after launching a nearby exoerience on quick look or inside our app, all the user in the group watch sometimes teh model blinking abd becoming transparet...
... just one user hasnt the issue, either the one who launched shareplay or the user who force align the immersive space in front
weird
Delve into the world of graphics and game development. Discuss creating stunning visuals, optimizing game mechanics, and share resources for game developers.
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Hello! I'm currently porting a videogame console emulator to iOS and I'm trying to make the renderer (tested on MacOS) work on iOS as well.
The emulator core is written in C++ and uses metal-cpp for rendering, whereas the iOS frontend is written in Swift with SwiftUI. I have an Objective-C++ bridging header for bridging the Swift and C++ sides.
On the Swift side, I create an MTKView. Inside the MTKView delegate, I run the emulator for 1 video frame and pass it the view's backing layer for it to render the final output image with. The emulator runs and returns, but when it returns I get a crash in Swift land (callstack attached below), inside objc_release, which indicates I'm doing something wrong with memory management.
My bridging interface (ios_driver.h):
#pragma once
#include <Foundation/Foundation.h>
#include <QuartzCore/QuartzCore.h>
void iosCreateEmulator();
void iosRunFrame(CAMetalLayer* layer);
Bridge implementation (ios_driver.mm):
#import <Foundation/Foundation.h>
extern "C" {
#include "ios_driver.h"
}
<...>
#define IOS_EXPORT extern "C" __attribute__((visibility("default")))
std::unique_ptr<Emulator> emulator = nullptr;
IOS_EXPORT void iosCreateEmulator() { ... }
// Runs 1 video frame of the emulator and
IOS_EXPORT void iosRunFrame(CAMetalLayer* layer) {
void* layerBridged = (__bridge void*)layer;
// Pass the CAMetalLayer to the emulator
emulator->getRenderer()->setMTKLayer(layerBridged);
// Runs the emulator for 1 frame and renders the output image using our layer
emulator->runFrame();
}
My MTKView delegate:
class Renderer: NSObject, MTKViewDelegate {
var parent: ContentView
var device: MTLDevice!
init(_ parent: ContentView) {
self.parent = parent
if let device = MTLCreateSystemDefaultDevice() {
self.device = device
}
super.init()
}
func mtkView(_ view: MTKView, drawableSizeWillChange size: CGSize) {}
func draw(in view: MTKView) {
var metalLayer = view.layer as! CAMetalLayer
// Run the emulator for 1 frame & display the output image
iosRunFrame(metalLayer)
}
}
Finally, the emulator's render function that interacts with the layer:
void RendererMTL::setMTKLayer(void* layer) {
metalLayer = (CA::MetalLayer*)layer;
}
void RendererMTL::display() {
CA::MetalDrawable* drawable = metalLayer->nextDrawable();
if (!drawable) {
return;
}
MTL::Texture* texture = drawable->texture();
<rest of rendering follows here using the drawable & its texture>
}
This is the Swift callstack at the time of the crash:
To my understanding, I shouldn't be violating ARC rules as my bridging header uses CAMetalLayer* instead of void* and Swift will automatically account for ARC when passing CoreFoundation objects to Objective-C. However I don't have any other idea as to what might be causing this. I've been trying to debug this code for a couple of days without much success.
If you need more info, the emulator code is also on Github
Metal renderer: https://github.com/wheremyfoodat/Panda3DS/blob/ios/src/core/renderer_mtl/renderer_mtl.cpp#L58-L68
Bridge implementation: https://github.com/wheremyfoodat/Panda3DS/blob/ios/src/ios_driver.mm
Bridging header: https://github.com/wheremyfoodat/Panda3DS/blob/ios/include/ios_driver.h
Any help is more than appreciated. Thank you for your time in advance.
hi
When analyzing our game using Instruments, I've always been confused about the two items "Drawable Present" and "Drawable Presented" in the GPU column. The timing of Drawable Present seems to be when the CPU layer calls commandbuffer:present, rather than when the actual encoding is completed on the GPU. Also, what does drawable presented specifically mean? In our case, when a CPU stall occurs, it appears that the vsync interval changes in the next frame, and a surface that has already been calculated is not displayed. Why is this happening?
Description:
I'm developing an AR effect using SceneKit and applying a transparent material to a face mesh. However, I'm facing an issue where the front faces of the mesh overlap each other, causing incorrect rendering.
Problem:
The front faces of the mesh overlap with each other when transparency is applied.
This causes areas like the cheeks to be visible through the nose, even though they should be occluded.
Expected Behavior: The material should behave as if it were opaque to itself—that is, overlapping front faces should be occluded properly, while still allowing transparency for background elements.
Actual Behavior: The mesh renders its own front faces incorrectly, making parts of the face visible through others when they should be blocked.
What I Have Tried:
testMaterial.writesToDepthBuffer = true
testMaterial.readsFromDepthBuffer = true
Question:
👉 How can I prevent SceneKit's transparent material from rendering overlapping front faces?
👉 Is there a way to force SceneKit to treat its own mesh as opaque for itself while still being transparent to the background?
👉 Does SceneKit support a proper depth pre-pass or an equivalent to Unity’s ZWrite shaders to solve this issue?
Attached screenshots demonstrate the problem visually. Any help would be greatly appreciated! 🚀
Deterministic RNG behaviour across Mac M1 CPU and Metal GPU – BigCrush pass & structural diagnostics
Hello,
I am currently working on a research project under ENINCA Consulting, focused on advanced diagnostic tools for pseudorandom number generators (structural metrics, multi-seed stability, cross-architecture reproducibility, and complementary indicators to TestU01).
To validate this diagnostic framework, I prototyped a small non-linear 64-bit PRNG (not as a goal in itself, but simply as a vehicle to test the methodology).
During these evaluations, I observed something interesting on Apple Silicon (Mac M1):
• bit-exact reproducibility between M1 ARM CPU and M1 Metal GPU,
• full BigCrush pass on both CPU and Metal backends,
• excellent p-values,
• stable behaviour across multiple seeds and runs.
This was not the intended objective, the goal was mainly to validate the diagnostic concepts, but these results raised some questions about deterministic compute behaviour in Metal.
My question: Is there any official guidance on achieving (or expecting) deterministic RNG or compute behaviour across CPU ↔ Metal GPU on Apple Silicon? More specifically:
• Are deterministic compute kernels expected or guaranteed on Metal for scientific workloads?
• Are there recommended patterns or best practices to ensure reproducibility across GPU generations (M1 → M2 → M3 → M4)?
• Are there known Metal features that can introduce non-determinism?
I am not sharing the internal recurrence (this work is proprietary), but I can discuss the high-level diagnostic observations if helpful.
Thank you for any insight, very interested in how the Metal engineering team views deterministic compute patterns on Apple Silicon.
Pascal ENINCA Consulting
Topic:
Graphics & Games
SubTopic:
Metal
Tags:
ML Compute
Metal
Metal Performance Shaders
Apple Silicon
Hi Apple,
In VisionOS, for real-time streaming of large 3D scenes, I plan to create Metal buffers and textures in multiple threads and then use a compute shader on the main thread to copy the Metal resources into RealityKit, minimizing main thread usage. Given that most of RealityKit's default APIs require execution on the main actor (main thread), it is not ideal for streaming data. Is this approach the best way to handle streaming data and real-time rendering?
Thank you very much.
Hi,
I wanted to do something quite simple: Put a box on a wall or on the floor.
My box:
let myBox = ModelEntity(
mesh: .generateBox(size: SIMD3<Float>(0.1, 0.1, 0.01)),
materials: [SimpleMaterial(color: .systemRed, isMetallic: false)],
collisionShape: .generateBox(size: SIMD3<Float>(0.1, 0.1, 0.01)),
mass: 0.0)
For that I used Plane Detection to identify the walls and floor in the room. Then with SpatialTapGesture I was able to retrieve the position where the user is looking and tap.
let position = value.convert(value.location3D, from: .local, to: .scene)
And then positioned my box
myBox.setPosition(position, relativeTo: nil)
When I then tested it I realized that the box was not parallel to the wall but had a slightly inclined angle.
I also realized if I tried to put my box on the wall to my left the box was placed perpendicular to this wall and not placed on it.
After various searches and several attempts I ended up playing with transform.matrix to identify if the plane is wall or a floor, if it was in front of me or on the side and set up a rotation on the box to "place" it on the wall or a floor.
let surfaceTransform = surface.transform.matrix
let surfaceNormal = normalize(surfaceTransform.columns.2.xyz)
let baseRotation = simd_quatf(angle: .pi, axis: SIMD3<Float>(0, 1, 0))
var finalRotation: simd_quatf
if acos(abs(dot(surfaceNormal, SIMD3<Float>(0, 1, 0)))) < 0.3 {
logger.info("Surface: ceiling/floor")
finalRotation = simd_quatf(angle: surfaceNormal.y > 0 ? 0 : .pi, axis: SIMD3<Float>(1, 0, 0))
} else if abs(surfaceNormal.x) > abs(surfaceNormal.z) {
logger.info("Surface: left/right")
finalRotation = simd_quatf(angle: surfaceNormal.x > 0 ? .pi/2 : -.pi/2, axis: SIMD3<Float>(0, 1, 0))
} else {
logger.info("Surface: front/back")
finalRotation = baseRotation
}
Playing with matrices is not really my thing so I don't know if I'm doing it right.
Could you tell me if my tests for the orientation of the walls are correct? During my tests I don't always correctly identify whether the wall is in front or on the side.
Is this generally the right way to do it?
Is there an easier way to do this?
Regards
Tof
https://developer.apple.com/documentation/arkit/arkit_in_ios/specifying_a_lighting_environment_in_ar_quick_look
How can I disable it? or at least use a custom texture that's just black?
I don't see the purpose of having the real-time environment probe that captures IBL, but always add this fake studio IBL that you can't remove...
Topic:
Graphics & Games
SubTopic:
RealityKit
I've been working on Swift game which is not yet launched or available for preview.
The game works in such a way that it has idle CPU while the user is thinking and sustained max CPU and GPU on as many cores as possible when he makes a move.
Rarely, due to OS activity or something else outside of my control (for example when dropping the OS curtain even if for just a bit then remove it), the game or some of its threads are moved to efficiency cores which results in major stuttering which persists precisely until the game is idle again at which point the game is moved back on performance cores - but if the player keeps making moves the stuttering simply won't go away and so I guess compuptation is locked onto efficiency cores.
The issue does not reproduce on MacCatalyst on Intel.
How do I tell Swift to avoid efficiency cores?
BTW Swift and SceneKIT have AMAZING performance especially when compared to others.
Hello Apple team,
I'm working on an iOS AR app using SwiftUI and RealityKit,
and I was wondering if the Cinematic API can be used with a RealityKit scene. I’d like to achieve a shallow depth of field while keeping the 3D asset in focus, and vice versa.
Thanks!
So, I'm done with GPTK and decided to delete it. The only thing I installed was brew -v install apple/apple/game-porting-toolkit and the external libraries from the ditto command. Now, I tried to remove it, but even after
brew remove game-porting-toolkit
brew autoremove
all of the dependencies installed with brew are still there. The most obvious was game-porting-toolkit-compiler, but even after removing this there are so many libraries that are now orphaned and it's just impossible to manually identify those. Is there a way or is the easiest way to simply uninstall Homebrew completely and reinstall it again?
We have a macOS app (not yet released, but in use by ourselves), that provides scoreboards for streaming sport events.
Today it is expected, that there are nice animations for goals, etc. We are streaming using NDI, which requires a CVPixelBuffer for each frame.
We currently create these animations using CABasicAnimation, CAAnimation and CAKeyframeAnimation. In addition we use ScreenCaptureKit to generate the frames.
This works fine with 25/30 fps, as long as the window where our animations are performed in is visible. But this is not what it should be. We have a smaller window as main app window and control display performing the animations in reduced size, while the streaming animations need to be in HD format and later maybe in 4K.
When using an offscreen window, the animations are not calculated. We get 1 frame per second or so. So we actually have to connect an external display to the MacBook and open the large windows there. Ugly solution.
Do we use a completely wrong approach? Or is there a way to tell the macOS to perform the animations although it is an offscreen window?
If it cannot work that way, what is an alternative?
RealityKit spatial audio crackles and pops on iOS 26.0 beta 5.
It works correctly on iOS 18.6 and visionOS 26.0 beta 5.
The APIs used are AudioPlaybackController, Entity.prepareAudio, Entity.play
Videos of the expected and observed behavior are attached to the feedback FB19423059.
The audio should be a consistent, repeating sound, but it seems oddly abbreviated and the volume varies unexpectedly.
Thank you for investigating this issue.
Hi everyone,
I'm using the Vision framework’s ImageAestheticsScoresObservation class (https://developer.apple.com/documentation/vision/imageaestheticsscoresobservation).
I noticed that the overallScore returned sometimes gives negative values. Could someone confirm whether the expected range of the score is from -1.0 to 1.0?
The documentation doesn’t explicitly state the possible score range, so I’d appreciate any clarification or insights.
Thanks in advance!
I am using Unity's GameKit to implement a turnbase game.
I want to make a UI in Unity to show all the games I can join.
I tried using
var matches = await GKTurnBasedMatch.LoadMatches();
to get all the open matches.
But it seems that I can only get the matcm related to the current apple account.
Can you help me get all the matches?
ALSO
I used
var match = await GKTurnBasedMatchmakerViewController.Request(request);
to exit the gamecenter interface and start a game (automatic matching, no one was invited)
Another device used
var match = await GKTurnBasedMatch.Find(request);
to find the game, but it did not find the game, but it start a new game (automatic matching).
Can you help me solve these problems?
I have a game built in Unreal Engine 5.6 which uses tilt motion controls to rotate an object. I've restricted the app to only run in portrait for iPhone, and everything works fine, however for iPad I've had a few issues relating to multitasking and I can't seem to solve it.
Forcing the app to portrait only still allows the app to run in landscape mode, but shows black bars either side of the game, and the axes for the motion controls are incorrect. X becomes Y and Y becomes X, and there's no way for my app to know which orientation it is because the container is still technically portrait.
Allowing my game to run in all orientations makes the whole app more presentable, it doesn't add black bars and the game is still functional and I'm able to map the controls correctly because the game knows it's landscape rather than portrait.
The problem with allowing my app to run in landscape mode is if multitasking is enabled on the ipad, you can resize the app to be portrait, and then I run into the same problem again where the game thinks it's portrait mode and all of the axes are wrong again.
I tried getting the true orientation of the device rather than the scene, but the game is intended to be played flat so instead of returning the orientation of the OS the orientation is FaceUp, which doesn't help.
I need to either disable multitasking or find a way of getting the orientation of the OS (not the scene or the device). I haven't found how to get the OS orientation so I've been trying to disable multitasking.
I've got Requires Fullscreen true and UIApplicationSupportsMultipleScreens false in my info.plist but my iPad still seems to allow the window to be resized in landscape view. Opening the IOS workspace of my project Requires Fullscreen is ticked but under that it says "Supports Multiple Windows" and the arrow button next to it takes my to my info.plist values, but no indication of how I can change it.
I'm using Unreal Engine 5.6 and Xcode 16.0. Xcode is old I know, but this version of unreal engine doesn't seem to support any newer.
Create the QRCode
CIFilter<CIBlendWithMask> *f = CIFilter.QRCodeGenerator;
f.message = [@"Message" dataUsingEncoding:NSASCIIStringEncoding];
f.correctionLevel = @"Q"; // increase level
CIImage *qrcode = f.outputImage;
Overlay the icon
CIImage *icon = [CIImage imageWithURL:url];
CGAffineTransform *t = CGAffineTransformMakeTranslation(
(qrcode.extent.width-icon.extent.width)/2.0,
(qrcode.extent.height-icon.extent.height)/2.0);
icon = [icon imageByApplyingTransform:t];
qrcode = [icon imageByCompositingOver:qrcode];
Round off the corners
static dispatch_once_t onceToken;
static CIWarpKernel *k;
dispatch_once(&onceToken, ^ {
k = [CIWarpKernel kernelWithFunctionName:name
fromMetalLibraryData:metalLibData()
error:nil];
});
CGRect iExtent = image.extent;
qrcode = [k applyWithExtent:qrcode.extent
roiCallback:^CGRect(int i, CGRect r) {
return CGRectInset(r, -radius, -radius); }
inputImage:qrcode
arguments:@[[CIVector vectorWithCGRect:qrcode.extent], @(radius)]];
…and this code for the kernel should go in a separate .ci.metal source file:
float2 bend_corners (float4 extent, float s, destination dest)
{
float2 p, dc = dest.coord();
float ratio = 1.0;
// Round lower left corner
p = float2(extent.x+s,extent.y+s);
if (dc.x < p.x && dc.y < p.y) {
float2 d = abs(dc - p);
ratio = min(d.x,d.y)/max(d.x,d.y);
ratio = sqrt(1.0 + ratio*ratio);
return (dc - p)*ratio + p;
}
// Round lower right corner
p = float2(extent.x+extent.z-s, extent.y+s);
if (dc.x > p.x && dc.y < p.y) {
float2 d = abs(dc - p);
ratio = min(d.x,d.y)/max(d.x,d.y);
ratio = sqrt(1.0 + ratio*ratio);
return (dc - p)*ratio + p;
}
// Round upper left corner
p = float2(extent.x+s,extent.y+extent.w-s);
if (dc.x < p.x && dc.y > p.y) {
float2 d = abs(dc - p);
ratio = min(d.x,d.y)/max(d.x,d.y);
ratio = sqrt(1.0 + ratio*ratio);
return (dc - p)*ratio + p;
}
// Round upper right corner
p = float2(extent.x+extent.z-s, extent.y+extent.w-s);
if (dc.x > p.x && dc.y > p.y) {
float2 d = abs(dc - p);
ratio = min(d.x,d.y)/max(d.x,d.y);
ratio = sqrt(1.0 + ratio*ratio);
return (dc - p)*ratio + p;
}
return dc;
}
Hello everyone,
I'm working on a screen recording app using ScreenCaptureKit and I've hit a strange issue. My app records the screen to an .mp4 file, and everything works perfectly until the .captureMicrophone is false
In this case, I get a valid, playable .mp4 file.
However, as soon as I try to enable the microphone by setting streamConfig.captureMicrophone = true, the recording seems to work, but the final .mp4 file is corrupted and cannot be played by QuickTime or any other player. This happens whether capturesAudio (app audio) is on or off.
I've already added the "Privacy - Microphone Usage Description" (NSMicrophoneUsageDescription) to my Info.plist, so I don't think it's a permissions problem.
I have my logic split into a ScreenRecorder class that manages state and a CaptureEngine that handles the SCStream. Here is how I'm configuring my SCStream:
ScreenRecorder.swift
// This is my main SCStreamConfiguration
private var streamConfiguration: SCStreamConfiguration {
var streamConfig = SCStreamConfiguration()
// ... other HDR/preset config ...
// These are the problem properties
streamConfig.capturesAudio = isAudioCaptureEnabled
streamConfig.captureMicrophone = isMicCaptureEnabled // breaks it if true
streamConfig.excludesCurrentProcessAudio = false
streamConfig.showsCursor = false
if let region = selectedRegion, let display = currentDisplay {
// My region/frame logic (works fine)
let regionWidth = Int(region.frame.width)
let regionHeight = Int(region.frame.height)
streamConfig.width = regionWidth * scaleFactor
streamConfig.height = regionHeight * scaleFactor
// ... (sourceRect logic) ...
}
streamConfig.pixelFormat = kCVPixelFormatType_32BGRA
streamConfig.colorSpaceName = CGColorSpace.sRGB
streamConfig.minimumFrameInterval = CMTime(value: 1, timescale: 60)
return streamConfig
}
And here is how I'm setting up the SCRecordingOutput that writes the file:
ScreenRecorder.swift
private func initRecordingOutput(for region: ScreenPickerManager.SelectedRegion) throws {
let screeRecordingOutputURL = try RecordingWorkspace.createScreenRecordingVideoFile(
in: workspaceURL,
sessionIndex: sessionIndex
)
let recordingConfiguration = SCRecordingOutputConfiguration()
recordingConfiguration.outputURL = screeRecordingOutputURL
recordingConfiguration.outputFileType = .mp4
recordingConfiguration.videoCodecType = .hevc
let recordingOutput = SCRecordingOutput(configuration: recordingConfiguration, delegate: self)
self.recordingOutput = recordingOutput
}
Finally, my CaptureEngine adds these to the SCStream:
CaptureEngine.swift
class CaptureEngine: NSObject, @unchecked Sendable {
private(set) var stream: SCStream?
private var streamOutput: CaptureEngineStreamOutput?
// ... (dispatch queues) ...
func startCapture(configuration: SCStreamConfiguration, filter: SCContentFilter, recordingOutput: SCRecordingOutput) async throws {
let streamOutput = CaptureEngineStreamOutput()
self.streamOutput = streamOutput
do {
stream = SCStream(filter: filter, configuration: configuration, delegate: streamOutput)
// Add outputs for raw buffers (not used for file recording)
try stream?.addStreamOutput(streamOutput, type: .screen, sampleHandlerQueue: videoSampleBufferQueue)
try stream?.addStreamOutput(streamOutput, type: .audio, sampleHandlerQueue: audioSampleBufferQueue)
try stream?.addStreamOutput(streamOutput, type: .microphone, sampleHandlerQueue: micSampleBufferQueue)
// Add the file recording output
try stream?.addRecordingOutput(recordingOutput)
try await stream?.startCapture()
} catch {
logger.error("Failed to start capture: \(error.localizedDescription)")
throw error
}
}
// ... (stopCapture, etc.) ...
}
When I had the .captureMicrophone value to be false, I get a perfect .mp4 video playable everywhere, however, when its true, I am getting corrupted video which doesn't play at all :-
Hey everyone, I am currently developing an app in visionOS and using RealityComposerPro create scenes in put in my app.
I have a humanoid model with hair strands, and each strand of hair has an opacity map. However, some reflections are still visible even though the opacity is zero. There are also some weird culling among hair strands (in the left circle) and weird reflections in hair cards (in the right circle).
Here's my settings for the materials.
Since all the hair strands are interconnected with each other, it is hard to decide the drawing order in Xcode, so I am wondering if there's an easier way to handle transparency objects.
Please let me know if you know anything helpful, much appreciated!
Context
I’m deploying large language models on iPhone using llama.cpp. A new iPhone Air (12 GB RAM) reports a Metal MTLDevice.recommendedMaxWorkingSetSize of 8,192 MB, and my attempt to load Llama-2-13B Q4_K (~7.32 GB weights) fails during model initialization.
Environment
Device: iPhone Air (12 GB RAM)
iOS: 26
Xcode: 26.0.1
Build: Metal backend enabled llama.cpp
App runs on device (not Simulator)
What I’m seeing
MTLCreateSystemDefaultDevice().recommendedMaxWorkingSetSize == 8192 MiB
Loading Llama-2-13B Q4_K (7.32 GB) fails to complete. Logs indicate memory pressure / allocation issues consistent with the 8 GB working-set guidance.
Smaller models (e.g., 7B/8B with similar quantization) load and run (8B Q4_K provide around 9 tokens/second decoding speed).
Questions
Is 8,192 MB an expected recommendedMaxWorkingSetSize on a 12 GB iPhone?
What values should I expect on other 2025 devices including iPhone 17 (8 GB RAM) and iPhone 17 Pro (12 GB RAM)
Is it strictly enforced by Metal allocations (heaps/buffers), or advisory for best performance/eviction behavior?
Can a process practically exceed this for long-lived buffers without immediate Jetsam risk?
Any guidance for LLM scenarios near the limit?