I'm building a weather map that shows the rain on the map. I'm able to retrieve PNG images that are used as tiles to put onto the map. I then reload all the tiles on the map with each timeframe (tile set for every 10 minutes). I'm able to get the map loaded up and I'm able to place the tiles and reload the data for each time slot. I preload all the PNG data needed for the tiles and store that NSData for them in memory so that they are quick for loading and showing on the map. I have timer's set to reload the overlay with the next set of tiles for each time slot. Giving the view of a moving precipitation map over time (just like you'd see on any weather map.) I have 12 time slots (timestamps) showing every 10 minutes for the past 2 hours. I have it showing each in sequence and then repeating. Over time I get a crash with this error as a Thread 1: signal SIGABRT. Failed to acquire drawable, rendering to temporary texture validateRenderPassDescriptor:782: failed assertion `RenderPass Descriptor Validation MTLRenderPassAttachmentDescriptor MTLStoreActionMultisampleResolve store action at attachment 0 requires resolve texture ' validateRenderPassDescriptor:782: failed assertion `RenderPass Descriptor Validation MTLRenderPassAttachmentDescriptor MTLStoreActionMultisampleResolve store action at attachment 0 requires resolve texture ' Through some searching I've discovered that this seems to be console output from Metal. I assume Metal is used for MapKit to render the overlay tiles? I'm using the same custom overlay where I set the timestamp on it and then tell it to reload. I also reuse the same MKOverlayRenderer as shown here... - (MKOverlayRenderer*)mapView:(MKMapView*)mapView rendererForOverlay:(id<MKOverlay>)overlay { if ([overlay isKindOfClass:[MKTileOverlay class]]) { if (!self.rainRenderer) { self.rainRenderer = [[MKTileOverlayRenderer alloc] initWithTileOverlay:overlay]; self.rainRenderer.alpha = 0.5; } return self.rainRenderer; } return nil; } And here's the function that reloads the overlay... - (void) updateRainFrame { self.currentFrameIndex = (self.currentFrameIndex + 1) % self.timestamps.count; if ((self.currentFrameIndex >= 0) && (self.timestamps.count > self.currentFrameIndex)) { NSLog (@"self.currentFrameIndex = %lu", self.currentFrameIndex); NSString *timestamp = self.timestamps[self.currentFrameIndex]; [self.overlay setTimestamp:timestamp]; [self.rainRenderer reloadData]; } } The time it takes to crash seems arbitrary. Sometimes it's very quick. Less than a minute. But usually it's several minutes. 10 or 20 minutes or more. Feels like some sort of race condition that's occurring. Perhaps ARC is not able to release the images for the tiles quick enough for each overlay reload? That's a wild guess but I think it's something more deeper in Metal as I feel I would see other errors related to memory availability. Some of my searches point to something about MSAA needing to be turned off in Metal to resolve this. However I have no idea how I would do that through MapKit. Any suggestions? Let me know if there is somehow a way to capture more from the crash to give more insight.

I am develop visionOS app. I am now very interested in Metal and Compositor Services, but I have not explored them in depth. I know that Metal has a higher degree of control freedom. I am wondering if using Compositor Services will have fewer functions than RealityKit in AR technology (such as scene reconstruction and understanding, hover effect, etc.).

Just downloaded XCode 26 and I see build fails despite Metal toolchain 26.0 downloaded. What am I missing? cannot execute tool 'metal' due to missing Metal Toolchain; use: xcodebuild -downloadComponent MetalToolchain

Hi, I'm developing a SwiftUI app using RealityKit and ARKit for an AR measuring feature. I’ve noticed that after navigating away from my AR view and performing extensive cleanup (including removing all anchors/entities, pausing the ARSession, and nil-ing out all references), memory usage remains elevated and sometimes grows with repeated AR sessions. Each time I enter and exit the AR view, memory increases The memory does not return to the baseline after cleanup, even though all custom objects are deallocated. Are there best practices beyond what I’ve described to ensure all ARKit/RealityKit resources are released after an AR session?

Hey, I need to know how to use texture mapping for rendering a spectrogram in metal. As I need smoothens the spectrogram. In my current project I am using vertex based approach which results in blocky behaviour between each quad. I need to smooth across each qaud so that It will smoothly gradient over.

Hi everyone, I'm creating an educational App that allows doing computational design in an immersive environment with the Vision Pro. The App is free and can be found here: https://apps.apple.com/us/app/arcade-topology/id6742103633 The problem I have is that the mesh of voxels I currently create use ModelEntity and I recently read that this is horrible for scalability. I already start to see issues when I try to use thousands of voxels. I also read somewhere that I should then take advantage of GPUs and use metal to that end. I was wondering if someone could point me to a tutorial or article that discusses this. In essence, I need to create a 3D voxel mesh, and those voxels have to update their opacity within an iterative loop. Thanks! —Alejandro

Hey, I've been struggling with this for some days now. I am trying to write to a sparse texture in a compute shader. I'm performing the following steps: Set up a sparse heap and create a texture from it Map the whole area of the sparse texture using updateTextureMapping(..) Overwrite every value with the value "4" in a compute shader Blit the texture to a shared buffer Assert that the values in the buffer are "4". I have a minimal example (which is still pretty long unfortunately). It works perfectly when removing the line heapDesc.type = .sparse. What am I missing? I could not find any information that writes to sparse textures are unsupported. Any help would be greatly appreciated. import Metal func sparseTexture64x64Demo() throws { // ── Metal objects guard let device = MTLCreateSystemDefaultDevice() else { throw NSError(domain: "SparseNotSupported", code: -1) } let queue = device.makeCommandQueue()! let lib = device.makeDefaultLibrary()! let pipeline = try device.makeComputePipelineState(function: lib.makeFunction(name: "addOne")!) // ── Texture descriptor let width = 64, height = 64 let format: MTLPixelFormat = .r32Uint // 4 B per texel let desc = MTLTextureDescriptor() desc.textureType = .type2D desc.pixelFormat = format desc.width = width desc.height = height desc.storageMode = .private desc.usage = [.shaderWrite, .shaderRead] // ── Sparse heap let bytesPerTile = device.sparseTileSizeInBytes let meta = device.heapTextureSizeAndAlign(descriptor: desc) let heapBytes = ((bytesPerTile + meta.size + bytesPerTile - 1) / bytesPerTile) * bytesPerTile let heapDesc = MTLHeapDescriptor() heapDesc.type = .sparse heapDesc.storageMode = .private heapDesc.size = heapBytes let heap = device.makeHeap(descriptor: heapDesc)! let tex = heap.makeTexture(descriptor: desc)! // ── CPU buffers let bytesPerPixel = MemoryLayout<UInt32>.stride let rowStride = width * bytesPerPixel let totalBytes = rowStride * height let dstBuf = device.makeBuffer(length: totalBytes, options: .storageModeShared)! let cb = queue.makeCommandBuffer()! let fence = device.makeFence()! // 2. Map the sparse tile, then signal the fence let rse = cb.makeResourceStateCommandEncoder()! rse.updateTextureMapping( tex, mode: .map, region: MTLRegionMake2D(0, 0, width, height), mipLevel: 0, slice: 0) rse.update(fence) // ← capture all work so far rse.endEncoding() let ce = cb.makeComputeCommandEncoder()! ce.waitForFence(fence) ce.setComputePipelineState(pipeline) ce.setTexture(tex, index: 0) let threadsPerTG = MTLSize(width: 8, height: 8, depth: 1) let tgCount = MTLSize(width: (width + 7) / 8, height: (height + 7) / 8, depth: 1) ce.dispatchThreadgroups(tgCount, threadsPerThreadgroup: threadsPerTG) ce.updateFence(fence) ce.endEncoding() // Blit texture into shared buffer let blit = cb.makeBlitCommandEncoder()! blit.waitForFence(fence) blit.copy( from: tex, sourceSlice: 0, sourceLevel: 0, sourceOrigin: MTLOrigin(x: 0, y: 0, z: 0), sourceSize: MTLSize(width: width, height: height, depth: 1), to: dstBuf, destinationOffset: 0, destinationBytesPerRow: rowStride, destinationBytesPerImage: totalBytes) blit.endEncoding() cb.commit() cb.waitUntilCompleted() assert(cb.error == nil, "GPU error: \(String(describing: cb.error))") // ── Verify a few texels let out = dstBuf.contents().bindMemory(to: UInt32.self, capacity: width * height) print("first three texels:", out[0], out[1], out[width]) // 0 1 64 assert(out[0] == 4 && out[1] == 4 && out[width] == 4) } Metal shader: #include <metal_stdlib> using namespace metal; kernel void addOne(texture2d<uint, access::write> tex [[texture(0)]], uint2 gid [[thread_position_in_grid]]) { tex.write(4, gid); }

I'm trying to build an MDLMesh then add normals let mdlMesh = MDLMesh.newBox(withDimensions: SIMD3<Float>(1, 1, 1), segments: SIMD3<UInt32>(2, 2, 2), geometryType: MDLGeometryType.triangles, inwardNormals:false, allocator: allocator) mdlMesh.addNormals(withAttributeNamed: MDLVertexAttributeNormal, creaseThreshold: 0) When I render the mesh, some normals are (0,0,0). I don't know if the problem is in the mesh, or in the conversion to MTKMesh. Is there a way to examine an MDLMesh with the geometry viewer? When I look at the variable values for my mdlMesh I get this: Not too useful. I don't know how to track down the normals. What's the best way to find out where the normals getting broken?

I am building a MacOS desktop app (https://anukari.com) that is using Metal compute to do real-time audio/DSP processing, as I have a problem that is highly parallelizable and too computationally expensive for the CPU. However it seems that the way in which I am using the GPU, even when my app is fully compute-limited, the OS never increases the power/performance state. Because this is a real-time audio synthesis application, it's a huge problem to not be able to take advantage of the full clock speeds that the GPU is capable of, because the app can't keep up with real-time. I discovered this issue while profiling the app using Instrument's Metal tracing (and Game tracing) modes. In the profiling configuration under "Metal Application" there is a drop-down to select the "Performance State." If I run the application under Instruments with Performance State set to Maximum, it runs amazingly well, and all my problems go away. For comparison, when I run the app on its own, outside of Instruments, the expensive GPU computation it's doing takes around 2x as long to complete, meaning that the app performs half as well. I've done a ton of work to micro-optimize my Metal compute code, based on every scrap of information from the WWDC videos, etc. A problem I'm running into is that I think that the more efficient I make my code, the less it signals to the OS that I want high GPU clock speeds! I think part of why the OS is confused is that in most use cases, my computation can be done using only a small number of Metal threadgroups. I'm guessing that the OS heuristics see that only a small fraction of the GPU is saturated and fail to scale up the power/clock state. I'm not sure what to do here; I'm in a bit of a bind. One possibility is that I intentionally schedule busy work -- spin threadgroups just to waste energy and signal to the OS that I need higher clock speeds. This is obviously a really bad idea, but it might work. Is there any other (better) way for my app to signal to the OS that it is doing real-time latency-sensitive computation on the GPU and needs the clock speeds to be scaled up? Note that game mode is not really an option, as my app also runs as an AU plugin inside hosts like Garageband, so it can't be made fullscreen, etc.

I made a box with MDLMesh.newBox(). I added normals. let mdlMesh = MDLMesh.newBox(withDimensions: SIMD3<Float>(1, 1, 1), segments: SIMD3<UInt32>(2, 2, 2), geometryType: MDLGeometryType.triangles, inwardNormals:false, allocator: allocator) mdlMesh.addNormals(withAttributeNamed: MDLVertexAttributeNormal, creaseThreshold: 0.25) After I convert to MTKMesh the normals are (0,0,0) for a group of vertices. I can only inspect the geometry after I convert to MTKMesh. Is there a way you can use Geometry Viewer on a MDLMesh?

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?

I am new to Xcode and trying to learn how to use Metal for my internship. I am trying to link the binaries of Foundation.framework, Metal.framework, and Quartcore.framework. But whenever I try to build it always fails to find any of them. I have my Header Search Path as $(PROJECT_DIR)/metal-cpp, I tried adding some for the Frameworks but that did not work either. I do have the binaries linked in the Build Phases, so I don't know what else I could be missing.

In the Creating A 3D Application With Hydra Rendering tutorial on the Apple Developer website, on the last step where I execute this command: cmake -S ~/Users/macuser/CreatingA3DApplicationWithHydraRendering/ -B ~/Users/macuser/CreatingA3DApplicationWithHydraRendering/ I keep getting an error: CMake Error at CMakeLists.txt:5 (include): include could not find requested file: /Users/macuser/USDInstall/bin/pxrConfig.cmake I've tried to follow the instructions as mentioned in the README.md file included in the project files at least 5 times as well as moving the pxrConfig.cmake file around and copying it in different folders, then executed the command and was still unsuccessful into generating the proper file expected to compile and render the HydraPlayer renderer. How do I get cmake to generate the Xcode file to create the HydraPlayer renderer?

I’m trying to follow Apple’s “WWDC24: Bring your machine learning and AI models to Apple Silicon” session to convert the Mistral-7B-Instruct-v0.2 model into a Core ML package, but I’ve run into a roadblock that I can’t seem to overcome. I’ve uploaded my full conversion script here for reference: https://pastebin.com/T7Zchzfc When I run the script, it progresses through tracing and MIL conversion but then fails at the backend_mlprogram stage with this error: https://pastebin.com/fUdEzzKM The core of the error is: ValueError: Op "keyCache_tmp" (op_type: identity) Input x="keyCache" expects list, tensor, or scalar but got state[tensor[1,32,8,2048,128,fp16]] I’ve registered my KV-cache buffers in a StatefulMistralWrapper subclass of nn.Module, matching the keyCache and valueCache state names in my ct.StateType definitions, but Core ML’s backend pass reports the state tensor as an invalid input. I’m using Core ML Tools 8.3.0 on Python 3.9.6, targeting iOS18, and forcing CPU conversion (MPS wasn’t available). Any pointers on how to satisfy the handle_unused_inputs pass or properly declare/cache state for GQA models in Core ML would be greatly appreciated! Thanks in advance for your help, Usman Khan

Hi, seems MSL is missing support for a clock() shader instruction available in other graphics APIs like Vulkan or OpenGL for example.. useful for counting cost in number of clock cycles of some code insider shader with much finer granularity than launching a micro kernel with same instructions and measuring cycles cost from CPU.. also useful for MoltenVK to support that extensions.. thanks..

Hi, Introducing Swift Concurrency to my Metal app has been a bit challenging as Swift Concurrency is limited by the cooperative thread pool. GPU work is obviously not CPU bound and can block forward moving progress, especially when using waitUntilCompleted on the command buffer. For concurrent render work this has the potential of under utilizing the CPU and even creating dead locks. My question is, what is the Metal's teams general recommendation when it comes to concurrency? It seems to me that Dispatch or OperationQueues are still the preferred way for Metal bound tasks in order to gain maximum performance? To integrate with Swift Concurrency my idea is to use continuations that kick off render jobs via Dispatch or Queues? Would this be the best solution to bridge async tasks with Metal work? Thanks!

Starting with iOS 18.0 beta 1, I've noticed that RealityKit frequently crashes in the simulator when an app launches and presents an ARView. I was able to create a small sample app with repro steps that demonstrates the issue, and I've submitted feedback: FB16144085 I've included a crash log with the feedback. If possible, I'd appreciate it if an Apple engineer could investigate and suggest a workaround. It's awkward to be restricted to the iOS 17 simulator, which does not exhibit this behavior. Please let me know if there's anything I can do to help. Thank you.

I am trying to achieve an animated gradient effect that changes values over time based on the current seconds. I am also using AVPlayer and AVMutableVideoComposition along with custom instruction and class to generate the effect. I didn't want to load any video file, but rather generate a custom video with my own set of instructions. I used Metal Compute shaders to generate the effects and make the video to be 20 seconds. However, when I run the code, I get a frozen player with the gradient applied, but when I try to play the video, I get this warning in the console :- Visual isTranslatable: NO; reason: observation failure: noObservations Here is the screenshot :- My entire code :- import AVFoundation import Metal class GradientVideoCompositorTest: NSObject, AVVideoCompositing { var sourcePixelBufferAttributes: [String: Any]? = [ kCVPixelBufferPixelFormatTypeKey as String: kCVPixelFormatType_32BGRA ] var requiredPixelBufferAttributesForRenderContext: [String: Any] = [ kCVPixelBufferPixelFormatTypeKey as String: kCVPixelFormatType_32BGRA ] private var renderContext: AVVideoCompositionRenderContext? private var metalDevice: MTLDevice! private var metalCommandQueue: MTLCommandQueue! private var metalLibrary: MTLLibrary! private var metalPipeline: MTLComputePipelineState! override init() { super.init() setupMetal() } func setupMetal() { guard let device = MTLCreateSystemDefaultDevice(), let queue = device.makeCommandQueue(), let library = try? device.makeDefaultLibrary(), let function = library.makeFunction(name: "gradientShader") else { fatalError("Metal setup failed") } self.metalDevice = device self.metalCommandQueue = queue self.metalLibrary = library self.metalPipeline = try? device.makeComputePipelineState(function: function) } func renderContextChanged(_ newRenderContext: AVVideoCompositionRenderContext) { renderContext = newRenderContext } func startRequest(_ request: AVAsynchronousVideoCompositionRequest) { guard let outputPixelBuffer = renderContext?.newPixelBuffer(), let metalTexture = createMetalTexture(from: outputPixelBuffer) else { request.finish(with: NSError(domain: "com.example.gradient", code: -1, userInfo: nil)) return } var time = Float(request.compositionTime.seconds) renderGradient(to: metalTexture, time: time) request.finish(withComposedVideoFrame: outputPixelBuffer) } private func createMetalTexture(from pixelBuffer: CVPixelBuffer) -> MTLTexture? { var texture: MTLTexture? let width = CVPixelBufferGetWidth(pixelBuffer) let height = CVPixelBufferGetHeight(pixelBuffer) let textureDescriptor = MTLTextureDescriptor.texture2DDescriptor( pixelFormat: .bgra8Unorm, width: width, height: height, mipmapped: false ) textureDescriptor.usage = [.shaderWrite, .shaderRead] CVPixelBufferLockBaseAddress(pixelBuffer, .readOnly) if let textureCache = createTextureCache(), let cvTexture = createCVMetalTexture(from: pixelBuffer, cache: textureCache) { texture = CVMetalTextureGetTexture(cvTexture) } CVPixelBufferUnlockBaseAddress(pixelBuffer, .readOnly) return texture } private func renderGradient(to texture: MTLTexture, time: Float) { guard let commandBuffer = metalCommandQueue.makeCommandBuffer(), let commandEncoder = commandBuffer.makeComputeCommandEncoder() else { return } commandEncoder.setComputePipelineState(metalPipeline) commandEncoder.setTexture(texture, index: 0) var mutableTime = time commandEncoder.setBytes(&mutableTime, length: MemoryLayout<Float>.size, index: 0) let threadsPerGroup = MTLSize(width: 16, height: 16, depth: 1) let threadGroups = MTLSize( width: (texture.width + 15) / 16, height: (texture.height + 15) / 16, depth: 1 ) commandEncoder.dispatchThreadgroups(threadGroups, threadsPerThreadgroup: threadsPerGroup) commandEncoder.endEncoding() commandBuffer.commit() } private func createTextureCache() -> CVMetalTextureCache? { var cache: CVMetalTextureCache? CVMetalTextureCacheCreate(kCFAllocatorDefault, nil, metalDevice, nil, &cache) return cache } private func createCVMetalTexture(from pixelBuffer: CVPixelBuffer, cache: CVMetalTextureCache) -> CVMetalTexture? { var cvTexture: CVMetalTexture? let width = CVPixelBufferGetWidth(pixelBuffer) let height = CVPixelBufferGetHeight(pixelBuffer) CVMetalTextureCacheCreateTextureFromImage( kCFAllocatorDefault, cache, pixelBuffer, nil, .bgra8Unorm, width, height, 0, &cvTexture ) return cvTexture } } class GradientCompositionInstructionTest: NSObject, AVVideoCompositionInstructionProtocol { var timeRange: CMTimeRange var enablePostProcessing: Bool = true var containsTweening: Bool = true var requiredSourceTrackIDs: [NSValue]? = nil var passthroughTrackID: CMPersistentTrackID = kCMPersistentTrackID_Invalid init(timeRange: CMTimeRange) { self.timeRange = timeRange } } func createGradientVideoComposition(duration: CMTime, size: CGSize) -> AVMutableVideoComposition { let composition = AVMutableComposition() let instruction = GradientCompositionInstructionTest(timeRange: CMTimeRange(start: .zero, duration: duration)) let videoComposition = AVMutableVideoComposition() videoComposition.customVideoCompositorClass = GradientVideoCompositorTest.self videoComposition.renderSize = size videoComposition.frameDuration = CMTime(value: 1, timescale: 30) // 30 FPS videoComposition.instructions = [instruction] return videoComposition } #include <metal_stdlib> using namespace metal; kernel void gradientShader(texture2d<float, access::write> output [[texture(0)]], constant float &time [[buffer(0)]], uint2 id [[thread_position_in_grid]]) { float2 uv = float2(id) / float2(output.get_width(), output.get_height()); // Animated colors based on time float3 color1 = float3(sin(time) * 0.8 + 0.1, 0.6, 1.0); float3 color2 = float3(0.12, 0.99, cos(time) * 0.9 + 0.3); // Linear interpolation for gradient float3 gradientColor = mix(color1, color2, uv.y); output.write(float4(gradientColor, 1.0), id); }

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.

Hello I am trying to get thread group memory access in fragment shader. In essence, I would like to have all the fragments in a tile to bitwiseOR some value. My idea was to use simd_or across the SIMD group, then make each SIMD group thread 0 to atomic or the value into thread group memory. Finally very first thread of the tile would be tasked with writing the value down to texture with write access. Now, I can allocate the thread group memory argument to the fragment function all right. MTLRenderEncoder has setThreadgroupMemoryLength call, which I am using the following way [renderEncoder setThreagroupMemoryLength: 16 offset: 0 atIndex:0] Unfortunately, all I am getting is the following error (runtime assertion) -[MTLDebugRenderCommandEncoder setThreadgroupMemoryLength:offset:atIndex:]:3487: failed assertion Set Threadgroup Memory Length Validation offset + length(16) must be <= threadgroupMemoryLength(0).` What I am doing wrong? How I can get thread group memory in the fragment shader? I know I could use tile shading and compute function but the problem is that here I really like to use fragment stuff. Will be grateful for help.