如何知道使用了哪个 malloc？

Question

据我了解，存在许多不同的 malloc 实现：

dlmalloc – 通用分配器
ptmalloc2 – glibc
jemalloc – FreeBSD 和 Firefox
tcmalloc – Google
libumem – Solaris

有什么方法可以确定我的 (linux) 系统上实际使用了哪个 malloc？

我读到 "due to ptmalloc2’s threading support, it became the default memory allocator for linux." 我可以自己检查一下吗？

我问是因为我似乎没有通过在下面的代码中并行化我的 malloc 循环来加快速度：

for (int i = 1; i <= 16; i += 1 ) {
    parallelMalloc(i);
}

 void parallelMalloc(int parallelism, int mallocCnt = 10000000) {

    omp_set_num_threads(parallelism);

    std::vector<char*> ptrStore(mallocCnt);

    boost::posix_time::ptime t1 = boost::posix_time::microsec_clock::local_time();

    #pragma omp parallel for
    for (int i = 0; i < mallocCnt; i++) {
        ptrStore[i] = ((char*)malloc(100 * sizeof(char)));
    }

    boost::posix_time::ptime t2 = boost::posix_time::microsec_clock::local_time();

    #pragma omp parallel for
    for (int i = 0; i < mallocCnt; i++) {
        free(ptrStore[i]);
    }

    boost::posix_time::ptime t3 = boost::posix_time::microsec_clock::local_time();


    boost::posix_time::time_duration malloc_time = t2 - t1;
    boost::posix_time::time_duration free_time   = t3 - t2;

    std::cout << " parallelism = "  << parallelism << "\t itr = " << mallocCnt <<  "\t malloc_time = " <<
            malloc_time.total_milliseconds() << "\t free_time = " << free_time.total_milliseconds() << std::endl;
}

这给了我

的输出

 parallelism = 1         itr = 10000000  malloc_time = 1225      free_time = 1517
 parallelism = 2         itr = 10000000  malloc_time = 1614      free_time = 1112
 parallelism = 3         itr = 10000000  malloc_time = 1619      free_time = 687
 parallelism = 4         itr = 10000000  malloc_time = 2325      free_time = 620
 parallelism = 5         itr = 10000000  malloc_time = 2233      free_time = 550
 parallelism = 6         itr = 10000000  malloc_time = 2207      free_time = 489
 parallelism = 7         itr = 10000000  malloc_time = 2778      free_time = 398
 parallelism = 8         itr = 10000000  malloc_time = 1813      free_time = 389
 parallelism = 9         itr = 10000000  malloc_time = 1997      free_time = 350
 parallelism = 10        itr = 10000000  malloc_time = 1922      free_time = 291
 parallelism = 11        itr = 10000000  malloc_time = 2480      free_time = 257
 parallelism = 12        itr = 10000000  malloc_time = 1614      free_time = 256
 parallelism = 13        itr = 10000000  malloc_time = 1387      free_time = 289
 parallelism = 14        itr = 10000000  malloc_time = 1481      free_time = 248
 parallelism = 15        itr = 10000000  malloc_time = 1252      free_time = 297
 parallelism = 16        itr = 10000000  malloc_time = 1063      free_time = 281

Answer 1

I read that "due to ptmalloc2’s threading support, it became the default memory allocator for linux." Is there any way for me to check this myself?

glibc 内部使用 ptmalloc2 这不是最近的发展。无论哪种方式，做 getconf GNU_LIBC_VERSION 都不是很难，然后交叉检查版本以查看该版本是否使用 ptmalloc2，但我敢打赌你会浪费你的时间。

I am asking because I do not seem to get any speed up by paralellizing my malloc loop in the code below

将您的示例转换为 MVCE（为简洁起见，此处省略代码），并使用 g++ -Wall -pedantic -O3 -pthread -fopenmp 进行编译，使用 g++ 5.3.1 这是我的结果。

使用 OpenMP：

 parallelism = 1     itr = 10000000  malloc_time = 746   free_time = 263
 parallelism = 2     itr = 10000000  malloc_time = 541   free_time = 267
 parallelism = 3     itr = 10000000  malloc_time = 405   free_time = 259
 parallelism = 4     itr = 10000000  malloc_time = 324   free_time = 221
 parallelism = 5     itr = 10000000  malloc_time = 330   free_time = 242
 parallelism = 6     itr = 10000000  malloc_time = 287   free_time = 244
 parallelism = 7     itr = 10000000  malloc_time = 257   free_time = 226
 parallelism = 8     itr = 10000000  malloc_time = 270   free_time = 225
 parallelism = 9     itr = 10000000  malloc_time = 253   free_time = 225
 parallelism = 10    itr = 10000000  malloc_time = 236   free_time = 226
 parallelism = 11    itr = 10000000  malloc_time = 225   free_time = 239
 parallelism = 12    itr = 10000000  malloc_time = 276   free_time = 258
 parallelism = 13    itr = 10000000  malloc_time = 241   free_time = 228
 parallelism = 14    itr = 10000000  malloc_time = 254   free_time = 225
 parallelism = 15    itr = 10000000  malloc_time = 278   free_time = 272
 parallelism = 16    itr = 10000000  malloc_time = 235   free_time = 220

23.87 user 
2.11 system 
0:10.41 elapsed 
249% CPU

没有 OpenMP：

 parallelism = 1     itr = 10000000  malloc_time = 748   free_time = 263
 parallelism = 2     itr = 10000000  malloc_time = 344   free_time = 256
 parallelism = 3     itr = 10000000  malloc_time = 751   free_time = 254
 parallelism = 4     itr = 10000000  malloc_time = 339   free_time = 262
 parallelism = 5     itr = 10000000  malloc_time = 748   free_time = 253
 parallelism = 6     itr = 10000000  malloc_time = 330   free_time = 256
 parallelism = 7     itr = 10000000  malloc_time = 734   free_time = 260
 parallelism = 8     itr = 10000000  malloc_time = 334   free_time = 259
 parallelism = 9     itr = 10000000  malloc_time = 750   free_time = 256
 parallelism = 10    itr = 10000000  malloc_time = 339   free_time = 255
 parallelism = 11    itr = 10000000  malloc_time = 743   free_time = 267
 parallelism = 12    itr = 10000000  malloc_time = 342   free_time = 261
 parallelism = 13    itr = 10000000  malloc_time = 739   free_time = 252
 parallelism = 14    itr = 10000000  malloc_time = 333   free_time = 252
 parallelism = 15    itr = 10000000  malloc_time = 740   free_time = 252
 parallelism = 16    itr = 10000000  malloc_time = 330   free_time = 252

13.38 user 
4.66 system 
0:18.08 elapsed 
99% CPU

并行度似乎快了大约 8 秒。还是不相信？好的。我继续抓取 dlmalloc、运行 make 产生 libmalloc.a。我的新命令是 g++ -Wall -pedantic -O3 -pthread -fopenmp -L$HOME/Development/test/dlmalloc/lib test.cpp -lmalloc

使用 OpenMP：

parallelism = 1  itr = 10000000  malloc_time = 814   free_time = 277

I CTRL-C'd 37 秒后.

没有 OpenMP：

 parallelism = 1     itr = 10000000  malloc_time = 772   free_time = 271
 parallelism = 2     itr = 10000000  malloc_time = 780   free_time = 272
 parallelism = 3     itr = 10000000  malloc_time = 783   free_time = 272
 parallelism = 4     itr = 10000000  malloc_time = 792   free_time = 277
 parallelism = 5     itr = 10000000  malloc_time = 813   free_time = 281
 parallelism = 6     itr = 10000000  malloc_time = 800   free_time = 275
 parallelism = 7     itr = 10000000  malloc_time = 795   free_time = 277
 parallelism = 8     itr = 10000000  malloc_time = 790   free_time = 273
 parallelism = 9     itr = 10000000  malloc_time = 788   free_time = 277
 parallelism = 10    itr = 10000000  malloc_time = 784   free_time = 276
 parallelism = 11    itr = 10000000  malloc_time = 786   free_time = 284
 parallelism = 12    itr = 10000000  malloc_time = 807   free_time = 279
 parallelism = 13    itr = 10000000  malloc_time = 791   free_time = 277
 parallelism = 14    itr = 10000000  malloc_time = 790   free_time = 273
 parallelism = 15    itr = 10000000  malloc_time = 785   free_time = 276
 parallelism = 16    itr = 10000000  malloc_time = 787   free_time = 275

6.48 user 
11.27 system 
0:17.81 elapsed 
99% CPU

非常显着的差异。我怀疑问题出在您更复杂的代码中，或者您的基准测试有问题。

如何知道使用了哪个 malloc？

How to know which malloc is used?

c++

malloc

heap-memory