and wait for CSV file to be generated
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run_benchmark() {
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echo "Running benchmark: $1"
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$1 &
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local pid=$!
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while [ ! -f $2 ]; do
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sleep 1
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done
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wait $pid
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echo "CSV file generated: $2"
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}
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# Run benchmarks
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run_benchmark "./benchRooFitBinned -b codegen --benchmark_out_format=csv --benchmark_out=out_codegen.csv" "out_codegen.csv"
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run_benchmark "./benchRooFitBinned -b codegen_no_grad --benchmark_out_format=csv --benchmark_out=out_codegen_ngrad.csv" "out_codegen_ngrad.csv"
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run_benchmark "./benchRooFitBinned -b legacy --benchmark_out_format=csv --benchmark_out=out_legacy.csv" "out_legacy.csv"
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run_benchmark "./benchRooFitBinned -b cpu --benchmark_out_format=csv --benchmark_out=out_cpu.csv" "out_cpu.csv"
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# Run Python script
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python3 compare_benchmarks.py

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