Performance comparison of popular libraries and frameworks in the C++ ecosystem

Libraries and frameworks vary in performance across the C++ ecosystem: Boost excels in vector and string processing. Eigen is the most efficient among matrix operations. fmt provides the fastest string formatting. Protobuf takes the lead in binary serialization.

Performance comparison of popular libraries and frameworks in the C++ ecosystem

Introduction

C++ is a powerful programming language with a rich ecosystem of libraries and frameworks that simplify development, improve code quality, and optimize performance. This article will explore the performance differences of several popular C++ libraries and frameworks and illustrate them with practical examples.

Benchmark.js

For performance comparison, we will use Benchmark.js, a library for Node.js and browser performance testing. This library provides an easy-to-use API for creating and running benchmarks.

Libraries and frameworks participating in the test

• Boost: A set of cross-platform C++ libraries that provide various functions.
• Eigen: A line generation library optimized for numerically intensive calculations.
• fmt: A fast and efficient formatting library.
• Protobuf: A binary protocol for data serialization and deserialization.

Practical case

We will compare the performance of these libraries and frameworks in the following scenarios:

• Vector calculation
• Matrix Multiplication
• String Formatting
• Binary Serialization

##Code Example

Vector calculation

#include <iostream>
#include <vector>
#include <benchmark/benchmark.h>

using namespace std;

void BM_VectorSum(benchmark::State& state) {
  vector<double> v(state.range(0));
  for (auto _ : state) {
    double sum = 0;
    for (auto x : v) {
      sum += x;
    }
  }
}

Matrix multiplication

#include <iostream>
#include <Eigen/Dense>
#include <benchmark/benchmark.h>

using namespace Eigen;

void BM_MatrixMult(benchmark::State& state) {
  MatrixXd A = MatrixXd::Random(state.range(0), state.range(1));
  MatrixXd B = MatrixXd::Random(state.range(1), state.range(2));
  for (auto _ : state) {
    MatrixXd C = A * B;
  }
}

String formatting

#include <iostream>
#include <fmt/core.h>
#include <benchmark/benchmark.h>

using namespace fmt;

void BM_StringFormat(benchmark::State& state) {
  for (auto _ : state) {
    format("Hello, {}!", "World");
  }
}

Binary sequence ization

#include <iostream>
#include <google/protobuf/message.h>
#include <benchmark/benchmark.h>

using namespace google::protobuf;

class MyMessage : public Message {
 public:
  int32_t id;
  string name;
};

void BM_ProtobufSerialize(benchmark::State& state) {
  MyMessage msg;
  msg.id = 1;
  msg.name = "John";
  for (auto _ : state) {
    msg.SerializeToString();
  }
}

Result Analysis

Benchmark results may vary depending on system configuration and compiler optimizations. However, in general, we observe the following results:

Boost performs well on vector and string processing.
• Eigen is the most efficient among matrix operations.
• fmt provides the fastest string formatting.
• Protobuf stands out in binary serialization.

Conclusion

This article demonstrated the performance differences of popular libraries and frameworks in the C++ ecosystem. Through practical cases, we see which library or framework is most suitable in different scenarios. This helps developers make informed decisions in performance-critical applications.

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