CPU instruction set optimization in C++ function performance optimization

CPU instruction set optimization is a technology that improves function performance by utilizing specific instructions of modern CPUs, including: AVX instruction set: Provides SIMD instructions to process multiple data elements at once to improve performance. SSE instruction set: Provides SIMD instructions and advanced features such as secure memory copying. Practical case: Use AVX instructions to optimize image filters, significantly improve performance and shorten image processing time.

CPU instruction set optimization in C function performance optimization

Overview

CPU instruction set optimization is a technique for improving function performance by taking advantage of specific instructions provided by modern CPUs. These instructions are usually optimized for specific types of operations, such as floating point calculations or string processing. By using these instructions, execution time can be significantly reduced.

AVX Instruction Set

AVX (Advanced Vector Extensions) is a CPU instruction set that provides instructions for performing Single Instruction Multiple Data (SIMD) operations . SIMD operations improve performance by allowing the processor to process multiple data elements at once.

For example, the following code uses AVX instructions to calculate the sum of a set of numbers in parallel:

#include <immintrin.h>

__m256 sum(float* arr, size_t size) {
  __m256 sum_vec = _mm256_setzero_ps();
  for (size_t i = 0; i < size; i += 8) {
    __m256 val_vec = _mm256_loadu_ps(arr + i);
    sum_vec = _mm256_add_ps(sum_vec, val_vec);
  }
  return sum_vec;
}

SSE Instruction Set

SSE (Streaming SIMD Extension) is another CPU instruction set that provides instructions for performing SIMD operations and other advanced features.

For example, the following code uses SSE instructions to safely copy a set of memory:

#include <tmmintrin.h>

void secure_memcpy(void* dst, void* src, size_t size) {
  char* dst_char = (char*)dst;
  char* src_char = (char*)src;
  for (size_t i = 0; i < size; i += 16) {
    _mm_storeu_si128((__m128i*)dst_char, _mm_loadu_si128((__m128i*)src_char));
    dst_char += 16;
    src_char += 16;
  }
}

Practical case

The following is an optimization using the CPU instruction set Let’s use a practical case to optimize image processing tasks:

// 使用 AVX 指令并行化图像滤波器
__m256 filter_image(float* image, float* filter, size_t width, size_t height) {
  __m256filtered_image = _mm256_setzero_ps();
  for (size_t y = 0; y < height; y++) {
    for (size_t x = 0; x < width; x += 8) {
      __m256 image_vec = _mm256_loadu_ps(image + y * width + x);
      __m256 filter_vec = _mm256_loadu_ps(filter);
      filtered_image_vec = _mm256_add_ps(filtered_image_vec,
                          _mm256_mul_ps(image_vec, filter_vec));
    }
  }
  return filtered_image;
}

After using the CPU instruction set optimization, the performance of the image filter is significantly improved, thereby reducing the image processing time.

The above is the detailed content of CPU instruction set optimization in C++ function performance optimization. For more information, please follow other related articles on the PHP Chinese website!