std::async 的 windows 实现似乎有一个 bug。在重负载下（大约每秒启动 1000 个异步线程），异步任务永远不会被调度，并且等待返回的 future 会导致死锁。请参阅这段代码（使用延迟启动策略而不是异步进行修改）：
BundlingChunk(size_t numberOfInputs, Bundler* parent, ChunkIdType chunkId)
: m_numberOfInputs(numberOfInputs), m_parent(parent), m_chunkId(chunkId)
{
const BundlerChunkDescription& chunk = m_parent->m_chunks[m_chunkId];
const ChunkInfo& original = chunk.m_original;
auto& deserializers = m_parent->m_deserializers;
// Fetch all chunks in parallel.
std::vector<std::map<ChunkIdType, std::shared_future<ChunkPtr>>> chunks;
chunks.resize(chunk.m_secondaryChunks.size());
static std::atomic<unsigned long long int> chunksInProgress = 0;
for (size_t i = 0; i < chunk.m_secondaryChunks.size(); ++i)
{
for (const auto& c : chunk.m_secondaryChunks[i])
{
const auto chunkCreationLambda = ([this, c, i] {
chunksInProgress++;
ChunkPtr chunk = m_parent->m_weakChunkTable[i][c].lock();
if (chunk) {
chunksInProgress--;
return chunk;
}
chunksInProgress--;
return m_parent->m_deserializers[i]->GetChunk(c);
});
std::future<ChunkPtr> chunkCreateFuture = std::async(std::launch::deferred, chunkCreationLambda);
chunks[i].emplace(c, chunkCreateFuture.share());
}
}
std::vector<SequenceInfo> sequences;
sequences.reserve(original.m_numberOfSequences);
// Creating chunk mapping.
m_parent->m_primaryDeserializer->SequenceInfosForChunk(original.m_id, sequences);
ChunkPtr drivingChunk = chunks.front().find(original.m_id)->second.get();
m_sequenceToSequence.resize(deserializers.size() * sequences.size());
m_innerChunks.resize(deserializers.size() * sequences.size());
for (size_t sequenceIndex = 0; sequenceIndex < sequences.size(); ++sequenceIndex)
{
if (chunk.m_invalid.find(sequenceIndex) != chunk.m_invalid.end())
{
continue;
}
size_t currentIndex = sequenceIndex * deserializers.size();
m_sequenceToSequence[currentIndex] = sequences[sequenceIndex].m_indexInChunk;
m_innerChunks[currentIndex] = drivingChunk;
}
// Creating sequence mapping and requiring underlying chunks.
SequenceInfo s;
for (size_t deserializerIndex = 1; deserializerIndex < deserializers.size(); ++deserializerIndex)
{
auto& chunkTable = m_parent->m_weakChunkTable[deserializerIndex];
for (size_t sequenceIndex = 0; sequenceIndex < sequences.size(); ++sequenceIndex)
{
if (chunk.m_invalid.find(sequenceIndex) != chunk.m_invalid.end())
{
continue;
}
size_t currentIndex = sequenceIndex * deserializers.size() + deserializerIndex;
bool exists = deserializers[deserializerIndex]->GetSequenceInfo(sequences[sequenceIndex], s);
if (!exists)
{
if(m_parent->m_verbosity >= (int)TraceLevel::Warning)
fprintf(stderr, "Warning: sequence '%s' could not be found in the deserializer responsible for stream '%ls'\n",
m_parent->m_corpus->IdToKey(sequences[sequenceIndex].m_key.m_sequence).c_str(),
deserializers[deserializerIndex]->StreamInfos().front().m_name.c_str());
m_sequenceToSequence[currentIndex] = SIZE_MAX;
continue;
}
m_sequenceToSequence[currentIndex] = s.m_indexInChunk;
ChunkPtr secondaryChunk = chunkTable[s.m_chunkId].lock();
if (!secondaryChunk)
{
secondaryChunk = chunks[deserializerIndex].find(s.m_chunkId)->second.get();
chunkTable[s.m_chunkId] = secondaryChunk;
}
m_innerChunks[currentIndex] = secondaryChunk;
}
}
}
我的上述版本经过修改，以便异步任务以延迟方式而不是异步方式启动，这解决了问题。从 VS2017 可再发行版 14.12.25810 开始，还有其他人见过类似的东西吗？重现这个问题就像训练 CNTK 模型一样简单，该模型在具有 GPU 和 SSD 的机器上使用文本和图像读取器，从而使 CPU 反序列化成为瓶颈。训练大约30分钟后，通常会出现僵局。有人在 Linux 上见过类似的问题吗？如果是这样，则可能是代码中的错误，尽管我对此表示怀疑，因为死锁后调试计数器
chunksInProgress新的一天，更好的答案（好多更好）。 继续阅读。
我花了一些时间研究
std::async因此，如果您的代码依赖于
std::async无论如何，我想更多地了解现代 C++，所以我尝试了自己的
std::asyncAsyncTask：
std::async#include <future>
#include <thread>
template <class Func, class... Args>
std::future <std::result_of_t <std::decay_t <Func> (std::decay_t <Args>...)>>
AsyncTask (Func&& f, Args&&... args)
{
using decay_func = std::decay_t <Func>;
using return_type = std::result_of_t <decay_func (std::decay_t <Args>...)>;
std::packaged_task <return_type (decay_func f, std::decay_t <Args>... args)>
task ([] (decay_func f, std::decay_t <Args>... args)
{
return f (args...);
});
auto task_future = task.get_future ();
std::thread t (std::move (task), f, std::forward <Args> (args)...);
t.detach ();
return task_future;
};
测试程序
#include <iostream>
#include <string>
int add_two_integers (int a, int b)
{
return a + b;
}
std::string append_to_string (const std::string& s)
{
return s + " addendum";
}
int main ()
{
auto /* i.e. std::future <int> */ f1 = AsyncTask (add_two_integers , 1, 2);
auto /* i.e. int */ i = f1.get ();
std::cout << "add_two_integers : " << i << std::endl;
auto /* i.e. std::future <std::string> */ f2 = AsyncTask (append_to_string , "Hello world");
auto /* i.e. std::string */ s = f2.get (); std::cout << "append_to_string : " << s << std::endl;
return 0;
}
输出
add_two_integers : 3
append_to_string : Hello world addendum
我从写这篇文章中学到了很多东西，而且很有趣。 我对这些东西还很陌生，所以欢迎所有评论。如果我有任何错误，我会很乐意更新这篇文章。
受到Paul Sander的回答的启发，我尝试稍微简化他的代码：
#include <functional>
#include <future>
#include <thread>
#include <type_traits>
template <class Func, class... Args>
[[nodiscard]] std::future<std::invoke_result_t<std::decay_t<Func>, std::decay_t<Args>...>>
RunInThread(Func&& func, Args&&... args){
using return_type = std::invoke_result_t<std::decay_t<Func>, std::decay_t<Args>...>;
auto bound_func = std::bind(std::forward<Func>(func), std::forward<Args>(args)...);
std::packaged_task<return_type(void)> task(bound_func);
auto task_future = task.get_future();
std::thread(std::move(task)).detach();
return task_future;
}
不幸的是，这和 Paul 的实现都不符合标准。 std::async 返回的 future 不是普通的 future，而是一种特殊的 future：在任务完成之前它无法被销毁，即它在其析构函数中在任务线程上调用
join()除了
std::futurestd::async