Virtual Thread: Maximizing Thread-Level Parallelism beyond GPU Scheduling Limit IEEE Conference Publication
Pooling is not required with virtual threads because they are cheap to create and dispose of, and therefore pooling is unnecessary. Instead, you can think of the JVM as managing the thread pool for you. Many programs do use executors, however, and so Java 19 includes a new preview method in executors to make refactoring to virtual threads easy. Initially, carrier threads for virtual threads are threads in a ForkJoinPool that operates in FIFO mode.
Also, we have to adopt a new programming style away from typical loops and conditional statements. The new lambda-style syntax makes it hard to understand the existing code and write programs because we must now break our program into multiple smaller units that can be run independently and asynchronously. But this pattern limits the throughput of the server because the number of concurrent requests becomes directly proportional to the server’s hardware performance. So, the number of available threads has to be limited even in multi-core processors. Platform threads have always been easy to model, program and debug because they use the platform’s unit of concurrency to represent the application’s unit of concurrency. In Java, a classic thread is an instance of java.lang.Thread class.
- To take advantage of virtual threads, it is not necessary to rewrite your program.
- So Spring is in pretty good shape already owing to its large community and extensive feedback from existing concurrent applications.
- With virtual threads, the Java runtime can easily support hundreds of thousands of active threads.
- However, many server applications will choose virtual threads to achieve greater scalability.
- Project Loom experimentally proved that the benefit of virtual lies not in its fast context switches, but in the throughput afforded by having so many threads executed at once.
- Again, this is not the end of the world, even when you don’t have shared mutable state.
With project loom java, the application instantiates virtual threads and thus expresses the need for concurrency. But it is the JVM that obtains and releases the resources from the operating system. Java developers may recall that in the Java 1.0 days, some JVMs implemented threads using user-mode, or “green”, threads.
You don’t have to learn anything new to use virtual threads
To run code in a virtual thread, the Java runtime arranges for it to run by mounting it on some platform thread, called a carrier thread. Mounting a virtual thread means temporarily copying the needed stack frames from the heap to the stack of the carrier thread, and borrowing the carriers stack while it is mounted. Our team has been experimenting with Virtual Threads since they were called Fibers.
It’s just that we dropped major releases altogether and then gave the feature releases new version numbers, and that confused many people . As a member of the Cassandra community I’m super excited to get my hands on virtual threads come the next LTS (and Cassandra’s upgrade cycle), as it will permit us to solve many outstanding problems much more cheaply. Golang had virtual threads much earlier, but the Structured Concurrency API, and the Extent Local Variable API is nicer than what Golang offers. Writing synchronous code that blocks on I/O is now ok. (You no longer need to write asynchronous code just to avoid blocking a thread e.g. using CompletableFuture). Virtual threads don’t require you to learn a whole new library.
The size of this pool defaults to the number of available processors. In the future, there may be more options to create custom schedulers. A more serious problem with async/await is the “function color” problem, where methods are divided into two kinds — one designed for threads and another designed for async methods — and the two do not interoperate perfectly. https://globalcloudteam.com/ This is a cumbersome programming model, often with significant duplication, and would require the new construct to be introduced into every layer of libraries, frameworks, and tooling in order to get a seamless result. Why would we implement yet another unit of concurrency — one that is only syntax-deep — which does not align with the threads we already have?
The ExecutorService would create 200 platform threads to be shared by all 10,000 tasks, so many of the tasks would run sequentially rather than concurrently and the program would take a long time to complete. For this program, a pool with 200 platform threads can only achieve a throughput of 200 tasks-per-second, whereas virtual threads achieve a throughput of about 10,000 tasks-per-second . It usually requires little awareness of concurrency because most requests are independent of each other.
Virtual threads help to improve the throughput of typical server applications precisely because such applications consist of a great number of concurrent tasks that spend much of their time waiting. Today, every instance of java.lang.Thread in the JDK is a platform thread. A platform thread runs Java code on an underlying OS thread and captures the OS thread for the code’s entire lifetime.
Capping the Number of Concurrent threads that can Access a shared Resource
ExecutorService now extends AutoCloseable, thus allowing this API to be used with the try-with-resource construct as shown in the examples above. New overloads of Thread.join and Thread.sleep accept wait and sleep times as instances of java.time.Duration. After that, the program no longer needs 10 seconds but only just over one second. It can hardly be faster because every task waits one second. This code is not only easier to write and read but also – like any sequential code – to debug by conventional means. If you don’t want to put specify the opening the java.lang module in your pom.xml file, you can also specify it as an argument when you start the dev mode.
They allow you to combine your GC pause and scheduler pause into one. Again, this is not the end of the world, even when you don’t have shared mutable state. If anything, it makes it easier to build a runtime on top of. You might want to preempt after scheduling quanta expirations, page faults, etc.
Pitfalls you encounter with virtual threads
Then, it does some simple math with random numbers and tracks how long the execution takes. Nearly all blocking points in the JDK were made aware of virtual threads, and will unmount a virtual thread rather than blocking it. Virtual threads, and their related APIs, are a preview feature.
So if you have a failure you get a single stack trace that includes everything. In JS the debuggers sometimes glue stack traces together which works for basic stuff but incurs a major runtime overhead and doesn’t work for production failures. Feature releases existed in Java 8, too, people just forget because they didn’t get their own version number back when major releases existed.
In addition, Java 19 introduces the Executors.newThreadPerTaskExecutor method, which can take a ThreadFactory that builds virtual threads. Such a factory can be obtained with Thread.ofVirtual().factory(). There are other ways of using Thread to spawn virtual threads, like Thread.ofVirtual().start. Virtual threads are fully compatible with the existing `Thread` API, so existing applications and libraries can support them with minimal change. This article dives into the throughput and quality of the async code review process, which are very important dimensions to optimize for in product development teams.
How to Create Virtual Threads?
To demo it, we have a very simple task that waits for 1 second before printing a message in the console. We are creating this task to keep the example simple so we can focus on the concept. The terminally deprecated suspend(), resume(), and stop() methods always throw an exception.
I find that an easier model to think about, and I opt into multithreading when I need it. It seems like most of the time you don’t want or need the full flexibility of async/await, but I don’t think the guaranteed structure is worth the benefits to me if the language doesn’t support it natively. Too much boilerplate, and static analysis is usually pretty good about catching mistakes, in python at least. Two separate threads run in parallel, but one thread cannot do two subtasks in parallel without submitting parallel jobs to an executor or a StructuredTaskScope subtask manager. It’s basically forcing the developer to do all the hard work and boilerplate that async/await saves you. JDK methods can be annotated as “internal” and optionally hidden in stack-traces, but in this case it’s unnecessary.
You can refer to this mail to get more information on how we envision our future with virtual threads. Platform threadUp until Java 19, every instance of the Thread class was a platform thread, that is, a wrapper around an OS thread. Creating a platform threads creates an OS thread, blocking a platform thread blocks an OS thread. The other primary way to start a virtual thread is with an executor. Executors are common in dealing with threads, offering a standard way to coordinate many tasks and thread pooling.
I think the reasons green threads can work in languages is that the runtime understands the language semantics, and can take advantage of them. The OS doesn’t understand the language and its concurrency semantics, and only has a blob of machine code to work with. You’re supposed to not do busy waiting on virtual threads (and better not do it at all, use wait-notify or a barrier or whatever). For CPU-bound tasks you’d want an OS thread per CPU core anyway.
Using virtual threads vs. platform threads
If a virtual thread performs a blocking operation such as I/O or BlockingQueue.take() while it is pinned, then its carrier and the underlying OS thread are blocked for the duration of the operation. Frequent pinning for long durations can harm the scalability of an application by capturing carriers. A clear presentation of the state of a running program is also essential for troubleshooting, maintenance, and optimization, and the JDK has long offered mechanisms to debug, profile, and monitor threads. Such tools should do the same for virtual threads — perhaps with some accommodation to their large quantity — since they are, after all, instances of java.lang.Thread.
API and platform changes
One of the most far-reaching Java 19 updates is the introduction of virtual threads. Virtual threads are part of Project Loom, and are available in Java 19 as a preview. For CPU-bound workloads, we already have tools to get to optimal CPU utilization, such as the fork-join framework and parallel streams.
Difference between Platform Threads and Virtual Threads
You can only do them concurrently, since only when a virtual thread blocks can you move on and schedule another thread in your runtime. For example how do you implement “debounce” using virtual threads? I don’t see how you can do that in the virtual threading model, although I haven’t used it and only read this article. You would have to spin up threads and wait for them to finish, which IMO is much more complicated and hard to read. Under the hood, the virtual thread feature does more or less the same as reactive.