.NET: Multi-threading with Tasks

Working with the Task class in .NET is practically identical to working with the Thread class (see related article) with one important difference — the .NET asynchronous functions support the CancellationToken for cancelling a thread which means it is mildly easier to work with tasks.

Advantages of Tasks Over Threads

1. Tasks can return a result whereas thread functions/methods are are always void return type
2. Tasks implement a thread pool and are load balanced
3. Tasks automatically implement cancellation tokens (threads can implement cancellation tokens, too)
4. Tasks are threads with some level of abstraction

.NET Tasks use threads but wraps them in classes to make them a higher level concept. Tasks seem similar to Intel Threading Building Blocks.

Example of a Task Returning a Value

using System;
using System.Threading.Tasks;

namespace ConsoleApp1
{
	class Program
	{
		static async Task Main(string[] args)
		{
			string s = await Task.Run(async () => // async not necessary in this example
			{
				return (args.Length > 0 ? args[0] : "no arguments"); // VALUE RETURNED ON THIS LINE
			});
			Console.WriteLine(s);
		}
	}
}

Example of Waiting for Tasks to Finish

Tasks are added to a List and then a special method, Task.WhenAll, holds execution until all tasks are finished. This is easily manipulated to work with classes containing a Task member through either a Select statement or simply looping through all the Tasks checking Task.IsCompleted.

using System.Collections.Generic;
using System.Threading.Tasks;

namespace ConsoleApp1
{
	class Program
	{
		static async Task Main(string[] args)
		{
			var tasks = new List<Task>();
			for (int i = 0; i < 20; i++)
			{
				tasks.Add(Task.Run(() =>
				{
					for (int x = 0; x < 1000000000; x++) ;
				}));
			}
			await Task.WhenAll(tasks); // wait for the tasks to finish
		}
	}
}

Find π on Each Logical Processor Using Tasks

This version of finding pi does so with floating point variables. See this article for an example of using .NET threading to solve pi with integers. FindPi_2 is the popular Bailey–Borwein–Plouffe formula.

using System;
using System.Collections.Generic;
using System.Linq;
using System.Threading;
using System.Threading.Tasks;

namespace ConsoleApp1
{
	class JobTask
	{
		public Task task { get; }
		public int id { get; }
		public double pi { get; set; }
		public ulong iterations { get; set; }
		public CancellationTokenSource CancelToken { get; }
		public JobTask(int id)
		{
			var spaces = Environment.ProcessorCount.ToString().Length;
			this.id = id;
			CancelToken = new CancellationTokenSource();
			iterations = (ulong)new Random().Next() * 10;
			Console.WriteLine("Starting Job: {0, -" + spaces + "} Iterations: {1}", id, iterations);
			task = Task.Run(async () => // async not necessary in this example
			{
				if((id & 1) == 0)
					pi = FindPi_2(iterations, CancelToken);
				else
					pi = FindPi_1(iterations, CancelToken);
				Console.WriteLine("Job: {0, -" + spaces + "} ended with pi={1}", id, pi.ToString("0.00000000000000")); // apply some fancy formatting
			}, CancelToken.Token);
		}

		static double FindPi_1(ulong count, CancellationTokenSource cancel)
		{
			//π = 3.14159265358979323846264338327950288419...
			//π = (4/1) - (4/3) + (4/5) - (4/7) + (4/9) - (4/11) + (4/13) - (4/15) + ...
			//π = 4 * (1 - 1/3 + 1/5 - 1/7 + 1/9 - 1/11 + 1/13 - 1/15 + ...)

			double x = 1.0;
			for (ulong i = 2; !cancel.IsCancellationRequested & i < count; i++)
				x += ((i & 1) == 0 ? -1.0 : 1.0) / ((i << 1) - 1);
			return 4.0 * x;
		}

		static ulong Power(ulong x, ulong y)
		{
			ulong m = 1;
			for (ulong i = 0; i < y; i++)
				m *= x;
			return m;
		}
		static double FindPi_2(ulong count, CancellationTokenSource cancel) // this is the fast, efficient and accurate Bailey–Borwein–Plouffe formula
		{
			//π = 3.14159265358979323846264338327950288419...

			double x = 0.0;
			for (ulong k = 0, p = Power(16, k); (p > 0) & (k < count); k++, p = Power(16, k))
				x += (4.0 / (8.0 * k + 1) - 2.0 / (8.0 * k + 4) - 1.0 / (8.0 * k + 5) - 1.0 / (8.0 * k + 6)) / p;
			return x;
		}
	}
	class Program
	{
		static void Main(string[] args)
		{
			var jobTasks = new List<JobTask>();
			Console.WriteLine("pi={0}", 3.1415926535897932384626433832795028841971693993751M.ToString("0.00000000000000"));
			Console.WriteLine("Logical Processors: {0}", Environment.ProcessorCount);
			Console.WriteLine("ENTER A JOB NUMBER TO TERMINATE IT AT ANYTIME");

			var spaces = Environment.ProcessorCount.ToString().Length;

			int[] jobsIds = new int[Environment.ProcessorCount];
			for (int i = 0; i < Environment.ProcessorCount; i++)
				jobsIds[i] = i;

			foreach (var jobId in jobsIds)
				jobTasks.Add(new JobTask(jobId));

			Task.Run(() => // create a task to terminate the app when all pi tasks are done; this is because Console.ReadLine() is blocking
			{
				while (jobTasks.Where(j => j.task.IsCompleted == false).Count() > 0)
					Thread.Sleep(250);
				Environment.Exit(0);
			});

			while (jobTasks.Where(j => j.task.IsCompleted == false).Count() > 0) // look for a request to cancel a job from the user
			{
				var id = Console.ReadLine(); // this is blocking
				JobTask jt = jobTasks.Where(j => j.id.ToString() == id).FirstOrDefault();
				if (jt != null)
					jt.CancelToken.Cancel();
			}
		}
	}
}

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