昨天发了博文后,对并发编程开始有点兴趣,我就看了Paul E. McKenney大师的并行编程的那本书,那本书第四章重点将了多线程并发条件下的计数。有兴趣的同学可以看下,讲的比较详细。我就对大师基于每线程变量的统计计数器做了研究,实现了下。其实大师基本代码都已经敲出来了。我只是实现了一下,就当练练手,同时向大师致敬。
这个方法原理比较简单,就是每个线程维护自己的计数器,到了统计计数的时候,把每个线程的计数器的值加在一起,就是总计数器的值。当然加的时候要加锁保护。比较特殊的地方是定义了个
这个__thread声明的表示每个线程各自维护一个各自的int型变量 count,这就是江湖上传闻已久的TLS, Thread-Local Storage,有兴趣的同学可以学习Ulrich Drepper大牛的ELF handling of Thread-Local Storage。
这种方案使用场合是计数器自加很频繁,但是查看计数器的值不频繁的场合,因为查看总计数器需要加锁操作,而每个线程自加不需要加锁,每个线程各自维护各自的计数器。这种应用场景很普遍,前文中我需要设计的计数器就是这样。日常维护也许好长时间才看一样相关统计量。
下面上代码:
- #define _GNU_SOURCE
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#include<stdio.h>
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#include<pthread.h>
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#include<stdlib.h>
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#include<sys/poll.h>
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#include<unistd.h>
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#include<time.h>
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#include<linux/types.h>
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#define NR_THREADS 10
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#define COUNT 5000
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int __thread count = 0;
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int *pcount[NR_THREADS] = {NULL};
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int finalcount = 0;
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pthread_spinlock_t g_spinlock;
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void inc_count()
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{
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count++;
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}
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int read_count()
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{
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int t;
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int sum ;
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pthread_spin_lock(&g_spinlock);
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sum = finalcount;
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for(t = 0;t<NR_THREADS;t++)
- {
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if(pcount[t] != NULL)
- sum += *pcount[t];
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}
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pthread_spin_unlock(&g_spinlock);
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return sum;
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}
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-
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typedef struct
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{
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int nr;
- pthread_t tid;
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}Thread;
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Thread Threads[NR_THREADS];
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void count_register_thread(int idx)
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{
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pthread_spin_lock(&g_spinlock);
- pcount[idx] = &count;
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pthread_spin_unlock(&g_spinlock);
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}
-
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void count_unregister_thread(int idx)
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{
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pthread_spin_lock(&g_spinlock);
- finalcount += count;
- pcount[idx] = NULL;
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pthread_spin_unlock(&g_spinlock);
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}
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void *thr_function(void* arg)
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{
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int nr = *(int*)arg;
- fprintf(stderr,"the %d thread init successful\n",nr);
- struct timespec delay = {0};
- delay.tv_sec = 0;
- delay.tv_nsec = 1000000;
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struct timeval tv_begin,tv_end;
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__u64 interval = 0;
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- count_register_thread(nr);
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int i,j;
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- gettimeofday(&tv_begin,NULL);
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for(i = 0;i<COUNT;i++)
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{
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inc_count();
- nanosleep(&delay,NULL);
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}
- gettimeofday(&tv_end,NULL);
- interval = (tv_end.tv_sec -tv_begin.tv_sec)*1000000 + (tv_end.tv_usec-tv_begin.tv_usec);
- fprintf(stderr,"the thread %d cost %llu us\n", nr,interval);
- count_unregister_thread(nr);
- fprintf(stderr,"the %d thread will exit\n",nr);
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return NULL;
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}
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int main()
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{
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int i;
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pthread_spin_init(&g_spinlock,0);
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for(i= 0;i<NR_THREADS;i++)
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{
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Threads[i].nr = i;
- if(pthread_create(&Threads[i].tid,NULL, thr_function,&Threads[i].nr))
- {
- fprintf(stderr,"error happened when create thread %d\n",i);
- return 0;
- }
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}
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for(i= 0;i<10;i++)
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{
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- poll(NULL,0,500);
- fprintf(stderr,"MASTER PROC: the finalcount is %d now \n",read_count());
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}
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for(i = 0;i<NR_THREADS;i++)
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{
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if(pthread_join(Threads[i].tid,NULL))
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{
- fprintf(stderr,"error happened when join the thread %d\n",i);
- return ;
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}
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}
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fprintf(stderr,"MASTER PROC: at last finalcount is %d\n ",finalcount);
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return 0;
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}
运行结果如下:
- the 1 thread init successful
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the 0 thread init successful
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the 3 thread init successful
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the 4 thread init successful
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the 2 thread init successful
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the 5 thread init successful
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the 6 thread init successful
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the 7 thread init successful
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the 8 thread init successful
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the 9 thread init successful
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MASTER PROC: the finalcount is 4634 now
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MASTER PROC: the finalcount is 9255 now
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MASTER PROC: the finalcount is 13880 now
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MASTER PROC: the finalcount is 18482 now
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MASTER PROC: the finalcount is 23129 now
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MASTER PROC: the finalcount is 27761 now
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MASTER PROC: the finalcount is 32395 now
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MASTER PROC: the finalcount is 36992 now
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MASTER PROC: the finalcount is 41644 now
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MASTER PROC: the finalcount is 46282 now
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the thread 1 cost 5401657 us
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the thread 4 cost 5401638 us
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the 4 thread will exit
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the 1 thread will exit
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the thread 8 cost 5403640 us
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the 8 thread will exit
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the thread 7 cost 5404796 us
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the 7 thread will exit
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the thread 6 cost 5405765 us
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the 6 thread will exit
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the thread 2 cost 5405876 us
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the 2 thread will exit
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the thread 3 cost 5406989 us
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the 3 thread will exit
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the thread 0 cost 5410352 us
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the 0 thread will exit
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the thread 9 cost 5411182 us
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the 9 thread will exit
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the thread 5 cost 5412392 us
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the 5 thread will exit
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MASTER PROC: at last finalcount is 50000
通过结果可以看出以下几点:
1 总计数器是精确的,线程退出后,finalcount的值和预想值一致可以看出。
2 nanosleep 延迟并不精确。我理论运行时间是5秒,但是实际运行时间都是5.4秒。
参考文献:
1 Paul E. McKenney Is Parallel Programming Hard, And, If So, What Can You Do About It?
2 Ulrich Drepper ELF handling of Thread-Local Storage。
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