如何使用 C++ 从 macOS 的 Activity Monitor 应用程序获取 CPU、GPU 和 RAM 使用情况？

Question

我有一个 C++ 应用程序，我想分析 CPU、GPU 和 RAM 的使用情况。

所有这些信息都可以在 macOS 的 Monitor Control 应用程序中找到

现在我正在通过 shell 命令获取这些信息

const std::string getCPUCommand =
    "ps -p " + std::to_string(pid) + " -o %cpu | awk 'FNR == 2 {print $1}'";

但这只会获取 CPU 使用率，而不是 GPU，而且也是一个性能不高的命令。

有没有更好的方法来获取所有这些信息？

Answer 1

关于 CPU 和 RAM 使用情况，已在此回答 post

简单地说-

交换/虚拟内存

#include <sys/param.h>
#include <sys/mount.h>

struct statfs stats;
if(statfs("/",&stats)==0)
    FreeSwap=(unisgned long long)stats.f_bsize * stats.f_bfree;

xsw_usage 结构用于查找使用的总交换内存

xsw_usage used_swap={0};

unsigned int size=sizeof(used_swap);

内存

当前使用的内存-

#include <mach/vm_statistics.h>
#include <mach/mach_types.h>
#include <mach/mach_init.h>
#include <mach/mach_host.h>

int main(int argc, const char * argv[]) {
    vm_size_t page_size;
    mach_port_t mach_port;
    mach_msg_type_number_t count;
    vm_statistics64_data_t vm_stats;

    mach_port = mach_host_self();
    count = sizeof(vm_stats) / sizeof(natural_t);
    if (KERN_SUCCESS == host_page_size(mach_port, &page_size) &&
        KERN_SUCCESS == host_statistics64(mach_port, HOST_VM_INFO,
                                        (host_info64_t)&vm_stats, &count))
    {
        long long free_memory = (int64_t)vm_stats.free_count * (int64_t)page_size;

        long long used_memory = ((int64_t)vm_stats.active_count +
                                 (int64_t)vm_stats.inactive_count +
                                 (int64_t)vm_stats.wire_count) *  (int64_t)page_size;
        printf("free memory: %lld\nused memory: %lld\n", free_memory, used_memory);
    }

    return 0;
}

对于 GPU 的使用，您可以使用 NVIDIA 的Cuda Toolkit

特别适用于 Mac -

#include <stdlib.h>
#include <iostream>
#include <iomanip>
#include <cuda_runtime_api.h>

#define CUDA_CALL(function, ...)  { \
    cudaError_t status = function(__VA_ARGS__); \
    anyCheck(status == cudaSuccess, cudaGetErrorString(status), #function, __FILE__, __LINE__); \
}

void anyCheck(bool is_ok, const char *description, const char *function, const char *file, int line) {
    if (!is_ok) {
        std::cout << "Error: " << description << " in " << function << " at " << file << ":" << line << std::endl;
        exit(EXIT_FAILURE);
    }
}

int main() {
    int cudaDeviceCount;
    struct cudaDeviceProp deviceProp;
    size_t memFree, memTotal;

    CUDA_CALL(cudaGetDeviceCount, &cudaDeviceCount);

    for (int deviceId = 0; deviceId < cudaDeviceCount; ++deviceId) {
        CUDA_CALL(cudaSetDevice, deviceId);
        CUDA_CALL(cudaGetDeviceProperties, &deviceProp, deviceId);

        //std::cout.imbue(std::locale("en_US.utf8"));
        std::cout << "Device " << deviceId;
        std::cout << " [PCIe " << deviceProp.pciDomainID << ":" << deviceProp.pciBusID
                  << ":" << deviceProp.pciDeviceID << ".0]";
        std::cout << ": " << deviceProp.name << " (CC " << deviceProp.major << "." << deviceProp.minor << ")";
        CUDA_CALL(cudaMemGetInfo, &memFree, &memTotal);
        std::cout << ": " << std::setprecision(5) << memFree/(1024*1024.) 
                  << " of " << memTotal/(1024*1024.) << " MB (i.e. "
                  << std::setprecision(3) << 100*memFree/(float)memTotal << "%) Free"
                  << std::endl;
    }
    return 0;
}

Ref-cuda-smi for mac