before_optimize.cpp

#include <chrono>
#include <cstddef>
#include <iostream>
#include <random>
#include <vector>

using std::vector;

class FigureProcessor {
private:
    vector<vector<unsigned char>> figure;
    vector<vector<unsigned char>> result;
    const size_t size;

public:
    FigureProcessor(size_t size, size_t seed = 0) : size(size) {
        
        // !!! Please do not modify the following code !!!
        // 如果你需要修改内存的数据结构，请不要修改初始化的顺序和逻辑
        // 助教可能会通过指定某个初始化seed 的方式来验证你的代码
        // 如果你修改了初始化的顺序，可能会导致你的代码无法通过测试
        std::random_device rd;
        std::mt19937_64 gen(seed == 0 ? rd() : seed);
        std::uniform_int_distribution<unsigned char> distribution(0, 255);
        // !!! ----------------------------------------- !!!

        // 两个数组的初始化在这里，可以改动，但请注意 gen 的顺序是从上到下从左到右即可。
        for (size_t i = 0; i < size; ++i) {
            figure.push_back(vector<unsigned char>());
            for (size_t j = 0; j < size; ++j) {
                figure[i].push_back(static_cast<unsigned char>(distribution(gen)));
            }
        }

        for (size_t i = 0; i < size; ++i) {
            result.push_back(vector<unsigned char>());
            for (size_t j = 0; j < size; ++j) {
                result[i].push_back(0);
            }
        }
    }

    ~FigureProcessor() = default;

    // Gaussian filter
    // [[1, 2, 1], [2, 4, 2], [1, 2, 1]] / 16
    //FIXME: Feel free to optimize this function
    //Hint: You can use SIMD instructions to optimize this function
    void gaussianFilter() {
        // 处理内部区域
        for (size_t i = 1; i < size - 1; ++i) {
            for (size_t j = 1; j < size - 1; ++j) {
                result[i][j] =
                        (figure[i - 1][j - 1] + 2 * figure[i - 1][j] +
                         figure[i - 1][j + 1] + 2 * figure[i][j - 1] + 4 * figure[i][j] +
                         2 * figure[i][j + 1] + figure[i + 1][j - 1] +
                         2 * figure[i + 1][j] + figure[i + 1][j + 1]) /
                        16;
            }
        }

        for (size_t i = 1; i < size - 1; ++i) {
            result[i][0] =
                    (figure[i - 1][0] + 2 * figure[i - 1][0] + figure[i - 1][1] +
                     2 * figure[i][0] + 4 * figure[i][0] + 2 * figure[i][1] +
                     figure[i + 1][0] + 2 * figure[i + 1][0] + figure[i + 1][1]) /
                    16;

            result[i][size - 1] =
                    (figure[i - 1][size - 2] + 2 * figure[i - 1][size - 1] +
                     figure[i - 1][size - 1] + 2 * figure[i][size - 2] +
                     4 * figure[i][size - 1] + 2 * figure[i][size - 1] +
                     figure[i + 1][size - 2] + 2 * figure[i + 1][size - 1] +
                     figure[i + 1][size - 1]) /
                    16;
        }

        for (size_t j = 1; j < size - 1; ++j) {
            result[0][j] =
                    (figure[0][j - 1] + 2 * figure[0][j] + figure[0][j + 1] +
                     2 * figure[0][j - 1] + 4 * figure[0][j] + 2 * figure[0][j + 1] +
                     figure[1][j - 1] + 2 * figure[1][j] + figure[1][j + 1]) /
                    16;

            result[size - 1][j] =
                    (figure[size - 2][j - 1] + 2 * figure[size - 2][j] +
                     figure[size - 2][j + 1] + 2 * figure[size - 1][j - 1] +
                     4 * figure[size - 1][j] + 2 * figure[size - 1][j + 1] +
                     figure[size - 1][j - 1] + 2 * figure[size - 1][j] +
                     figure[size - 1][j + 1]) /
                    16;
        }

        // 处理四个角点
        // 左上角
        result[0][0] = (4 * figure[0][0] + 2 * figure[0][1] + 2 * figure[1][0] +
                                        figure[1][1]) /
                                     9; 

        // 右上角
        result[0][size - 1] = (4 * figure[0][size - 1] + 2 * figure[0][size - 2] +
                                                     2 * figure[1][size - 1] + figure[1][size - 2]) /
                                                    9;

        // 左下角
        result[size - 1][0] = (4 * figure[size - 1][0] + 2 * figure[size - 1][1] +
                                                     2 * figure[size - 2][0] + figure[size - 2][1]) /
                                                    9;

        // 右下角
        result[size - 1][size - 1] =
                (4 * figure[size - 1][size - 1] + 2 * figure[size - 1][size - 2] +
                 2 * figure[size - 2][size - 1] + figure[size - 2][size - 2]) /
                9;
    }

    // Power law transformation
    // FIXME: Feel free to optimize this function
    // Hint: LUT to optimize this function?
    void powerLawTransformation() {
        constexpr float gamma = 0.5f;
        
        for (size_t i = 0; i < size; ++i) {
            for (size_t j = 0; j < size; ++j) {
                if(figure[i][j] == 0) {
                    result[i][j] = 0;
                    continue;
                }
                float normalized = (figure[i][j]) / 255.0f;
                result[i][j] = static_cast<unsigned char>(
                        255.0f * std::pow(normalized, gamma) + 0.5f); 
            }
        }
    }

    // Run benchmark
    unsigned int calcChecksum() {
        unsigned int sum = 0;
        constexpr size_t mod = 1000000007;
        for (size_t i = 0; i < size; ++i) {
            for (size_t j = 0; j < size; ++j) {
                sum += result[i][j];
                sum %= mod;
            }
        }
        return sum;
    }
    void runBenchmark() {
        auto start = std::chrono::high_resolution_clock::now();
        gaussianFilter();
        auto middle = std::chrono::high_resolution_clock::now();

        unsigned int sum = calcChecksum();

        auto middle2 = std::chrono::high_resolution_clock::now();
        powerLawTransformation();
        auto end = std::chrono::high_resolution_clock::now();

        sum += calcChecksum();
        sum %= 1000000007;
        std::cout << "Checksum: " << sum << "\n";

        auto milliseconds =
                std::chrono::duration_cast<std::chrono::milliseconds>(middle - start) +
                std::chrono::duration_cast<std::chrono::milliseconds>(end - middle2);
        std::cout << "Benchmark time: " << milliseconds.count() << " ms\n";
    }
};

// Main function
// !!! Please do not modify the main function !!!
int main(int argc, const char **argv) {
    constexpr size_t size = 16384;
    FigureProcessor processor(size, argc > 1 ? std::stoul(argv[1]) : 0);
    processor.runBenchmark();
    return 0;
}