void *thread_worker2(void *args)

这是一个函数定义，它返回一个指向 void 类型的指针，函数名为 thread_worker2，参数为一个指向 void 类型的指针 args。这个函数可能是用来创建一个线程的工作函数。具体实现需要看上下文和代码。

相关问题

Write a multithreaded C program that calculates various statistical values for a list of numbers: • Average • Minimum • Maximum • Median • Standard deviation This program will be passed a series of numbers on the command line and will then create three separate worker threads first. One thread will determine the average of the numbers, the second will determine the maximum value, and the third will determine the minimum value. For example, suppose your program is passed the integers 90 81 78 95 79 72 85 The program will report The average value is 82 The minimum value is 72 The maximum value is 95 The variables representing the average, minimum, and maximum values will be stored globally. The worker threads will set these values, and the parent thread will output the values once the workers have exited. After that, add two more global variables and two more threads that will determine the median and the standard deviation, respectively.

Here's an implementation of the program in C:

#include <stdio.h>
#include <stdlib.h>
#include <pthread.h>
#include <math.h>

// Global variables for storing statistical values
double average = 0.0;
int minimum = 0;
int maximum = 0;
double median = 0.0;
double std_dev = 0.0;

// Struct for passing arguments to worker threads
typedef struct {
    int* numbers;
    int count;
} thread_args;

// Worker thread for calculating average
void* calculate_average(void* args) {
    thread_args* targs = (thread_args*) args;
    int* numbers = targs->numbers;
    int count = targs->count;
    double sum = 0.0;
    for (int i = 0; i < count; i++) {
        sum += numbers[i];
    }
    average = sum / count;
    pthread_exit(NULL);
}

// Worker thread for calculating minimum
void* calculate_minimum(void* args) {
    thread_args* targs = (thread_args*) args;
    int* numbers = targs->numbers;
    int count = targs->count;
    minimum = numbers[0];
    for (int i = 1; i < count; i++) {
        if (numbers[i] < minimum) {
            minimum = numbers[i];
        }
    }
    pthread_exit(NULL);
}

// Worker thread for calculating maximum
void* calculate_maximum(void* args) {
    thread_args* targs = (thread_args*) args;
    int* numbers = targs->numbers;
    int count = targs->count;
    maximum = numbers[0];
    for (int i = 1; i < count; i++) {
        if (numbers[i] > maximum) {
            maximum = numbers[i];
        }
    }
    pthread_exit(NULL);
}

// Worker thread for calculating median
void* calculate_median(void* args) {
    thread_args* targs = (thread_args*) args;
    int* numbers = targs->numbers;
    int count = targs->count;
    int* sorted_numbers = malloc(count * sizeof(int));
    for (int i = 0; i < count; i++) {
        sorted_numbers[i] = numbers[i];
    }
    for (int i = 0; i < count - 1; i++) {
        for (int j = i + 1; j < count; j++) {
            if (sorted_numbers[i] > sorted_numbers[j]) {
                int temp = sorted_numbers[i];
                sorted_numbers[i] = sorted_numbers[j];
                sorted_numbers[j] = temp;
            }
        }
    }
    if (count % 2 == 0) {
        median = (sorted_numbers[count / 2 - 1] + sorted_numbers[count / 2]) / 2.0;
    } else {
        median = sorted_numbers[count / 2];
    }
    free(sorted_numbers);
    pthread_exit(NULL);
}

// Worker thread for calculating standard deviation
void* calculate_std_dev(void* args) {
    thread_args* targs = (thread_args*) args;
    int* numbers = targs->numbers;
    int count = targs->count;
    double sum = 0.0;
    for (int i = 0; i < count; i++) {
        sum += pow(numbers[i] - average, 2);
    }
    std_dev = sqrt(sum / count);
    pthread_exit(NULL);
}

int main(int argc, char* argv[]) {
    // Parse command line arguments
    if (argc < 2) {
        printf("Usage: %s <number1> <number2> ... <numberN>\n", argv[0]);
        return 1;
    }
    int count = argc - 1;
    int* numbers = malloc(count * sizeof(int));
    for (int i = 0; i < count; i++) {
        numbers[i] = atoi(argv[i + 1]);
    }

    // Create worker threads
    pthread_t threads[5];
    thread_args targs = {numbers, count};
    pthread_create(&threads[0], NULL, calculate_average, &targs);
    pthread_create(&threads[1], NULL, calculate_minimum, &targs);
    pthread_create(&threads[2], NULL, calculate_maximum, &targs);
    pthread_create(&threads[3], NULL, calculate_median, &targs);
    pthread_create(&threads[4], NULL, calculate_std_dev, &targs);

    // Wait for worker threads to complete
    for (int i = 0; i < 5; i++) {
        pthread_join(threads[i], NULL);
    }

    // Print results
    printf("The average value is %.2f\n", average);
    printf("The minimum value is %d\n", minimum);
    printf("The maximum value is %d\n", maximum);
    printf("The median value is %.2f\n", median);
    printf("The standard deviation is %.2f\n", std_dev);

    // Clean up
    free(numbers);

    return 0;
}

The program takes a list of numbers as command line arguments, creates five worker threads to calculate statistical values, and then outputs the results once the worker threads have completed their calculations. Note that the median calculation uses a simple sorting algorithm to sort the list of numbers first. This may not be efficient for very large lists of numbers, but it works well enough for small lists. Also note that the standard deviation calculation uses the formula for sample standard deviation, which divides by N-1 instead of N to correct for bias.

利用freertos的线程写一个线程池

可以通过以下步骤实现使用 FreeRTOS 的线程编写线程池：

1. 定义线程池结构体：

typedef struct {
    int num_threads; // 线程数
    TaskHandle_t *threads; // 线程句柄数组
    SemaphoreHandle_t task_sem; // 任务信号量
    SemaphoreHandle_t done_sem; // 完成信号量
    task_func_t *task_funcs; // 任务函数数组
    void **task_args; // 任务参数数组
    int *task_results; // 任务结果数组
    int next_task; // 下一个任务的索引
} thread_pool_t;

2. 初始化线程池：

void thread_pool_init(thread_pool_t *pool, int num_threads) {
    pool->num_threads = num_threads;
    pool->threads = malloc(num_threads * sizeof(TaskHandle_t));
    pool->task_funcs = malloc(num_threads * sizeof(task_func_t));
    pool->task_args = malloc(num_threads * sizeof(void *));
    pool->task_results = malloc(num_threads * sizeof(int));
    pool->next_task = 0;

    pool->task_sem = xSemaphoreCreateBinary();
    pool->done_sem = xSemaphoreCreateCounting(num_threads, 0);

    for (int i = 0; i < num_threads; i++) {
        xTaskCreatePinnedToCore(thread_pool_worker, "worker", 4096, (void *)pool, 5, &pool->threads[i], 0);
    }
}

3. 定义任务函数类型：

typedef void *(*task_func_t)(void *);

4. 定义线程池工作函数：

void thread_pool_worker(void *arg) {
    thread_pool_t *pool = (thread_pool_t *)arg;
    for (;;) {
        // 等待任务信号量
        xSemaphoreTake(pool->task_sem, portMAX_DELAY);
        
        // 获取下一个任务
        int task_index = pool->next_task++;
        
        // 执行任务
        if (task_index < pool->num_threads) {
            pool->task_results[task_index] = pool->task_funcs[task_index](pool->task_args[task_index]);
        }

        // 发送完成信号量
        xSemaphoreGive(pool->done_sem);
    }
}

5. 提交任务到线程池：

int thread_pool_submit(thread_pool_t *pool, task_func_t func, void *arg) {
    if (pool->next_task >= pool->num_threads) {
        return -1; // 线程池已满
    }

    int task_index = pool->next_task++;

    pool->task_funcs[task_index] = func;
    pool->task_args[task_index] = arg;

    // 发送任务信号量
    xSemaphoreGive(pool->task_sem);

    return task_index;
}

6. 等待线程池中所有任务完成：

void thread_pool_wait(thread_pool_t *pool) {
    for (int i = 0; i < pool->num_threads; i++) {
        xSemaphoreTake(pool->done_sem, portMAX_DELAY);
    }
}

7. 销毁线程池：

void thread_pool_destroy(thread_pool_t *pool) {
    vSemaphoreDelete(pool->task_sem);
    vSemaphoreDelete(pool->done_sem);
    for (int i = 0; i < pool->num_threads; i++) {
        vTaskDelete(pool->threads[i]);
    }
    free(pool->threads);
    free(pool->task_funcs);
    free(pool->task_args);
    free(pool->task_results);
}

这样，我们就可以使用 FreeRTOS 的线程实现一个简单的线程池。