TBB：parallel_for 中的局部和全局结果
我有一个关于并行循环中的局部值和更新全局变量的问题。
例如，在伪代码中：我正在一个很长的向量中搜索最大值。我可以在循环中执行此操作，如下所示：
int max;
for(i ...) {
if (max < vector[i]) max = vector[i];
}
我可以轻松地将其与 OpenMP 并行化：
int max;
#pragma omp parallel
{
int local_max;
#pragma omp parallel for
for(i ...) {
if (local_max < vector[i]) local_max = vector[i];
}
#pragma omp critical
{
// choose the best solution from all
if (max < local_max) max = local_max; local_max
}
}
如何在 TBB parallel_for 中执行相同操作？我不要求确切的代码，我只想知道如何在循环结束时更新全局结果，而不是在每次迭代时更新......
（我是 TBB 新手）
I have a question regarding local values in a parallel loop, and updating a global variable.
Example, in pseudo-code: I am searching for a maximum value in a very long vector. I can do it in a loop, like that:
int max;
for(i ...) {
if (max < vector[i]) max = vector[i];
}
I can easily parallelize it with OpenMP:
int max;
#pragma omp parallel
{
int local_max;
#pragma omp parallel for
for(i ...) {
if (local_max < vector[i]) local_max = vector[i];
}
#pragma omp critical
{
// choose the best solution from all
if (max < local_max) max = local_max; local_max
}
}
How can I do the same in TBB parallel_for? I don't request an exact code, I would like just to know how to update the global result at the end of the loop, not at every iteration...
(I am new to TBB)
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您在此示例中执行的操作称为缩减，因此请使用
parallel_reduce。它应该比更新锁下的全局变量更有效。基本思想是，local_max是parallel_reduce的body类的成员变量，它的join()方法接收body的另一个实例并将local_max更新为当前值和另一个实例中的值中的较大者。然后在调用parallel_reduce之后，从原始主体对象中取出local_max值并将其分配给全局变量。What you do in this example is called reduction, so use
parallel_reduce. It should be more efficient than updating a global variable under a lock. The basic idea is thatlocal_maxis a member variable of the body class forparallel_reduce, and itsjoin()method receives another instance of the body and updateslocal_maxto be the bigger of the current value and the value in the other instance. Then after the call to parallel_reduce you take thelocal_maxvalue out of the original body object and assign it to the global variable.