Mastering Multithreading in Unreal Engine 5 C++: A Complete Guide

Multithreading is a powerful technique in game development that allows multiple tasks to run concurrently, leveraging the full potential of modern multi-core processors. In a game, numerous processes such as rendering, physics calculations, AI, and input handling need to be executed simultaneously. Properly implemented multithreading can significantly improve the performance and responsiveness of your game by ensuring these processes run smoothly without blocking each other.

Unreal Engine 5 provides robust support for multithreading, enabling developers to create high-performance, scalable games. The engine uses several threading models and provides various tools and classes to manage threads and tasks efficiently. Here’s an overview of Unreal Engine’s multithreading capabilities:

Game Thread: The main thread where most gameplay logic runs. It processes input, updates game objects, and handles most of the game’s logic.
Render Thread: A separate thread responsible for rendering graphics. It works in tandem with the game thread to ensure smooth and efficient rendering.
Task Graph System: A powerful system for managing asynchronous tasks and parallel execution. It helps in efficiently scheduling and running tasks across multiple threads.

The combination of these threads and systems allows Unreal Engine to handle complex and demanding games with high performance and scalability.

Improved Performance: By distributing tasks across multiple threads, you can take full advantage of multi-core processors, resulting in faster and more efficient execution of tasks.
Smooth Gameplay: Multithreading helps maintain a smooth gameplay experience by ensuring that resource-intensive tasks like rendering and physics calculations do not block the game thread.
Scalability: Properly implemented multithreading allows your game to scale efficiently with hardware advancements, ensuring better performance on modern systems.

Multithreading is a critical aspect of modern game development, and Unreal Engine 5 offers powerful tools and systems to implement it effectively. Understanding the importance of multithreading and the capabilities provided by Unreal Engine will help you create high-performance and scalable games. In the next sections, we will dive deeper into the threading model of Unreal Engine 5 and explore how to create and manage threads, use the Task Graph System, and more.

Unreal Engine 5 employs a sophisticated threading model to manage the various tasks that need to run simultaneously in a game. Understanding this model is crucial for effectively utilizing multithreading in your projects.

The Game Thread is the primary thread in Unreal Engine where most of the gameplay logic runs. It handles:

Input processing
Actor updates
Game state management
Logic execution

The Game Thread operates on a variable time step, meaning the time elapsed between frames (DeltaTime) can vary. This ensures consistent gameplay updates by adjusting calculations based on the actual time elapsed. While it is responsible for most of the core game logic, offloading certain tasks to other threads can improve performance and responsiveness.

Certain subsystems, such as physics simulations, often operate on a fixed time step. This approach ensures stable and deterministic physics behavior by updating at consistent intervals, independent of the variable frame times of the Game Thread.

The Render Thread is dedicated to rendering graphics. It works closely with the Game Thread to process rendering commands and draw the game world. Key responsibilities include:

Preparing rendering data
Communicating with the GPU
Executing draw calls

By separating rendering from the game logic, Unreal Engine can achieve smoother frame rates and better performance.

The Task Graph System is a powerful system for managing asynchronous tasks and parallel execution in Unreal Engine. It allows developers to schedule and execute tasks concurrently, making full use of multi-core processors.

FGraphEventRef: Represents a reference to a graph event, used to track the completion of tasks.
FFunctionGraphTask: Allows you to define and schedule tasks.

				
					FGraphEventRef MyTask = FFunctionGraphTask::CreateAndDispatchWhenReady([]()
{
    // Task code here
});
MyTask->Wait(); // Optionally wait for the task to complete

Unreal Engine utilizes Worker Threads to perform background tasks that do not require immediate attention. These threads handle tasks such as:

Asset loading
Physics calculations
AI processing

Worker threads help offload work from the Game Thread and Render Thread, ensuring smoother gameplay and responsiveness.

1- Game Thread and Render Thread Coordination:

The Game Thread prepares data for rendering, while the Render Thread processes this data and communicates with the GPU to draw the frame.

2- Using the Task Graph System:

You can create and schedule tasks to run concurrently using the Task Graph System.
Example: Running a computationally intensive task in parallel.

				
					FGraphEventRef ComputeTask = FFunctionGraphTask::CreateAndDispatchWhenReady([]()
{
    // Perform heavy computation here
});
ComputeTask->Wait(); // Optionally wait for the task to complete

3- Worker Threads for Asset Loading:

Background asset loading ensures that the Game Thread is not blocked while assets are being loaded.
Example: Asynchronously loading a texture.

				
					UTexture2D* MyTexture = LoadObject<UTexture2D>(nullptr, TEXT("/Game/Textures/MyTexture"));

Understanding the threading model in Unreal Engine 5 is essential for implementing efficient and responsive multithreading in your projects. By leveraging the Game Thread, Render Thread, Task Graph System, and Worker Threads, you can optimize performance and create a smoother gameplay experience. In the next section, we will explore basic multithreading concepts and how they apply to Unreal Engine development.

Before diving into the specifics of implementing multithreading in Unreal Engine 5, it’s essential to understand some basic concepts of multithreading and concurrency. These fundamentals will help you grasp how Unreal Engine manages tasks and threads, and how you can leverage these features in your projects.

Overview of Threads and Concurrency

Threads are the smallest units of processing that can be scheduled by an operating system. Multithreading is the ability of a CPU to execute multiple threads concurrently. In a multithreaded application, multiple threads can run simultaneously, improving performance by utilizing multiple CPU cores.

Concurrency refers to the ability of a program to make progress on multiple tasks at the same time. It is achieved through the use of threads, allowing different parts of a program to run independently and simultaneously.

Synchronous vs. Asynchronous Execution

Synchronous Execution: In synchronous execution, tasks are performed sequentially. Each task must complete before the next one starts. This can lead to inefficiencies, especially if a task involves waiting for I/O operations or other time-consuming processes.

Asynchronous Execution: In asynchronous execution, tasks can run concurrently, without waiting for each other to complete. This allows for more efficient use of resources and can significantly improve the performance of an application.

Multithreading in Unreal Engine 5

Unreal Engine 5 provides several mechanisms for implementing multithreading, including manual thread creation, the Task Graph System, and asynchronous tasks. Understanding these mechanisms will help you choose the appropriate method for your specific needs.

1- FRunnable and FRunnableThread

FRunnable: An interface that provides a way to define the work that a thread will perform. It includes methods like Init, Run, and Stop.
FRunnableThread: A class that creates and manages a thread that runs an FRunnable object.

				
					class FMyRunnable : public FRunnable
{
public:
    virtual bool Init() override { return true; }
    virtual uint32 Run() override
    {
        // Thread work here
        return 0;
    }
    virtual void Stop() override {}
};

FMyRunnable* MyRunnable = new FMyRunnable();
FRunnableThread* MyThread = FRunnableThread::Create(MyRunnable, TEXT("MyThread"));

2- Task Graph System

The Task Graph System is a high-level abstraction for managing and executing tasks concurrently. It is used for scheduling small units of work that can run in parallel.
FGraphEventRef: Represents a reference to a task or event.
FFunctionGraphTask: A helper class for creating and scheduling tasks.

				
					FGraphEventRef MyTask = FFunctionGraphTask::CreateAndDispatchWhenReady([]()
{
    // Task code here
});
MyTask->Wait(); // Optionally wait for the task to complete

3- FAsync and Asynchronous Tasks

FAsync: A utility for running tasks asynchronously. It is often used for operations that can be performed in the background without blocking the main thread.

				
					FAsyncTask<FMyAsyncTask> MyAsyncTask;
MyAsyncTask.StartBackgroundTask();

1- Simple Thread Example Using FRunnable

Define a class that implements the FRunnable interface.
Create and start a thread to run the FRunnable object.

				
					class FMyRunnable : public FRunnable
{
public:
    virtual bool Init() override { return true; }
    virtual uint32 Run() override
    {
        // Perform thread work here
        for (int32 i = 0; i < 10; ++i)
        {
            UE_LOG(LogTemp, Warning, TEXT("Thread is running: %d"), i);
            FPlatformProcess::Sleep(1.0f); // Sleep for 1 second
        }
        return 0;
    }
    virtual void Stop() override {}
};

FMyRunnable* MyRunnable = new FMyRunnable();
FRunnableThread* MyThread = FRunnableThread::Create(MyRunnable, TEXT("MyThread"));

2- Using FGraphEventRef and FFunctionGraphTask

Create and schedule a task using the Task Graph System.

				
					FGraphEventRef MyTask = FFunctionGraphTask::CreateAndDispatchWhenReady([]()
{
    // Task code here
    UE_LOG(LogTemp, Warning, TEXT("Task is running"));
});
MyTask->Wait(); // Optionally wait for the task to complete

3- Running Asynchronous Tasks with FAsync

Use FAsync to run a task asynchronously.

				
					FAsyncTask<FMyAsyncTask> MyAsyncTask;
MyAsyncTask.StartBackgroundTask();

Understanding basic multithreading concepts is essential for effectively using Unreal Engine 5’s multithreading capabilities. By grasping the differences between synchronous and asynchronous execution, and learning about Unreal’s threading mechanisms, you can create efficient and responsive applications. In the next section, we will dive into creating and managing threads in Unreal Engine 5 using FRunnable and FRunnableThread.

In Unreal Engine 5, creating and managing threads can be done using the FRunnable and FRunnableThread classes. These classes provide a framework for defining and running tasks on separate threads, allowing for parallel execution and improved performance.

FRunnable is an interface that you implement to define the work that a thread will perform. It includes the following methods:

Init(): Called once when the thread starts. Use this for any initialization work.
Run(): Contains the main logic for the thread. This method runs in a loop until the thread is stopped.
Stop(): Called to stop the thread. Use this to clean up resources.

FRunnableThread is a class that creates and manages a thread running an FRunnable object.

Step-by-Step Guide to Creating a Thread

Define the Runnable Class:
- Create a class that implements the FRunnable interface.
- Implement the Init, Run, and Stop methods.

				
					class FMyRunnable : public FRunnable
{
public:
    // Constructor and destructor
    FMyRunnable() {}
    virtual ~FMyRunnable() {}

    // Initialization logic
    virtual bool Init() override
    {
        // Initialization code here
        UE_LOG(LogTemp, Warning, TEXT("Thread initialized"));
        return true;
    }

    // Main thread logic
    virtual uint32 Run() override
    {
        // Thread work here
        for (int32 i = 0; i < 10; ++i)
        {
            UE_LOG(LogTemp, Warning, TEXT("Thread running: %d"), i);
            FPlatformProcess::Sleep(1.0f); // Sleep for 1 second
        }
        return 0;
    }

    // Cleanup logic
    virtual void Stop() override
    {
        // Cleanup code here
        UE_LOG(LogTemp, Warning, TEXT("Thread stopping"));
    }
};

2.Create and Start the Thread:

Create an instance of your runnable class.
Use FRunnableThread to create and start a new thread that runs your runnable.

				
					FMyRunnable* MyRunnable = new FMyRunnable();
FRunnableThread* MyThread = FRunnableThread::Create(MyRunnable, TEXT("MyThread"));

3.Stopping the Thread:

Call the Stop method on your runnable object to stop the thread.
Optionally, you can use a condition variable or a boolean flag to signal the thread to stop.

				
					MyRunnable->Stop();
MyThread->WaitForCompletion();
delete MyRunnable;
delete MyThread;

Let’s implement a more practical example where we perform a computational task on a separate thread.

Define the Runnable Task:

				
					class FPrimeNumberRunnable : public FRunnable
{
private:
    int32 MaxNumber;
    TArray<int32> PrimeNumbers;

public:
    FPrimeNumberRunnable(int32 InMaxNumber)
        : MaxNumber(InMaxNumber)
    {
    }

    virtual bool Init() override
    {
        UE_LOG(LogTemp, Warning, TEXT("Prime number thread initialized"));
        return true;
    }

    virtual uint32 Run() override
    {
        for (int32 Num = 2; Num <= MaxNumber; ++Num)
        {
            bool bIsPrime = true;
            for (int32 Div = 2; Div <= FMath::Sqrt(Num); ++Div)
            {
                if (Num % Div == 0)
                {
                    bIsPrime = false;
                    break;
                }
            }
            if (bIsPrime)
            {
                PrimeNumbers.Add(Num);
            }
        }
        return 0;
    }

    virtual void Stop() override
    {
        UE_LOG(LogTemp, Warning, TEXT("Prime number thread stopping"));
    }

    const TArray<int32>& GetPrimeNumbers() const
    {
        return PrimeNumbers;
    }
};

2.Create and Start the Prime Number Thread:

				
					int32 MaxNumber = 100;
FPrimeNumberRunnable* PrimeRunnable = new FPrimeNumberRunnable(MaxNumber);
FRunnableThread* PrimeThread = FRunnableThread::Create(PrimeRunnable, TEXT("PrimeThread"));

// Wait for the thread to complete
PrimeThread->WaitForCompletion();

// Retrieve and log the prime numbers
const TArray<int32>& PrimeNumbers = PrimeRunnable->GetPrimeNumbers();
for (int32 Prime : PrimeNumbers)
{
    UE_LOG(LogTemp, Warning, TEXT("Prime number: %d"), Prime);
}

// Clean up
delete PrimeRunnable;
delete PrimeThread;

Creating and managing threads in Unreal Engine 5 using FRunnable and FRunnableThread allows you to offload work from the main thread and take advantage of multi-core processors. By understanding how to define runnable tasks and manage their lifecycle, you can implement efficient and responsive multithreaded applications. In the next section, we will explore the Task Graph System and how to use it for parallel processing.

The Task Graph System in Unreal Engine 5 is a powerful framework for managing and executing tasks concurrently. It provides a high-level abstraction for parallel processing, allowing developers to schedule and execute tasks efficiently across multiple threads. This system is particularly useful for distributing workloads and improving the performance of your game or application.

The Task Graph System allows you to break down complex tasks into smaller, manageable units of work that can be executed concurrently. It is designed to optimize CPU usage by leveraging all available cores, ensuring that tasks are processed in parallel whenever possible.

Key components of the Task Graph System include:

Tasks: Units of work that can be executed concurrently.
Events: Mechanisms to signal the completion of tasks.
Dependencies: Relationships between tasks that define the order of execution.

The Task Graph System uses the FGraphEventRef and FFunctionGraphTask classes to create and manage tasks.

FGraphEventRef: Represents a reference to a task or event. It is used to track the completion of tasks and manage dependencies.
FFunctionGraphTask: A helper class for creating and scheduling tasks. It allows you to define the work that a task will perform and dispatch it for execution.

Let’s look at some practical examples to demonstrate how to use the Task Graph System.

1.Simple Task Example

In this example, we create a simple task that runs concurrently and logs a message.

				
					FGraphEventRef SimpleTask = FFunctionGraphTask::CreateAndDispatchWhenReady([]()
{
    UE_LOG(LogTemp, Warning, TEXT("Simple task is running"));
});
SimpleTask->Wait(); // Optionally wait for the task to complete

2.Task with Dependencies

You can create tasks with dependencies, ensuring that certain tasks are completed before others begin.

				
					// Create the first task
FGraphEventRef FirstTask = FFunctionGraphTask::CreateAndDispatchWhenReady([]()
{
    UE_LOG(LogTemp, Warning, TEXT("First task is running"));
});

// Create the second task, which depends on the first task
FGraphEventRef SecondTask = FFunctionGraphTask::CreateAndDispatchWhenReady([]()
{
    UE_LOG(LogTemp, Warning, TEXT("Second task is running"));
}, TStatId(), FirstTask);

// Wait for both tasks to complete
FirstTask->Wait();
SecondTask->Wait();

3.Parallel Processing Example

In this example, we demonstrate parallel processing by creating multiple tasks to perform a computationally intensive operation.

				
					void ParallelComputation(int32 Start, int32 End)
{
    for (int32 i = Start; i < End; ++i)
    {
        // Perform computation here
    }
}

int32 NumTasks = 4;
int32 Range = 1000 / NumTasks;
TArray<FGraphEventRef> Tasks;

for (int32 i = 0; i < NumTasks; ++i)
{
    int32 Start = i * Range;
    int32 End = Start + Range;

    FGraphEventRef Task = FFunctionGraphTask::CreateAndDispatchWhenReady([Start, End]()
    {
        ParallelComputation(Start, End);
    });
    Tasks.Add(Task);
}

// Wait for all tasks to complete
for (FGraphEventRef Task : Tasks)
{
    Task->Wait();
}

4.Using Enqueue Function

Another way to add tasks to the Task Graph System is by using the Enqueue function, which allows you to specify the task and its dependencies.

				
					FGraphEventRef MyTask = FGraphEvent::CreateGraphEvent();
FGraphEventRef Dependency = FFunctionGraphTask::CreateAndDispatchWhenReady([]()
{
    UE_LOG(LogTemp, Warning, TEXT("Dependency task running"));
});

FFunctionGraphTask::CreateAndDispatchWhenReady([]()
{
    UE_LOG(LogTemp, Warning, TEXT("Main task running"));
}, TStatId(), Dependency);

The Task Graph System in Unreal Engine 5 provides a robust framework for managing and executing tasks concurrently. By leveraging this system, you can efficiently distribute workloads across multiple threads, improving the performance and responsiveness of your application. In the next section, we will explore using async tasks and the FAsync class for asynchronous task execution.

Unreal Engine 5 provides powerful tools for managing asynchronous tasks through the FAsync utility and related classes. These tools enable you to run tasks in the background without blocking the main thread, improving the responsiveness and performance of your game or application.

FAsync is a utility class in Unreal Engine that allows you to run tasks asynchronously. It provides a straightforward way to perform operations in the background, ensuring that your main thread remains responsive.

Key Concepts of FAsync

Asynchronous Execution: Tasks are executed in the background, allowing the main thread to continue running without interruption.
Task Management: FAsync provides methods for managing the lifecycle of asynchronous tasks, including starting, stopping, and waiting for completion.
Lambda Functions: FAsync often uses lambda functions to define the work that the task will perform.

Let’s look at some practical examples to demonstrate how to use FAsync for asynchronous task execution.

1.Simple Async Task

In this example, we create a simple asynchronous task that runs in the background and logs a message.

				
					#include "Async/Async.h"

void RunSimpleAsyncTask()
{
    FAsyncTask<FMyAsyncTask> MyAsyncTask;
    MyAsyncTask.StartBackgroundTask();
}

class FMyAsyncTask : public FNonAbandonableTask
{
public:
    void DoWork()
    {
        UE_LOG(LogTemp, Warning, TEXT("Simple async task is running"));
    }

    FORCEINLINE TStatId GetStatId() const
    {
        RETURN_QUICK_DECLARE_CYCLE_STAT(FMyAsyncTask, STATGROUP_ThreadPoolAsyncTasks);
    }
};

2.Returning Results from Async Tasks

You can use FAsync to run a task that returns a result. This is useful for operations that require processing and returning data.

				
					#include "Async/Async.h"

void RunAsyncTaskWithResult()
{
    auto AsyncTask = FAsync::Async(EAsyncExecution::Thread, []() -> int32
    {
        // Perform a computation or task
        int32 Result = 42; // Example result
        return Result;
    });

    int32 ComputedResult = AsyncTask.Get();
    UE_LOG(LogTemp, Warning, TEXT("Computed result: %d"), ComputedResult);
}

3.Using EAsyncExecution to Control Execution

FAsync provides different execution options through the EAsyncExecution enum, allowing you to control where the task runs.

EAsyncExecution::Thread: Runs the task on a background thread.
EAsyncExecution::ThreadPool: Runs the task on a thread pool.
EAsyncExecution::TaskGraph: Runs the task using the Task Graph System.

				
					#include "Async/Async.h"

void RunAsyncTaskWithExecutionOption()
{
    auto AsyncTask = FAsync::Async(EAsyncExecution::ThreadPool, []() -> int32
    {
        // Perform a computation or task
        int32 Result = 42; // Example result
        return Result;
    });

    int32 ComputedResult = AsyncTask.Get();
    UE_LOG(LogTemp, Warning, TEXT("Computed result: %d"), ComputedResult);
}

Cancelling Async Tasks

You can implement logic to cancel an asynchronous task if needed. This is useful for long-running tasks that may need to be stopped under certain conditions.

				
					#include "Async/Async.h"

class FMyCancellableAsyncTask : public FNonAbandonableTask
{
public:
    bool bShouldCancel;

    FMyCancellableAsyncTask() : bShouldCancel(false) {}

    void DoWork()
    {
        for (int32 i = 0; i < 10; ++i)
        {
            if (bShouldCancel)
            {
                UE_LOG(LogTemp, Warning, TEXT("Async task was cancelled"));
                return;
            }
            UE_LOG(LogTemp, Warning, TEXT("Async task running: %d"), i);
            FPlatformProcess::Sleep(1.0f); // Simulate work
        }
    }

    void Cancel()
    {
        bShouldCancel = true;
    }

    FORCEINLINE TStatId GetStatId() const
    {
        RETURN_QUICK_DECLARE_CYCLE_STAT(FMyCancellableAsyncTask, STATGROUP_ThreadPoolAsyncTasks);
    }
};

void RunCancellableAsyncTask()
{
    FMyCancellableAsyncTask* AsyncTask = new FMyCancellableAsyncTask();
    FAsyncTask<FMyCancellableAsyncTask>* MyAsyncTask = new FAsyncTask<FMyCancellableAsyncTask>(AsyncTask);
    MyAsyncTask->StartBackgroundTask();

    // Simulate some condition to cancel the task
    FPlatformProcess::Sleep(3.0f);
    AsyncTask->Cancel();

    MyAsyncTask->EnsureCompletion();
    delete MyAsyncTask;
}

Using FAsync and related classes, you can efficiently manage asynchronous tasks in Unreal Engine 5. These tools allow you to perform background operations without blocking the main thread, improving the responsiveness and performance of your application. In the next section, we will explore synchronization primitives and how to use them to ensure thread safety in your multithreaded applications.

In multithreaded applications, synchronization primitives are essential for ensuring that threads can safely access shared resources without causing data corruption or race conditions. Unreal Engine 5 provides several synchronization primitives that you can use to manage concurrency and ensure thread safety in your projects.

1.FCriticalSection

A mutual exclusion lock (mutex) that prevents multiple threads from accessing a shared resource simultaneously. Only one thread can own the lock at a time.
Use FCriticalSection to protect critical sections of code where shared data is accessed.

2.FScopeLock

A helper class that provides automatic locking and unlocking of an FCriticalSection. It ensures that the lock is released when the FScopeLock goes out of scope.
Use FScopeLock to simplify the management of critical sections and avoid common pitfalls with manual locking and unlocking.

3.FEvent

A synchronization primitive that allows threads to wait for or signal events. FEvent can be used to coordinate the execution of threads.
Use FEvent to implement signaling mechanisms between threads, such as waiting for a task to complete or triggering an action.

Let’s look at some practical examples to demonstrate how to use synchronization primitives in Unreal Engine 5.

1.Using FCriticalSection and FScopeLock

In this example, we use FCriticalSection and FScopeLock to protect a shared resource from concurrent access by multiple threads.

				
					#include "HAL/ThreadSafeCounter.h"
#include "HAL/CriticalSection.h"
#include "Misc/ScopeLock.h"

// Shared resource
int32 SharedCounter = 0;
FCriticalSection CriticalSection;

void IncrementCounter()
{
    for (int32 i = 0; i < 1000; ++i)
    {
        // Protect the critical section with FScopeLock
        FScopeLock Lock(&CriticalSection);
        SharedCounter++;
    }
}

void RunMultithreadedIncrement()
{
    FGraphEventRef Task1 = FFunctionGraphTask::CreateAndDispatchWhenReady([]()
    {
        IncrementCounter();
    });

    FGraphEventRef Task2 = FFunctionGraphTask::CreateAndDispatchWhenReady([]()
    {
        IncrementCounter();
    });

    // Wait for both tasks to complete
    Task1->Wait();
    Task2->Wait();

    UE_LOG(LogTemp, Warning, TEXT("Final counter value: %d"), SharedCounter);
}

2.Using FEvent for Signaling

In this example, we use FEvent to signal the completion of a task and coordinate between threads.

				
					#include "HAL/Event.h"
#include "HAL/Runnable.h"
#include "HAL/RunnableThread.h"

class FSignalingRunnable : public FRunnable
{
private:
    FEvent* CompletionEvent;

public:
    FSignalingRunnable(FEvent* InCompletionEvent)
        : CompletionEvent(InCompletionEvent)
    {
    }

    virtual bool Init() override
    {
        return true;
    }

    virtual uint32 Run() override
    {
        // Simulate work
        FPlatformProcess::Sleep(2.0f);

        // Signal completion
        CompletionEvent->Trigger();

        return 0;
    }

    virtual void Stop() override
    {
    }
};

void RunSignalingTask()
{
    // Create an event
    FEvent* CompletionEvent = FPlatformProcess::CreateSynchEvent(true);

    // Create and start the runnable
    FSignalingRunnable* Runnable = new FSignalingRunnable(CompletionEvent);
    FRunnableThread* Thread = FRunnableThread::Create(Runnable, TEXT("SignalingThread"));

    // Wait for the event to be triggered
    CompletionEvent->Wait();

    UE_LOG(LogTemp, Warning, TEXT("Task completed"));

    // Clean up
    delete Runnable;
    delete Thread;
    FPlatformProcess::ReturnSynchEventToPool(CompletionEvent);
}

3.Using FPlatformProcess::Sleep for Delays

Sometimes you may need to introduce delays in your tasks. FPlatformProcess::Sleep can be used to pause the execution of a thread for a specified duration.

				
					void DelayedTask()
{
    UE_LOG(LogTemp, Warning, TEXT("Task started"));
    FPlatformProcess::Sleep(2.0f); // Sleep for 2 seconds
    UE_LOG(LogTemp, Warning, TEXT("Task completed after delay"));
}

void RunDelayedTask()
{
    FGraphEventRef Task = FFunctionGraphTask::CreateAndDispatchWhenReady([]()
    {
        DelayedTask();
    });

    Task->Wait(); // Wait for the task to complete
}

Synchronization primitives are essential tools for managing concurrency and ensuring thread safety in multithreaded applications. By using FCriticalSection, FScopeLock, and FEvent, you can coordinate the execution of threads and protect shared resources from concurrent access. In the next section, we will explore thread pools and how to use them for efficient parallel processing in Unreal Engine 5.

Thread pools are an efficient way to manage and execute multiple tasks concurrently without the overhead of constantly creating and destroying threads. Unreal Engine 5 provides built-in support for thread pools, allowing you to schedule tasks and run them in parallel using a pool of pre-allocated threads.

A thread pool is a collection of reusable threads that can be used to execute tasks. When a task is scheduled, it is assigned to a thread from the pool. Once the task is complete, the thread returns to the pool, ready to execute another task. This approach reduces the overhead associated with thread creation and destruction, leading to more efficient execution of concurrent tasks.

Reduced Overhead: By reusing threads, the overhead of creating and destroying threads is minimized.
Improved Performance: Tasks can be executed concurrently, making full use of multi-core processors.
Simplified Task Management: The thread pool manages the scheduling and execution of tasks, simplifying the code required for concurrent execution.

Unreal Engine 5 provides a built-in thread pool that you can use to schedule and run tasks. You can use the FQueuedThreadPool class to interact with the thread pool.

Let’s look at some practical examples to demonstrate how to use thread pools in Unreal Engine 5.

1.Creating and Using a Thread Pool

In this example, we create a custom thread pool and use it to run tasks concurrently.

				
					#include "HAL/ThreadPool.h"
#include "HAL/Runnable.h"
#include "HAL/RunnableThread.h"

// Define a runnable task
class FMyThreadPoolTask : public FRunnable
{
public:
    FMyThreadPoolTask(int32 InTaskId)
        : TaskId(InTaskId)
    {
    }

    virtual bool Init() override
    {
        return true;
    }

    virtual uint32 Run() override
    {
        // Perform the task
        UE_LOG(LogTemp, Warning, TEXT("Task %d is running"), TaskId);
        FPlatformProcess::Sleep(1.0f); // Simulate work
        return 0;
    }

    virtual void Stop() override
    {
    }

private:
    int32 TaskId;
};

void RunThreadPoolExample()
{
    // Create a thread pool
    FQueuedThreadPool* ThreadPool = FQueuedThreadPool::Allocate();
    ThreadPool->Create(4, 128 * 1024, TPri_Normal); // 4 threads with stack size 128KB

    // Schedule tasks in the thread pool
    for (int32 i = 0; i < 10; ++i)
    {
        ThreadPool->AddQueuedWork(new FMyThreadPoolTask(i));
    }

    // Optionally wait for all tasks to complete
    ThreadPool->Destroy();
    delete ThreadPool;
}

2.Using the Global Thread Pool

Unreal Engine provides a global thread pool that you can use to schedule tasks without creating a custom thread pool.

				
					#include "Async/AsyncWork.h"

// Define a runnable task
class FMyAsyncTask : public FNonAbandonableTask
{
public:
    FMyAsyncTask(int32 InTaskId)
        : TaskId(InTaskId)
    {
    }

    void DoWork()
    {
        // Perform the task
        UE_LOG(LogTemp, Warning, TEXT("Task %d is running"), TaskId);
        FPlatformProcess::Sleep(1.0f); // Simulate work
    }

    FORCEINLINE TStatId GetStatId() const
    {
        RETURN_QUICK_DECLARE_CYCLE_STAT(FMyAsyncTask, STATGROUP_ThreadPoolAsyncTasks);
    }

private:
    int32 TaskId;
};

void RunGlobalThreadPoolExample()
{
    // Schedule tasks in the global thread pool
    for (int32 i = 0; i < 10; ++i)
    {
        (new FAutoDeleteAsyncTask<FMyAsyncTask>(i))->StartBackgroundTask();
    }
}

3.Implementing a Complex Task with Dependencies

In this example, we use the global thread pool to run tasks with dependencies, ensuring that tasks are executed in the correct order.

				
					#include "Async/AsyncWork.h"

// Define a complex task
class FMyComplexTask : public FNonAbandonableTask
{
public:
    FMyComplexTask(int32 InTaskId, TSharedPtr<FMyComplexTask> InDependency)
        : TaskId(InTaskId), Dependency(InDependency)
    {
    }

    void DoWork()
    {
        if (Dependency.IsValid())
        {
            Dependency->EnsureCompletion(); // Wait for the dependency to complete
        }

        // Perform the task
        UE_LOG(LogTemp, Warning, TEXT("Complex task %d is running"), TaskId);
        FPlatformProcess::Sleep(1.0f); // Simulate work
    }

    void EnsureCompletion()
    {
        AsyncTask->EnsureCompletion();
    }

    FORCEINLINE TStatId GetStatId() const
    {
        RETURN_QUICK_DECLARE_CYCLE_STAT(FMyComplexTask, STATGROUP_ThreadPoolAsyncTasks);
    }

private:
    int32 TaskId;
    TSharedPtr<FMyComplexTask> Dependency;
    FAutoDeleteAsyncTask<FMyComplexTask>* AsyncTask;
};

void RunComplexTaskExample()
{
    // Create tasks with dependencies
    TSharedPtr<FMyComplexTask> Task1 = MakeShareable(new FMyComplexTask(1, nullptr));
    TSharedPtr<FMyComplexTask> Task2 = MakeShareable(new FMyComplexTask(2, Task1));
    TSharedPtr<FMyComplexTask> Task3 = MakeShareable(new FMyComplexTask(3, Task2));

    // Schedule tasks in the global thread pool
    (new FAutoDeleteAsyncTask<FMyComplexTask>(*Task1))->StartBackgroundTask();
    (new FAutoDeleteAsyncTask<FMyComplexTask>(*Task2))->StartBackgroundTask();
    (new FAutoDeleteAsyncTask<FMyComplexTask>(*Task3))->StartBackgroundTask();
}

Thread pools are an efficient way to manage and execute multiple tasks concurrently in Unreal Engine 5. By using custom thread pools or the global thread pool, you can optimize the performance of your application and ensure that tasks are executed efficiently. In the next section, we will explore performance considerations and best practices for optimizing multithreaded code in Unreal Engine 5.

Optimizing multithreaded code is essential for achieving high performance in Unreal Engine 5. While multithreading can significantly improve the efficiency of your application, it’s important to consider various factors that affect performance. This section covers best practices and performance considerations to help you get the most out of your multithreaded code.

Use Profiling Tools
- Unreal Engine provides powerful profiling tools such as Unreal Insights and the built-in profiler. Use these tools to identify performance bottlenecks and optimize your code.
- Unreal Insights allows you to capture and analyze performance data, including CPU and GPU usage, memory allocation, and task execution times.
Minimize Lock Contention
- Lock contention occurs when multiple threads compete for the same lock, leading to performance degradation. Minimize the use of locks and ensure that critical sections are as short as possible.
- Use fine-grained locking strategies to reduce contention. For example, instead of locking an entire data structure, lock individual elements or smaller sections.
Avoid Blocking Operations
- Avoid blocking operations on the main thread or critical paths. Blocking operations, such as waiting for I/O or network responses, can cause frame drops and reduce responsiveness.
- Use asynchronous operations and background threads for tasks that may block execution.
Use Thread Pools Effectively
- Thread pools can improve performance by reusing threads and reducing the overhead of thread creation and destruction. Ensure that your thread pool is appropriately sized for the workload.
- Avoid oversubscribing the CPU by creating too many threads. The number of threads should ideally match the number of available CPU cores.
Optimize Data Access Patterns
- Optimize data access patterns to minimize cache misses and improve memory access efficiency. Strive for data locality by organizing data structures to maximize cache usage.
- Use aligned memory allocation and contiguous memory blocks to improve cache performance.

- Race Conditions
  - Race conditions occur when multiple threads access shared data simultaneously, leading to unpredictable results. Use synchronization primitives such as FCriticalSection and FScopeLock to prevent race conditions.
  - Carefully review and test your code to identify and resolve race conditions.
- Deadlocks
  - Deadlocks occur when two or more threads are waiting for each other to release locks, causing a standstill. Avoid deadlocks by following consistent lock ordering and using timeout mechanisms.
  - Use tools and techniques to detect and diagnose deadlocks during development and testing.
- False Sharing
  - False sharing occurs when multiple threads access different variables that reside on the same cache line, causing unnecessary cache invalidations. Align data structures to avoid false sharing and improve cache performance.

Let’s optimize a multithreaded task that performs a computationally intensive operation by minimizing lock contention and improving data access patterns.

1.Original Code with Potential Issues

				
					#include "HAL/ThreadPool.h"
#include "HAL/Runnable.h"

class FOriginalTask : public FRunnable
{
public:
    TArray<int32> SharedData;
    FCriticalSection CriticalSection;

    virtual bool Init() override
    {
        return true;
    }

    virtual uint32 Run() override
    {
        for (int32 i = 0; i < 1000; ++i)
        {
            FScopeLock Lock(&CriticalSection);
            SharedData.Add(i); // Potential lock contention
        }
        return 0;
    }

    virtual void Stop() override
    {
    }
};

void RunOriginalTask()
{
    FOriginalTask* Task = new FOriginalTask();
    FRunnableThread* Thread = FRunnableThread::Create(Task, TEXT("OriginalTaskThread"));
    Thread->WaitForCompletion();
    delete Task;
    delete Thread;
}

2.Optimized Code

				
					#include "HAL/ThreadPool.h"
#include "HAL/Runnable.h"
#include "Containers/Array.h"

class FOptimizedTask : public FRunnable
{
public:
    TArray<int32> LocalData; // Local data to minimize lock contention
    TArray<int32>* SharedData;
    FCriticalSection* CriticalSection;

    FOptimizedTask(TArray<int32>* InSharedData, FCriticalSection* InCriticalSection)
        : SharedData(InSharedData), CriticalSection(InCriticalSection)
    {
    }

    virtual bool Init() override
    {
        return true;
    }

    virtual uint32 Run() override
    {
        for (int32 i = 0; i < 1000; ++i)
        {
            LocalData.Add(i);
        }

        // Merge local data into shared data with minimal lock contention
        FScopeLock Lock(CriticalSection);
        SharedData->Append(LocalData);

        return 0;
    }

    virtual void Stop() override
    {
    }
};

void RunOptimizedTask()
{
    TArray<int32> SharedData;
    FCriticalSection CriticalSection;

    // Create and start multiple tasks
    TArray<FRunnableThread*> Threads;
    for (int32 i = 0; i < 4; ++i)
    {
        FOptimizedTask* Task = new FOptimizedTask(&SharedData, &CriticalSection);
        FRunnableThread* Thread = FRunnableThread::Create(Task, *FString::Printf(TEXT("OptimizedTaskThread%d"), i));
        Threads.Add(Thread);
    }

    // Wait for all tasks to complete
    for (FRunnableThread* Thread : Threads)
    {
        Thread->WaitForCompletion();
        delete Thread;
    }

    // Log the final size of the shared data array
    UE_LOG(LogTemp, Warning, TEXT("Final size of shared data: %d"), SharedData.Num());
}

Multithreading in Unreal Engine 5 can significantly enhance various aspects of your game, from AI calculations to asset loading and gameplay systems. This section explores practical examples and use cases where multithreading can be effectively utilized to improve performance and responsiveness.

1.Multithreading in AI Calculations

AI calculations can be computationally intensive, especially in games with complex behaviors and large numbers of NPCs. By offloading AI processing to background threads, you can ensure smooth gameplay without impacting the main thread.

Example: Multithreaded AI Pathfinding

				
					#include "HAL/ThreadPool.h"
#include "HAL/Runnable.h"
#include "NavigationSystem.h"
#include "AIController.h"

class FAIPathfindingTask : public FRunnable
{
public:
    AAIController* AIController;
    FVector Destination;

    FAIPathfindingTask(AAIController* InAIController, const FVector& InDestination)
        : AIController(InAIController), Destination(InDestination)
    {
    }

    virtual bool Init() override
    {
        return true;
    }

    virtual uint32 Run() override
    {
        FNavLocation NavLocation;
        UNavigationSystemV1* NavSys = FNavigationSystem::GetCurrent<UNavigationSystemV1>(AIController->GetWorld());

        if (NavSys && NavSys->GetRandomReachablePointInRadius(Destination, 1000.0f, NavLocation))
        {
            AIController->MoveToLocation(NavLocation.Location);
        }

        return 0;
    }

    virtual void Stop() override
    {
    }
};

void RunAIPathfinding(AAIController* AIController, const FVector& Destination)
{
    FAIPathfindingTask* PathfindingTask = new FAIPathfindingTask(AIController, Destination);
    FRunnableThread::Create(PathfindingTask, TEXT("AIPathfindingThread"));
}

2.Parallelizing Asset Loading and Processing

Loading and processing assets can be a time-consuming task that can impact the responsiveness of your game. By performing these operations in the background, you can improve load times and ensure a smoother experience for players.

Example: Asynchronous Asset Loading

				
					#include "Async/Async.h"
#include "Engine/StreamableManager.h"
#include "Engine/AssetManager.h"

void LoadAssetAsync(const FString& AssetPath)
{
    FStreamableManager& Streamable = UAssetManager::GetStreamableManager();
    Streamable.RequestAsyncLoad(FSoftObjectPath(AssetPath), [AssetPath]()
    {
        UObject* LoadedAsset = StaticLoadObject(UObject::StaticClass(), nullptr, *AssetPath);
        if (LoadedAsset)
        {
            UE_LOG(LogTemp, Warning, TEXT("Asset loaded: %s"), *AssetPath);
        }
    });
}

3.Improving Performance with Multithreading in Gameplay Systems

Gameplay systems often involve complex calculations and state management. By leveraging multithreading, you can improve the performance and responsiveness of these systems.

Example: Parallel Processing of Game Logic

				
					#include "HAL/ThreadPool.h"
#include "HAL/Runnable.h"

class FGameplayTask : public FRunnable
{
public:
    int32 TaskId;

    FGameplayTask(int32 InTaskId)
        : TaskId(InTaskId)
    {
    }

    virtual bool Init() override
    {
        return true;
    }

    virtual uint32 Run() override
    {
        // Perform gameplay logic here
        UE_LOG(LogTemp, Warning, TEXT("Gameplay task %d is running"), TaskId);
        FPlatformProcess::Sleep(0.5f); // Simulate work
        return 0;
    }

    virtual void Stop() override
    {
    }
};

void RunGameplayTasks()
{
    TArray<FRunnableThread*> Threads;

    for (int32 i = 0; i < 10; ++i)
    {
        FGameplayTask* Task = new FGameplayTask(i);
        FRunnableThread* Thread = FRunnableThread::Create(Task, *FString::Printf(TEXT("GameplayTaskThread%d"), i));
        Threads.Add(Thread);
    }

    // Wait for all tasks to complete
    for (FRunnableThread* Thread : Threads)
    {
        Thread->WaitForCompletion();
        delete Thread;
    }
}

4.Multithreading in Animation Systems

Complex animations, particularly those involving physics simulations or procedural generation, can benefit from multithreading to ensure they run smoothly without affecting the main game loop.

Example: Multithreaded Animation Update

				
					#include "HAL/ThreadPool.h"
#include "HAL/Runnable.h"
#include "Animation/AnimInstance.h"

class FAnimationUpdateTask : public FRunnable
{
public:
    UAnimInstance* AnimInstance;

    FAnimationUpdateTask(UAnimInstance* InAnimInstance)
        : AnimInstance(InAnimInstance)
    {
    }

    virtual bool Init() override
    {
        return true;
    }

    virtual uint32 Run() override
    {
        // Perform animation update logic here
        AnimInstance->UpdateAnimation(0.016f); // Example update with 16ms delta time
        return 0;
    }

    virtual void Stop() override
    {
    }
};

void RunAnimationUpdate(UAnimInstance* AnimInstance)
{
    FAnimationUpdateTask* AnimationTask = new FAnimationUpdateTask(AnimInstance);
    FRunnableThread::Create(AnimationTask, TEXT("AnimationUpdateThread"));
}

Multithreading in Unreal Engine 5 can significantly enhance the performance and responsiveness of various systems, from AI calculations and asset loading to gameplay logic and animations. By leveraging the examples and use cases provided in this section, you can implement efficient and effective multithreading solutions in your projects. In the next section, we will explore debugging techniques and tools for identifying and resolving issues in multithreaded code.

Multithreading in Unreal Engine 5

Introduction

Importance of Multithreading in Game Development

Overview of Unreal Engine's Multithreading Capabilities

Why Use Multithreading in Unreal Engine?

Conclusion

Understanding the Threading Model

Game Thread

Render Thread

Task Graph System

Worker Threads

Examples of Thread Usage

Conclusion

Basic Multithreading Concepts

Overview of Threads and Concurrency

Synchronous vs. Asynchronous Execution

Multithreading in Unreal Engine 5

Key Multithreading Concepts in Unreal Engine

Practical Examples

Conclusion

Creating and Managing Threads

Using FRunnable and FRunnableThread

Step-by-Step Guide to Creating a Thread

Practical Example: Implementing a Runnable Task

Conclusion

Task Graph System

Overview of the Task Graph System

FGraphEventRef and FFunctionGraphTask

Practical Examples of Using the Task Graph System

Conclusion

Async Tasks and FAsync

Overview of FAsync

Key Concepts of FAsync

Practical Examples of Using FAsync

Conclusion

Synchronization Primitives

Overview of Synchronization Primitives

Practical Examples of Using Synchronization Primitives

Conclusion

Thread Pools

Overview of Thread Pools

Benefits of Using Thread Pools

Using Thread Pools in Unreal Engine

Practical Examples of Using Thread Pools

Conclusion

Performance Considerations

Profiling and Optimizing Multithreaded Code

Avoiding Common Pitfalls

Practical Example: Optimizing a Multithreaded Task

Conclusion

Practical Examples and Use Cases

1.Multithreading in AI Calculations

2.Parallelizing Asset Loading and Processing

3.Improving Performance with Multithreading in Gameplay Systems

4.Multithreading in Animation Systems

Conclusion

Amir Nobandegani

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