async/await is about asynchrony, whereas Parallel.ForEach is about parallelism. They’re related concepts, but not the same. Parallel.ForEach is used when you want to execute the same operation on all the items in a collection, in parallel, blocking the current thread until all operations have completed. async/await is used when the current operation can’t make any … Read more
The answer is that it is the upper limit for the entire parallel operation, irrespective of the number of cores. So even if you don’t use the CPU because you are waiting on IO, or a lock, no extra tasks will run in parallel, only the maximum that you specifiy. To find this out, I … Read more
Thanks for your feedback. I did look up parallel after I posted this question. Finally after a few tries, I got it running. I have added the code below in case it is useful to others library(foreach) library(doParallel) #setup parallel backend to use many processors cores=detectCores() cl <- makeCluster(cores[1]-1) #not to overload your computer registerDoParallel(cl) … Read more
Does both my Parallel.ForEach loops use the same thread pool under the hood. Yes How does Parallel.ForEach limits the threads with MaxDegreeOfParallelism. ParallelOptions.MaxDegreeOfParallelism Gets or sets the maximum number of concurrent tasks enabled by this ParallelOptions instance. By default, methods on the Parallel class attempt to use all available processors, are non-cancelable, and target the … Read more
Suppose you have a task to perform. Let’s say you’re a math teacher and you have twenty papers to grade. It takes you two minutes to grade a paper, so it’s going to take you about forty minutes. Now let’s suppose that you decide to hire some assistants to help you grade papers. It takes … Read more
In this case, the second method will asynchronously wait for the tasks to complete instead of blocking. However, there is a disadvantage to use Task.Run in a loop- With Parallel.ForEach, there is a Partitioner which gets created to avoid making more tasks than necessary. Task.Run will always make a single task per item (since you’re … Read more
Foreach loop: Iterations takes place sequentially, one by one foreach loop is run from a single Thread. foreach loop is defined in every framework of .NET Execution of slow processes can be slower, as they’re run serially Process 2 can’t start until 1 is done. Process 3 can’t start until 2 & 1 are done… … Read more
You can specify a MaxDegreeOfParallelism in a ParallelOptions parameter: Parallel.ForEach( listOfWebpages, new ParallelOptions { MaxDegreeOfParallelism = 4 }, webpage => { Download(webpage); } ); MSDN: Parallel.ForEach MSDN: ParallelOptions.MaxDegreeOfParallelism
async doesn’t work well with ForEach. In particular, your async lambda is being converted to an async void method. There are a number of reasons to avoid async void (as I describe in an MSDN article); one of them is that you can’t easily detect when the async lambda has completed. ASP.NET will see your … Read more
If you just want simple parallelism, you can do this: var bag = new ConcurrentBag<object>(); var tasks = myCollection.Select(async item => { // some pre stuff var response = await GetData(item); bag.Add(response); // some post stuff }); await Task.WhenAll(tasks); var count = bag.Count; If you need something more complex, check out Stephen Toub’s ForEachAsync post.