activeviam / StructuredConcurrencyDemo

A sample project that show the new concept of structured concurrency

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Structured Game Of Life Demo

This is a demo project showing the concept of Structured Concurrency and its implementation in Project Loom using a Game Of Life simulation as an example.

Concepts

Structured Concurrency

The main idea of Structured Concurrency is that using the go operator (or the new Thread(...).start(), executor.submit() constructs, etc.) makes the code more complex. From the code, it becomes impossible to understand how many parallel tasks are being executed at the same time. This statement is similar to the goto operator. Just like goto, the go statement can create a new branch of control flow anywhere in the program, which is extremely difficult to trace syntactically. It also makes debugging and error handling much more difficult. Using callback chains breaks logically sequential code into unrelated parts.

In order to cope with these problems, it is proposed to switch to another design pattern, linking the moments of creation and completion of parallel subtasks to the block structure of the code. For this, the concept of scope is introduced. The code in this paradigm looks something like this:

class Foo {

	void bar() {
		try (var scope = new StructuredTaskScope<?>()) {
			Future<?> f1 = scope.fork(subtask1);
			Future<?> f2 = scope.fork(subtask2);
			// ...
			scope.join();
			// Error handling, result processing
		}
	}
}
// Here all the subtasks are guaranteed to be terminated

This approach is somewhat similar to the parallelism in OpenMP, but much more flexible. Abandoning the goto statement in favor of if, for/while statements and function calls, proposed by E. Dijkstra in the article "Go to statement considered harmful" allowed the emergence of high-level programming languages with a block code structure. The absence of a goto operator ensures that if you call a function, eventually you shall exit it and return to the point where you started. Likewise, you can't just jump out of an if block or out of a loop (actually, loops have break and continue which were not in Dijkstra's article, but they are nowhere near as destructive as goto). It was this "black box" format with clear entry and exit points that allowed such constructs as exceptions, try-with-resources, RAII, and many others to appear. At the same time, at the level of machine code, the goto operator has not disappeared anywhere: it’s just that now it is used not haphazardly, but only according to several pre-negotiated patterns.

Structured Concurrency suggests doing the same with the go operator. Scopes allow the programmer to think of a piece of code as a black box, which we first enter and then exit, while we know for sure that there are no tasks in the background. Everything that we launched in the block must be completed in it. Every error raised in a subtask will be delivered to the caller code. Every resource opened before the scope may be closed after the scope since no background tasks use it.

Virtual Threads

Another important concept introduced in Project Loom is virtual threads. For the user, a virtual thread is practically no different from a normal, "physical" thread. The main difference lies in implementation. Regular Java threads most often correspond to operating system threads. Their management is done by the OS, and this imposes significant restrictions. First, the process of creating a system thread takes a lot of time. Secondly, using more than a couple of hundred threads leads to performance degradation, since a significant part of the time is spent switching between threads. Switching between system threads occurs when the timer expires.

Unlike physical threads, virtual threads are managed by the Java Virtual Machine. From the JVM point of view, a virtual thread is a special kind of Runnable executing on a special ForkJoinPool. A virtual thread has its own call stack, ThreadLocal and ExtentLocal variables. When the system starts executing the virtual thread code, it is associated with the physical carrier thread and executed on it until it is preempted by another virtual thread. In this case, there is no timer switching: the points where a switch can occur are blocking operations. Typically, if a virtual thread starts a blocking operation, it will be unmounted from the carrier thread and queued.

Virtual threads are designed with the expectation that there will be a lot of them. Creating a new virtual thread is very cheap, and their number does not affect system performance (because there is no forced timer switching). This allows you to create a separate virtual thread for each task. Moreover, using virtual threads we can return to the “blocking” code design: code pieces like future.get() or thread.join() will cause the current virtual thread to be unmounted until the result is ready.

Structured Concurrency combined with Virtual Threads allows you to write easy-to-understand multi-threaded code.

Extent Locals

Extent locals is a new concept introduced in Java 19 as an alternative to thread locals. Virtual threads support working with ThreadLocal variables, but their usage can be associated with a significant memory consumption (a hash table is created in each thread containing all thread-local variables associated with this thread).

A common reason to use ThreadLocal variables is to pass some context between tasks. To do this, the following wrapper code is often used:

class Task {

	private static final ThreadLocal<Task> CURRENT_TASK = new ThreadLocal<>();
	private Task currentTask;

	public void compute() {
		pushExecutionContext();
		try {
			computeSafely();
		} finally {
			popExecutionContext();
		}
	}

	void pushExecutionContext() {
		this.previousTask = CURRENT_TASK.get();
		CURRENT_TASK.set(this);
	}

	void popExecutionContext() {
		CURRENT_TASK.set(this.previousTask);
		this.previousTask = null;
	}
}

This approach is justified when working with a pool of threads. Nevertheless, this approach can cause various errors and vulnerabilities, ranging from incorrect values of variables (if some part of the context was forgotten to be set) and up to leaks of secret variables (for example, if as a result of the work-stealing algorithm one task gains access to the data of another task).

If we use virtual threads, then such a context has another important property: it is set only once during the lifetime of the thread (because one thread executes only one task). In some sense, a context variable must be declared final.

ExtentLocal is a concept designed to solve this problem. Like ThreadLocal, an extent-local variable is most often declared as a static final field of some class. The value that code can read from the extent-local variable depends on which thread the code is executing on. The key difference from a thread-local variable is how an extent-local variable is bound to a value.

In order to assign the value of extent-local to a variable, you must declare a scope. Within this scope, the extent-local variable has the constant value specified when the scope was created. This is done as follows:

class Foo {

	final static ExtentLocal<T> V = ExtentLocal.newInstance();

	void bar() {
		// caller code
		ExtentLocal
				.where(V, someValue)
				.run(() -> {
					// ... some code here ...
					var foo = V.get();
					// ... some more code ...
				});
	}
}

This code structure makes it much easier to understand what value the code can read. The immutability of an extent-local variable allows you to get the required value much faster than in the case of thread-local variables ( scopes create a tree structure, and each node of such a tree stores a cache of extent-local variables, which cannot be invalidated, since the variables are immutable).

The problem with leakage of secret values is solved as follows. Consider the following code snippet (example from https://openjdk.org/jeps/8263012, section "Rebinding of extent-local variables" ):

class Foo {

	void foo() {
		String password = PASSWORD.get();
		doSomethingWithPassword(password);

		Logger.log(() -> {
			return "Password: " + PASSWORD.get();
			// Security leak:     ^^^^^^^^^^^^^^
		});
	}
}

Inside the foo() method, we need access to PASSWORD. But in the logger code, the password must be hidden. To do this, you can change the logger as follows:

class Logger {

	void log(Supplier<String> supplier) {
		if (loggingEnabled) {
			var message = ExtentLocal
					.where(PASSWORD, null)
					.call(supplier::get);
			doLog(message);
		}
	}
}

In the log() method itself, the code will be able to read the password, but the supplier code will be executed in a new scope, and in it the value of the PASSWORD variable will be hidden behind the new binding.

Extent-locals and structured concurrency scopes are compatible with each other. Using extent-locals is the recommended way to pass context variables to the parallel subtasks (see GameOfLifeContext class).

Implementation

Task

The main building block of this project is the ATask abstract class. This class encapsulates functionality that allows multiple blocks of code to refer to the same subtask. The code for this class looks like this:

abstract class ATask<V> extends Callable<V> {

	private final AtomicBoolean startedFlag = new AtomicBoolean(false);
	private final CountDownLatch done = new CountDownLatch(1);

	public V call() throws Exception {
		if (tryStart()) {
			return unsafeCall();
		} else {
			return waitForResult();
		}
	}


	boolean tryStart() {
		return startedFlag.compareAndSet(false, true);
	}

	V unsafeCall() throws Exception {
		try {
			this.result = compute();
			return this.result;
		} catch (Exception ex) {
			this.ex = ex;
			throw ex;
		} finally {
			try {
				dispose();
			} finally {
				done.countDown();
			}
		}
	}

	V waitForResult() throws Exception {
		done.await();
		if (this.ex != null) {
			throw new RuntimeException(this.ex);
		} else {
			return this.result;
		}
	}

	protected abstract V compute() throws Exception;

	protected abstract void dispose();
}

You can use this class like this:

class Foo {

	T bar() {
		try (var scope = new StructuredTaskScope.ShutdownOnFailure()) {
			Future<T1> f1 = scope.fork(task1);
			Future<T2> f2 = scope.fork(task2);

			// ...

			scope.join().throwIfFailed();

			return merge(f1.resultNow(), f2.resultNow());
		}
	}
}

If any of the tasks is already running, the new virtual thread will simply block and wait for the corresponding task to complete. At the same time, its termination with an error will cause the error to be thrown in all calling threads.

Watcher pattern

In the following example, we add a simple watcher that traces the computation progress:

class Foo {

	T runWithWatcher(ATask<T> mainTask) {
		try (var scope = new StructuredTaskScope.ShutdownOnSuccess<T>()) {
			scope.fork(mainTask);
			scope.fork(() -> {
				try {
					while (true) {
						traceProgress();
						Thread.sleep(1000);
					}
				} catch (InterruptedException e) {
					traceSummary();
					throw e;
				}
			});

			return scope.join().result();
		}
	}
}

Compile & Run

In order to compile the project, you need to download OpenJDK Early-Access build with Project Loom support: https://jdk.java.net/loom/. The code is tested on the Build 19-loom+6-625 (2022/4/29). Since the API is unstable, further updates my break this code.

This build includes the following bug (JDK-8286859). It seems that this bug doesn't affect the code, but I cannot guarantee it.

To run the project, use the following command:

java \
  -cp target/classes \
  --enable-preview \
  --add-modules jdk.incubator.concurrent \
  com.activeviam.experiments.gameoflife.Main 

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A sample project that show the new concept of structured concurrency


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