Parallel Luau

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With the Parallel Luau programming model, you can run code on multiple threads simultaneously, which can improve the performance of your experience. As you expand your experience with more content, you can adopt this model to help maintain the performance and safety of your Luau scripts.

Parallel Programming Model

By default, scripts execute sequentially. If your experience has complex logic or content, such as non-player characters (NPCs), raycasting validation, and procedural generation, then sequential execution might cause lag for your users. With the parallel programming model, you can split tasks into multiple scripts and run them in parallel. This makes your experience code run faster, which improves the user experience.

The parallel programming model also adds safety benefits to your code. By splitting code into multiple threads, when you edit code in one thread, it doesn't affect other code running in parallel. This reduces the risk of having one bug in your code corrupting the entire experience, and minimizes the delay for users in live servers when you push an update.

Adopting the parallel programming model doesn't mean to put everything in multiple threads. For example, the Server-side Raycasting Validation sets each individual user a remote event in parallel but still requires the initial code to run serially to change global properties, which is a common pattern for parallel execution.

Most times you need to combine serial and parallel phases to achieve your desired output, since currently there are some operations not supported in parallel that can prevent scripts from running, such as modifying instances in parallel phases. For more information on the level of usage of APIs in parallel, see Thread Safety.

Splitting Code Into Multiple Threads

To run your experience's scripts in multiple threads concurrently, you need to split them into logical chunks under different actors in the data model. Actors are represented by Actor instances inheriting from DataModel. They work as units of execution isolation that distribute the load across multiple cores running simultaneously.

Placing Actor Instances

You can put actors in proper containers or use them to replace the top-level instance types of your 3D entities such as NPCs and raycasters, then add corresponding scripts.

An example of a Script under an Actor

For most situations, you shouldn't put an actor as a child of another actor in the data model. However, if you decide to place a script nested within multiple actors for your specific use case, the script is owned by its closest ancestor actor.

A tree of actors and scripts that shows how a script is owned by its closest actor

Desynchronizing Threads

Though putting scripts under actors grants them the capability for parallel execution, by default the code still runs on the single thread serially, which doesn't improve the runtime performance. You need to call the task.desynchronize(), a yieldable function that suspends the execution of the current coroutine for running code in parallel and resumes it at the next parallel execution opportunity. To switch a script back to serial execution, call task.synchronize().

Alternatively, you can use RBXScriptSignal:ConnectParallel() method when you want to schedule a signal callback to immediately run your code in parallel upon triggering. You don't need to call task.desynchronize() inside the signal callback.

Desynchronize a Thread

local RunService = game:GetService("RunService")
RunService.Heartbeat:ConnectParallel(function()
... -- Some parallel code that computes a state update
task.synchronize()
... -- Some serial code that changes the state of instances
end)

Scripts that are part of the same actor always execute sequentially with respect to each other, so you need multiple actors. For example, if you put all parallel-enabled behavior scripts for your NPC in one actor, they still run serially on a single thread, but if you have multiple actors for different NPC logic, each of them runs in parallel on its own thread. For more information, see Best Practices.

Parallel code in Actors running serially in a single thread
Parallel code in Actors running simultaneously in multiple threads

Thread Safety

During the parallel execution, you can access most instances of the DataModel hierarchy as usual, but some API properties and functions aren't safe to read or write. If you use them in your parallel code, Roblox engine can automatically detect and prevent these accesses from occurring.

API members have a thread safety level that indicates whether and how you can use them in your parallel code, as the following table shows:

Safety LevelFor PropertiesFor Functions
UnsafeCannot be read or written in parallel.Cannot be called in parallel.
Read ParallelCan be read but not written in parallel.N/A
Local SafeCan be used within the same Actor; can be read but not written to by other Actors in parallel.Can be called within the same Actor; cannot be called by other Actors in parallel.
SafeCan be read and written.Can be called.

You can find thread safety tags for API members on the API reference. When using them, you should also consider how API calls or property changes might interact between parallel threads. Usually it's safe for multiple actors to read the same data as other actors but not modify the state of other actors.

Cross-Thread Communication

Under the multithreading context, you can still allow scripts in different actors to communicate with each other to exchange data, coordinate tasks, and synchronize activities. The engine supports the following mechanisms for cross-thread communication:

You can support multiple mechanisms to accommodate your cross-thread communication needs. For example, you can send a shared table through the Actor Messaging API.

Actor Messaging

The Actor Messaging API allows a script, either in a serial or parallel context, to send data to an actor in the same data model. Communication through this API is asynchronous, in which the sender doesn't block until the receiver receives the message.

When sending messages using this API, you need to define a topic for categorizing the message. Each message can only be sent to a single actor, but that actor can internally have multiple callbacks bound to a message. Only scripts that are descendants of an actor can receive messages.

The API has the following methods:

The following example shows how to use Actor:SendMessage() to define a topic and send a message on the sender's end:

Example Message Sender

-- Send two messages to the worker actor with a topic of "Greeting"
local workerActor = workspace.WorkerActor
workerActor:SendMessage("Greeting", "Hello World!")
workerActor:SendMessage("Greeting", "Welcome")
print("Sent messages")

The following example shows how to use Actor:BindToMessageParallel() to bind a callback for certain topic in a parallel context on the receiver's end:

Example Message Receiver

-- Get the actor this script is parented to
local actor = script:GetActor()
-- Bind a callback for the "Greeting" message topic
actor:BindToMessageParallel("Greeting", function(greetingString)
print(actor.Name, "-", greetingString)
end)
print("Bound to messages")

Shared Table

SharedTable is a table-like data structure accessible from scripts running under multiple actors. It's useful for situations that involve a large amount of data and require a common shared state between multiple threads. For example, when multiple actors work on a common world state that is not stored in the data model.

Sending a shared table to another actor doesn't make a copy of the data. Instead, shared tables allow safe and atomic updates by multiple scripts simultaneously. Every update to a shared table by one actor is immediately visible to all actors. Shared tables can also be cloned in a resource-efficient process that utilizes structural sharing instead of copying the underlying data.

Direct Data Model Communication

You can also facilitate communication between multiple threads directly using the data model, in which different actors can write and subsequently read properties or attributes. However, to maintain the thread-safety, scripts running in parallel generally can't write to the data model. So directly using the data model for communication comes with restrictions and may force scripts to synchronize frequently, which can impact performance of your scripts.

Examples

Server-Side Raycasting Validation

For a fighting and battle experience, you need to enable raycasting for your users' weapons. With the client simulating the weapons to achieve good latency, the server has to confirm the hit, which involves doing raycasts and some amount of heuristics that compute expected character velocity, and look at past behavior.

Instead of using a single centralized script that connects to a remote event that clients use to communicate hit information, you can run each hit validation process on the server side in parallel with every user character having a separate remote event.

The server-side script that runs under that character's Actor connects to this remote event using a parallel connection to run the relevant logic for confirming the hit. If the logic finds a confirmation of a hit, the damage is deducted, which involves changing properties, so it runs serially initially.


local tool = script.Parent.Parent
local remoteEvent = Instance.new("RemoteEvent") -- Create new remote event and parent it to the tool
remoteEvent.Name = "RemoteMouseEvent" -- Rename it so that the local script can look for it
remoteEvent.Parent = tool
local remoteEventConnection -- Create a reference for the remote event connection
-- Function which listens for a remote event
local function onRemoteMouseEvent(player: Player, clickLocation: CFrame)
-- SERIAL: Execute setup code in serial
local character = player.Character
-- Ignore the user's character while raycasting
local params = RaycastParams.new()
params.FilterType = Enum.RaycastFilterType.Exclude
params.FilterDescendantsInstances = { character }
-- PARALLEL: Perform the raycast in parallel
task.desynchronize()
local origin = tool.Handle.CFrame.Position
local epsilon = 0.01 -- Used to extend the ray slightly since the click location might be slightly offset from the object
local lookDirection = (1 + epsilon) * (clickLocation.Position - origin)
local raycastResult = workspace:Raycast(origin, lookDirection, params)
if raycastResult then
local hitPart = raycastResult.Instance
if hitPart and hitPart.Name == "block" then
local explosion = Instance.new("Explosion")
-- SERIAL: The code below modifies state outside of the actor
task.synchronize()
explosion.DestroyJointRadiusPercent = 0 -- Make the explosion non-deadly
explosion.Position = clickLocation.Position
-- Multiple actors could get the same part in a raycast and decide to destroy it
-- This is perfectly safe but it would result in two explosions at once instead of one
-- The following double checks that execution got to this part first
if hitPart.Parent then
explosion.Parent = workspace
hitPart:Destroy() -- Destroy it
end
end
end
end
-- Connect the signal in serial initially since some setup code is not able to run in parallel
remoteEventConnection = remoteEvent.OnServerEvent:Connect(onRemoteMouseEvent)

Server-Side Procedural Terrain Generation

To create a vast world for your experience, you can populate the world dynamically. Procedural generation typically creates independent terrain chunks, with the generator performing relatively intricate calculations for object placement, material usage, and voxel filling. Running generation code in parallel can enhance efficiency of the process. The following code sample serves as an example.


-- Parallel execution requires the use of actors
-- This script clones itself; the original initiates the process, while the clones act as workers
local actor = script:GetActor()
if actor == nil then
local workers = {}
for i = 1, 32 do
local actor = Instance.new("Actor")
script:Clone().Parent = actor
table.insert(workers, actor)
end
-- Parent all actors under self
for _, actor in workers do
actor.Parent = script
end
-- Instruct the actors to generate terrain by sending messages
-- In this example, actors are chosen randomly
task.defer(function()
local rand = Random.new()
local seed = rand:NextNumber()
local sz = 10
for x = -sz, sz do
for y = -sz, sz do
for z = -sz, sz do
workers[rand:NextInteger(1, #workers)]:SendMessage("GenerateChunk", x, y, z, seed)
end
end
end
end)
-- Exit from the original script; the rest of the code runs in each actor
return
end
function makeNdArray(numDim, size, elemValue)
if numDim == 0 then
return elemValue
end
local result = {}
for i = 1, size do
result[i] = makeNdArray(numDim - 1, size, elemValue)
end
return result
end
function generateVoxelsWithSeed(xd, yd, zd, seed)
local matEnums = {Enum.Material.CrackedLava, Enum.Material.Basalt, Enum.Material.Asphalt}
local materials = makeNdArray(3, 4, Enum.Material.CrackedLava)
local occupancy = makeNdArray(3, 4, 1)
local rand = Random.new()
for x = 0, 3 do
for y = 0, 3 do
for z = 0, 3 do
occupancy[x + 1][y + 1][z + 1] = math.noise(xd + 0.25 * x, yd + 0.25 * y, zd + 0.25 * z)
materials[x + 1][y + 1][z + 1] = matEnums[rand:NextInteger(1, #matEnums)]
end
end
end
return {materials = materials, occupancy = occupancy}
end
-- Bind the callback to be called in parallel execution context
actor:BindToMessageParallel("GenerateChunk", function(x, y, z, seed)
local voxels = generateVoxelsWithSeed(x, y, z, seed)
local corner = Vector3.new(x * 16, y * 16, z * 16)
-- Currently, WriteVoxels() must be called in the serial phase
task.synchronize()
workspace.Terrain:WriteVoxels(
Region3.new(corner, corner + Vector3.new(16, 16, 16)),
4,
voxels.materials,
voxels.occupancy
)
end)

Best Practices

To apply the maximum benefits of parallel programming, refer to the following best practices when adding your Lua code:

  • Avoid Long Computations — Even in parallel, long computations can block execution of other scripts and cause lag. Avoid using parallel programming to handle a large volume of long, unyielding calculations.

    Diagram demonstrating how overloading the parallel execution phase can still cause lag
  • Use the Right Number of Actors — For the best performance, use more Actors. Even if the device has fewer cores than Actors, the granularity allows for more efficient load balancing between the cores.

    Demonstration of how using more actors balances the load across cores

    This doesn't mean you should use as many Actors as possible. You should still divide code into Actors based on logic units rather than breaking code with connected logic to different Actors. For example, if you want to enable raycasting validation in parallel, it's reasonable to use 64 Actors and more instead of just 4, even if you're targeting 4-core systems. This is valuable for scalability of the system and allows it to distribute the work based on the capability of the underlying hardware. However, you also shouldn't use too many Actors, which are hard to maintain.