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C++ Intel TBB 和 Microsoft PPL,如何在并行循环中使用 next_permutation?

转载 作者:搜寻专家 更新时间:2023-10-31 01:10:08 25 4
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我安装了 Visual Studio 2012 和 Intel parallel studio 2013,所以我有 Intel TBB。

假设我有以下代码:

const int cardsCount = 12; // will be READ by all threads
// the required number of cards of each colour to complete its set:
// NOTE that the required number of cards of each colour is not the same as the total number of cards of this colour available
int required[] = {2,3,4}; // will be READ by all threads
Card cards[cardsCount]; // will be READ by all threads
int cardsIndices[cardsCount];// this will be permuted, permutations need to be split among threads !

// set "cards" to 4 cards of each colour (3 colours total = 12 cards)
// set cardsIndices to {0,1,2,3...,11}

// this variable will be written to by all threads, maybe have one for each thread and combine them later?? or can I use concurrent_vector<int> instead !?
int logColours[] = {0,0,0};

int permutationsCount = fact(cardsCount);

for (int pNum=0; pNum<permutationsCount; pNum++) // I want to make this loop parallel !!
{
int countColours[3] = {0,0,0}; // local loop variable, no problem with multithreading
for (int i=0; i<cardsCount; i++)
{
Card c = cards[cardsIndices[i]]; // accessed "cards"

countColours[c.Colour]++; // local loop variable, np.
// we got the required number of cards of this colour to complete it
if (countColours[c.Colour] == required[c.Colour]) // read global variable "required" !
{
// log that we completed this colour and go to next permutation
logColours[c.Colour] ++; // should I use a concurrent_vector<int> for this shared variable?
break;
}
}
std::next_permutation(cardsIndices, cardsIndices+cardsCount); // !! this is my main issue
}

我正在计算的是,如果我们从可用的卡片中随机挑选,我们将完成多少次颜色,这是通过遍历每个可能的排列并按顺序挑选来完成的,当颜色“完成”时,我们打破并开始到下一个排列。请注意,每种颜色我们有 4 张卡片,但完成每种颜色所需的卡片数量是 {2,3,4}(红色、绿色、蓝色)。 2 张红色卡片足以完成红色,而我们有 4 张可用,因此红色比蓝色更有可能完成,蓝色需要全部 4 张卡片都被选中。

我想让这个 for 循环并行,但我的主要问题是如何处理“卡片”排列?你这里有大约 5 亿个排列(12!),如果我有 4 个线程,我如何将它分成 4 个不同的部分并让每个线程通过它们中的每一个?

如果我不知道机器的核心数,而我希望程序自动选择正确的并发线程数怎么办?肯定有办法使用 Intel 或 Microsoft 工具来做到这一点?

这是我的卡片结构以防万一:

struct Card
{
public:
int Colour;
int Symbol;
}

最佳答案

N = cardsNumber , M = required[0] * required[1] * ... * required[maxColor] .然后,实际上,您的问题可以在 O(N * M) 时间内轻松解决。在您的情况下,即 12 * 2 * 3 * 4 = 288操作。 :)

执行此操作的一种可能方法是使用递归关系。考虑一个函数 logColours f(n, required) .让n是当前已经考虑过的牌的数量; required是您示例中的一个 vector 。函数返回 vector 中的答案 logColours .您对f(12, {2,3,4})感兴趣.函数内部的简短循环计算 f可以这样写:

std::vector<int> f(int n, std::vector<int> require) {
if (cache[n].count(require)) {
// we have already calculated function with same arguments, do not recalculate it again
return cache[n][require];
}

std::vector<int> logColours(maxColor, 0); // maxColor = 3 in your example

for (int putColor=0; putColor<maxColor; ++putColor) {
if (/* there is still at least one card with color 'putColor'*/) {
// put a card of color 'putColor' on place 'n'
if (require[putColor] == 1) {
// means we've reached needed amount of cards of color 'putColor'
++logColours[putColor];
} else {
--require[putColor];
std::vector<int> logColoursRec = f(n+1, require);
++require[putColor];
// merge child array into your own.
for (int i=0; i<maxColor; ++i)
logColours[i] += logColoursRec[i];
}
}
}

// store logColours in a cache corresponding to this function arguments
cache[n][required] = std::move(logColours);
return cache[n][required];
}

缓存可以实现为 std::unordered_map<int, std::unordered_map<std::vector<int>, std::vector<int>>> .

一旦您理解了主要思想,您将能够以更高效的代码来实现它。

关于C++ Intel TBB 和 Microsoft PPL,如何在并行循环中使用 next_permutation?,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/16250302/

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