Is there a way to render stereoscopic (left/right) images in a 2d plane that resides in a swiftUI view? I know this is possible in realityKit shaders, and in immersive metal composits, but is it possible via swiftUI shaders, CAMetalLayer, etc? I'd like to draw a 2d window with standard UI chrome (resize, move etc) that displays stereoscopic content on the flat plane of the window.

I'm currently learning Metal. While reading the reference, I came across a strange description. Page 78 in Version 4 Reference (2025-10-25) says: It is legal to call the following set_indices functions to set the indices if the position in the index buffer is valid and if the position in the index buffer is a multiple of 2 (uchar2 overload) or 2 (uchar4 overload). The index I needs to be in the range [0, max_indices). void set_indices(uint I, uchar2 v); void set_indices(uint I, uchar4 v); However, it seems that the uchar4 overload should be multiple of 4. Furthermore, there is no explanation of what these methods actually do. I believe it involves setting two to four consecutive indices at once, but there is no mention of that here. I would like to know if the above understanding is correct.

In my project I need to do the following: In runtime create metal Dynamic library from source. In runtime create metal Executable library from source and Link it with my previous created Dynamic library. Create compute pipeline using those two libraries created above. But I get the following error at the third step: Error Domain=AGXMetalG15X_M1 Code=2 "Undefined symbols: _Z5noisev, referenced from: OnTheFlyKernel " UserInfo={NSLocalizedDescription=Undefined symbols: _Z5noisev, referenced from: OnTheFlyKernel } import Foundation import Metal class MetalShaderCompiler { let device = MTLCreateSystemDefaultDevice()! var pipeline: MTLComputePipelineState! func compileDylib() -> MTLDynamicLibrary { let source = """ #include <metal_stdlib> using namespace metal; half3 noise() { return half3(1, 0, 1); } """ let option = MTLCompileOptions() option.libraryType = .dynamic option.installName = "@executable_path/libFoundation.metallib" let library = try! device.makeLibrary(source: source, options: option) let dylib = try! device.makeDynamicLibrary(library: library) return dylib } func compileExlib(dylib: MTLDynamicLibrary) -> MTLLibrary { let source = """ #include <metal_stdlib> using namespace metal; extern half3 noise(); kernel void OnTheFlyKernel(texture2d<half, access::read> src [[texture(0)]], texture2d<half, access::write> dst [[texture(1)]], ushort2 gid [[thread_position_in_grid]]) { half4 rgba = src.read(gid); rgba.rgb += noise(); dst.write(rgba, gid); } """ let option = MTLCompileOptions() option.libraryType = .executable option.libraries = [dylib] let library = try! self.device.makeLibrary(source: source, options: option) return library } func runtime() { let dylib = self.compileDylib() let exlib = self.compileExlib(dylib: dylib) let pipelineDescriptor = MTLComputePipelineDescriptor() pipelineDescriptor.computeFunction = exlib.makeFunction(name: "OnTheFlyKernel") pipelineDescriptor.preloadedLibraries = [dylib] pipeline = try! device.makeComputePipelineState(descriptor: pipelineDescriptor, options: .bindingInfo, reflection: nil) } }

Hello All, I’m working on a computer-vision–heavy iOS application that uses the camera, LiDAR depth maps, and semantic segmentation to reason about the environment (object identification, localization and measurement - not just visualization). Current architecture I initially built the image pipeline around CIImage as a unifying abstraction. It seemed like a good idea because: CIImage integrates cleanly with Vision, ARKit, AVFoundation, Metal, Core Graphics, etc. It provides a rich set of out-of-the-box transforms and filters. It is immutable and thread-safe, which significantly simplified concurrency in a multi-queue pipeline. The LiDAR depth maps, semantic segmentation masks, etc. were treated as CIImages, with conversion to CVPixelBuffer or MTLTexture only at the edges when required. Problem I’ve run into cases where Core Image transformations do not preserve numeric fidelity for non-visual data. Example: Rendering a CIImage-backed segmentation mask into a larger CVPixelBuffer can cause label values to change in predictable but incorrect ways. This occurs even when: using nearest-neighbor sampling disabling color management (workingColorSpace / outputColorSpace = NSNull) applying identity or simple affine transforms I’ve confirmed via controlled tests that: Metal → CVPixelBuffer paths preserve values correctly CIImage → CVPixelBuffer paths can introduce value changes when resampling or expanding the render target This makes CIImage unsafe as a source of numeric truth for segmentation masks and depth-based logic, even though it works well for visualization, and I should have realized this much sooner. Direction I’m considering I’m now considering refactoring toward more intent-based abstractions instead of a single image type, for example: Visual images: CIImage (camera frames, overlays, debugging, UI) Scalar fields: depth / confidence maps backed by CVPixelBuffer + Metal Label maps: segmentation masks backed by integer-preserving buffers (no interpolation, no transforms) In this model, CIImage would still be used extensively — but primarily for visualization and perceptual processing, not as the container for numerically sensitive data. Thread safety concern One of the original advantages of CIImage was that it is thread-safe by design, and that was my biggest incentive. For CVPixelBuffer / MTLTexture–backed data, I’m considering enforcing thread safety explicitly via: Swift Concurrency (actor-owned data, explicit ownership) Questions For those may have experience with CV / AR / imaging-heavy iOS apps, I was hoping to know the following: Is this separation of image intent (visual vs numeric vs categorical) a reasonable architectural direction? Do you generally keep CIImage at the heart of your pipeline, or push it to the edges (visualization only)? How do you manage thread safety and ownership when working heavily with CVPixelBuffer and Metal? Using actor-based abstractions, GCD, or adhoc? Are there any best practices or gotchas around using Core Image with depth maps or segmentation masks that I should be aware of? I’d really appreciate any guidance or experience-based advice. I suspect I’ve hit a boundary of Core Image’s design, and I’m trying to refactor in a way that doesn't involve too much immediate tech debt, remains robust and maintainable long-term. Thank you in advance!

Hello developers, i have a project for SSC that includes metal shader code. The project runs fine when I build and run it in Xcode, but it does not run in the Swift Playground app. The reason is that Swift Playgrounds doesn’t compile/build source files with the .metal extension the same way Xcode does (so the shader never gets built/loaded in Playgrounds). The requirements say: “Your app playground must be built with and run on Swift Playgrounds 4.6 or Xcode 26, or later.” Since it says “or” (not “and”), does that mean it’s acceptable if the project only builds/runs in Xcode?

Unable to find intelgpu_kbl_gt2r0 slice or a compatible one in binary archive 'file:///System/Library/PrivateFrameworks/IconRendering.framework/Resources/binary.metallib' available slices: applegpu_g13g, applegpu_g13s, applegpu_g13d, applegpu_g14g, applegpu_g14s, applegpu_g14d, applegpu_g15g, applegpu_g15s, applegpu_g15d, applegpu_g16g, applegpu_g16s, applegpu_g17g, applegpu_g15g, applegpu_g15s, applegpu_g15d, applegpu_g16s Is it related to performance of applications in macOS 26.2 on Intel Macs?

Hi. I'm a 3D designer, using Blender for most of my work. The most recent Blender conference discussed utilizing the Open Shading Language (OSL) in their latest versions, which allows designers to write custom shaders for their workflows. At the moment, only Nvidia Optix GPU's can utilize this language for rendering (from what I understand), but Blender developers stated they are waiting on other GPU manufacturers to implement this feature as well. I'm not sure if there are any licensing issues here, but would this be something Apple could implement in Metal to make their hardware more attractive to the 3D design community? Any help or knowledge on this topic would be greatly appreciated.

I’m attempting to install the Metal toolchain in Xcode, but the installation keeps hanging. Through Xcode, it stops at the “Processing” step, and via the terminal, it never goes past “Beginning asset download…”.

Hi everyone, I’ve been developing a custom, end-to-end 3D rendering engine called Crescent from scratch using C++20 and Metal-cpp (targeting macOS and visionOS). My primary goal is to build a zero-bottleneck, GPU-driven pipeline that maximizes the potential of Apple Silicon’s Unified Memory and TBDR architecture. While the fundamental systems are stable, I am looking for architectural feedback from Metal framework engineers regarding specific synchronization and latency challenges. Current Core Implementations: GPU-Driven Instance Culling: High-performance occlusion culling using a Hierarchical Z-Buffer (HZB) approach via Compute Shaders. Clustered Forward Shading: Support for high-count dynamic lights through view-space clustering. Temporal Stability: Custom TAA with history rejection and Motion Blur resolve. Asset Infrastructure: Robust GUID-based scene serialization and a JSON-driven ECS hierarchy. The Architectural Challenge: I am currently seeing slight synchronization overhead when generating the HZB mip-chain. On Apple Silicon, I am evaluating the cost of encoder transitions versus cache-friendly barriers. && m_hzbInitPipeline && m_hzbDownsamplePipeline && !m_hzbMipViews.empty(); if (canBuildHzb) { MTL::ComputeCommandEncoder* hzbInit = commandBuffer->computeCommandEncoder(); hzbInit->setComputePipelineState(m_hzbInitPipeline); hzbInit->setTexture(m_depthTexture, 0); hzbInit->setTexture(m_hzbMipViews[0], 1); if (m_pointClampSampler) { hzbInit->setSamplerState(m_pointClampSampler, 0); } else if (m_linearClampSampler) { hzbInit->setSamplerState(m_linearClampSampler, 0); } const uint32_t hzbWidth = m_hzbMipViews[0]->width(); const uint32_t hzbHeight = m_hzbMipViews[0]->height(); const uint32_t threads = 8; MTL::Size tgSize = MTL::Size(threads, threads, 1); MTL::Size gridSize = MTL::Size((hzbWidth + threads - 1) / threads * threads, (hzbHeight + threads - 1) / threads * threads, 1); hzbInit->dispatchThreads(gridSize, tgSize); hzbInit->endEncoding(); for (size_t mip = 1; mip < m_hzbMipViews.size(); ++mip) { MTL::Texture* src = m_hzbMipViews[mip - 1]; MTL::Texture* dst = m_hzbMipViews[mip]; if (!src || !dst) { continue; } MTL::ComputeCommandEncoder* downEncoder = commandBuffer->computeCommandEncoder(); downEncoder->setComputePipelineState(m_hzbDownsamplePipeline); downEncoder->setTexture(src, 0); downEncoder->setTexture(dst, 1); const uint32_t mipWidth = dst->width(); const uint32_t mipHeight = dst->height(); MTL::Size downGrid = MTL::Size((mipWidth + threads - 1) / threads * threads, (mipHeight + threads - 1) / threads * threads, 1); downEncoder->dispatchThreads(downGrid, tgSize); downEncoder->endEncoding(); } if (m_instanceCullHzbPipeline) { dispatchInstanceCulling(m_instanceCullHzbPipeline, true); } } My Questions: Encoder Synchronization: Would you recommend moving this loop into a single ComputeCommandEncoder using MTLBarrier between dispatches to maintain L2 cache residency, or is the overhead of separate encoders negligible for depth-downsampling on TBDR? visionOS Bindless Latency: For stereo rendering on visionOS, what are the best practices for managing MTL4ArgumentTable updates at 90Hz+? I want to ensure that updating bindless resources for each eye doesn't introduce unnecessary CPU-to-GPU latency. Memory Management: Are there specific hints for Memoryless textures that could be applied to intermediate HZB levels to save bandwidth during this process? I’ve attached a screenshot of a scene rendered with the engine (PBR, SSR, and IBL).

Code is download from apple official metal4 sample [https://developer.apple.com/documentation/metal/drawing-a-triangle-with-metal-4?language=objc] enable metal gpu trace in macOS schema and trace a frame in Xcode. Xcode may show segment fault on App from some 'GTTrace' function when click trace button. When replay a .gputrace file, Xcode may crash , throw an internal error or a XPC error. The example code using old metal-renderer can trace without any problem and everything works fine. Test Environment: Xcode Version 26.2 (17C52) macOS 26.2 (25C56) M1 Pro 16GB A2442

Hello, I have some confusion regarding ResidencySet. Specifically, about the requestResidency() function: how often should we call it? I have a captureOutput(_:didOutput:from:) method that is triggered at 60 or 120 fps. Inside this method, I am calling the following code every frame: computeResidencySet.removeAllAllocations() сomputeResidencySet.addAllocation(TextureA) computeResidencySet.addAllocation(TextureB) computeResidencySet.addAllocation(TextureC) computeResidencySet.commit() computeResidencySet.requestResidency() // Should we call it every frame? Please keep in mind that TextureA, TextureB, and TextureC are unique for each call (new instances are provided on every frame)."

We’ve encountered what appears to be a CoreML regression between macOS 26.0.1 and macOS 26.1 Beta. In macOS 26.0.1, CoreML models run and produce correct results. However, in macOS 26.1 Beta, the same models produce scrambled or corrupted outputs, suggesting that tensor memory is being read or written incorrectly. The behavior is consistent with a low-level stride or pointer arithmetic issue — for example, using 16-bit strides on 32-bit data or other mismatches in tensor layout handling. Reproduction Install ON1 Photo RAW 2026 or ON1 Resize 2026 on macOS 26.0.1. Use the newest Highest Quality resize model, which is Stable Diffusion–based and runs through CoreML. Observe correct, high-quality results. Upgrade to macOS 26.1 Beta and run the same operation again. The output becomes visually scrambled or corrupted. We are also seeing similar issues with another Stable Diffusion UNet model that previously worked correctly on macOS 26.0.1. This suggests the regression may affect multiple diffusion-style architectures, likely due to a change in CoreML’s tensor stride, layout computation, or memory alignment between these versions. Notes The affected models are exported using standard CoreML conversion pipelines. No custom operators or third-party CoreML runtime layers are used. The issue reproduces consistently across multiple machines. It would be helpful to know if there were changes to CoreML’s tensor layout, precision handling, or MLCompute backend between macOS 26.0.1 and 26.1 Beta, or if this is a known regression in the current beta.

[CRITICAL] Metal API Memory Leak - Heap Memory Never Released to OS (CWE-400) Security Classification This issue constitutes a resource exhaustion vulnerability (CWE-400): Aspect Details Type Uncontrolled Resource Consumption CWE CWE-400 Vector Local (any Metal application) Impact System instability, denial of service User Control None - no mitigation available Recovery Requires application restart Summary Metal heap allocations are never released back to macOS, even when the memory is entirely unused. This causes continuous, unbounded memory growth until system instability or crash. The issue affects any application using Metal API heap allocation. This was discovered in Unreal Engine 5, but reproduces in a completely blank UE5 project with zero application code - confirming this is Metal framework behavior, not application-level. Environment OS: macOS Tahoe 26.2 Hardware: Apple Silicon M4 Max (also reproduced on M1, M2, M3) API: Metal Reproduction Steps Run any Metal application that allocates and deallocates GPU buffers via Metal heaps Open Activity Monitor and observe the application's memory usage Let the application run idle (no user interaction required) Observe memory growing continuously at ~1-2 MB per second Memory never plateaus or stabilizes Eventually system becomes unstable For testing: Any Unreal Engine 5.4+ project on macOS will reproduce this. Even a blank project with no gameplay code exhibits the leak. (Tested on UE 5.7.1) Observed Behavior Memory Analysis Using Unreal's memreport -full command, two reports taken 86 seconds apart: Metric Report 1 (183s) Report 2 (269s) Delta Process Physical 4373.64 MB 4463.39 MB +89.75 MB Metal Heap Buffer 7168 MB 8192 MB +1024 MB Unused Heap 3453 MB 4477 MB +1024 MB Object Count 73,840 73,840 0 (no change) Key Finding Metal Heap grew by exactly 1 GB while "Unused Heap" also grew by 1 GB. This demonstrates: Metal is allocating new heap blocks in ~1 GB increments Previously allocated heap memory becomes "unused" but is never released The unused memory accumulates indefinitely No application-level objects are leaking (count remains constant) Memory Growth Pattern Continuous growth while idle (no user interaction) Growth rate: approximately 1-2 MB per second No plateau or stabilization occurs Metal allocates new 1 GB heap blocks rather than reusing freed space Eventually leads to system instability and crash What is NOT Causing This We verified the following are NOT the source: Application objects - Object count remains constant Application code - Blank project with no code reproduces the issue Texture streaming - Disabling texture streaming had no effect CPU garbage collection - Running GC has no effect (this is GPU memory) Mitigations Attempted (None Worked) setPurgeableState Setting resources to purgeable state before release: [buffer setPurgeableState:MTLPurgeableStateEmpty]; Result: Metal ignores this hint and does not reclaim heap memory. Avoiding Heap Pooling Forcing individual buffer allocations instead of heap-based pooling. Result: Leak persists - Metal still manages underlying allocations. Aggressive Buffer Compaction Attempting to compact/defragment buffers within heaps every frame. Result: Only moves data between existing heaps. Does NOT release heaps back to OS. Reducing Pool Sizes Minimizing all buffer pool sizes to force more frequent reuse. Result: Slightly slows the leak rate but does not stop it. Root Cause Analysis How Metal Heap Allocation Appears to Work Metal allocates GPU heap blocks in large chunks (~1 GB observed) Application requests buffers from these heaps When application releases buffers, memory becomes "unused" within the heap Metal does NOT release heap blocks back to macOS, even when entirely unused When fragmentation prevents reuse, Metal allocates new heap blocks Result: Continuous memory growth with no upper bound The Core Problem There appears to be no Metal API to force heap memory release. The only way to reclaim this memory is to destroy the Metal device entirely, which requires restarting the application. Expected Behavior Metal should: Release unused heaps - When a heap block is entirely unused, release it back to macOS Respect purgeable hints - Honor setPurgeableState calls from applications Compact allocations - Defragment heap allocations to reduce fragmentation Provide control APIs - Allow applications to request heap compaction or release Enforce limits - Have configurable maximum heap memory consumption Security Implications Local Denial of Service - Any Metal application can exhaust system memory, causing instability affecting all running applications Memory Pressure Attack - Forces other applications to swap to disk, degrading system-wide performance No Upper Bound - Memory consumption continues until system failure Unmitigable - End users have no way to prevent or limit the leak Affects All Metal Apps - Any application using Metal heaps is potentially affected Impact Applications become unstable after extended use System-wide performance degrades as memory pressure increases Users must periodically restart applications Developers cannot work around this at the application level Long-running applications (games, creative tools, servers) are particularly affected Request Investigate Metal heap memory management behavior Implement heap release when blocks become entirely unused Honor setPurgeableState hints from applications Consider providing an API for applications to request heap compaction Document any intended behavior or workarounds Additional Notes This issue has been observed across multiple Unreal Engine versions (5.4, 5.7) and multiple Apple Silicon generations (M1 through M4). The behavior is consistent and reproducible. The Unreal Engine team has implemented various CVars to attempt mitigation (rhi.Metal.HeapBufferBytesToCompact, rhi.Metal.ResourcePurgeInPool, etc.) but none successfully address the issue because the root cause is at the Metal framework level. Tested: January 2026 Platform: macOS Tahoe 26.2, Apple Silicon (M1/M2/M3/M4)

When building our project for Mac Catalyst with Xcode 26.2, we get this warning almost a hundred times, once for every object file: directory not found for option '-L/var/run/com.apple.security.cryptexd/mnt/com.apple.MobileAsset.MetalToolchain-v17.3.48.0.UZtKea/Metal.xctoolchain/usr/lib/swift/maccatalyst' Somehow, every Link <FileName>.o build step got the following parameter, regardless if the target contained Metal files or not: -L/var/run/com.apple.security.cryptexd/mnt/com.apple.MobileAsset.MetalToolchain-v17.3.48.0.UZtKea/Metal.xctoolchain/usr/lib/swift/maccatalyst The toolchain is mounted at this point, but the directory usr/lib/swift/maccatalyst doesn't exist. When building the project for iOS, the option doesn't exist and the warning is not shown. We already check the build settings, but we couldn't find a reason why the linker is trying to link against the toolchain here. Even for targets that do contain Metal files, we get the following linker warning: search path '/var/run/com.apple.security.cryptexd/mnt/com.apple.MobileAsset.MetalToolchain-v17.3.48.0.UZtKea/Metal.xctoolchain/usr/lib/swift/maccatalyst' not found Is this a known issue? Is there a way to get rid of these warnings?

Hi! I'd like to share a technical sample app, SKRenderer Demo. This app demonstrates: Setting up SKRenderer Recording SpriteKit scenes to image sequences Recording SpriteKit scenes to video using IOSurface and AVFoundation Applying Core Image filters Exploring SpriteKit's simulation timing and physics determinism Use Case Record SpriteKit simulations as video or images for sharing and creating content. I explored several approaches, including the excellent view.texture(from:crop:) for live recording from SKView. The SKRenderer approach assumes recording happens asynchronously: you capture user interactions as commands during live interaction, then replay those commands through an offline render pass to generate the final output. I hope this helps others working on replay systems, simulation capture, or SpriteKit projects in general!

I am developing a custom app for Apple Vision Pro using Compositor Services to stream content from NVIDIA Omniverse. The app is based on: https://github.com/NVIDIA-Omniverse/apple-configurator-sample Environment: Device: Apple Vision Pro OS Version: visionOS 26.2 Xcode Version: 26.2 The Issue: The application crashes hard (__abort_with_payload) in "libsystem_kernel.dylib" on Task 6 immediately after initialization. This appears to be a deliberate abort triggered by the compositor, not a typical crash. The issue occurs on both physical device and simulator. Important detail: The console output shows a specific CLIENT BUG assertion. By checking the metadata of the warning, I found that it is related to "Library: CompositorNonUI". Relevant console output before abort: Missed 'FrameLimiter' target of 90.0 Hz running compositor services to get IPD, FOV, etc fence tx observer 14f27 timed out after 0.600000 fence tx observer bc1b timed out after 0.600000 BUG IN CLIENT: For mixed reality experiences please use cp_drawable_compute_projection API

My goal is to print a debug message from a shader. I follow the guide that orders to set -fmetal-enable-logging metal compiler flag and following environment variables: MTL_LOG_LEVEL=MTLLogLevelDebug MTL_LOG_BUFFER_SIZE=2048 MTL_LOG_TO_STDERR=1 However there's an issue with the guide, it's only covers Xcode project setup, however I'm working on a Swift Package. It has a Metal-only target that's included into main target like this: targets: [ // A separate target for shaders. .target( name: "MetalShaders", resources: [ .process("Metal") ], plugins: [ // https://github.com/schwa/MetalCompilerPlugin .plugin(name: "MetalCompilerPlugin", package: "MetalCompilerPlugin") ] ), // Main target .target( name: "MegApp", dependencies: ["MetalShaders"] ), .testTarget( name: "MegAppTests", dependencies: [ "MegApp", "MetalShaders", ] ] So to apply compiler flag I use MetalCompilerPlugin which emits debug.metallib, it also allows to define DEBUG macro for shaders. This code compiles: #ifdef DEBUG logger.log_error("Hello There!"); os_log_default.log_debug("Hello thread: %d", gid); // this proves that code exectutes result.flag = true; #endif Environment is set via .xctestplan and valideted to work with ProcessInfo. However, nothing is printed to Xcode console nor to Console app. In attempt to fix it I'm trying to setup a MTLLogState, however the makeLogState(descriptor:) fails with error: if #available(iOS 18.0, *) { let logDescriptor = MTLLogStateDescriptor() logDescriptor.level = .debug logDescriptor.bufferSize = 2048 // Error Domain=MTLLogStateErrorDomain Code=2 "Cannot create residency set for MTLLogState: (null)" UserInfo={NSLocalizedDescription=Cannot create residency set for MTLLogState: (null)} let logState = try! device.makeLogState(descriptor: logDescriptor) commandBufferDescriptor.logState = logState } Some LLMs suggested that this is connected with Simulator, and truly, I run the tests on simulator. However tests don't want to run on iPhone... I found solution running them on My Mac (Mac Catalyst). Surprisingly descriptor log works there, even without MTLLogState. But the Simulator behaviour seems like a bug...

Hello, As far as I know and in all of my testing there is no way for a user or a developer to change the frame rate of the video output on iPadOS. If you connect an iPad via a USB Hub or a USB to HDMI Adaptor and then connect it to an external monitor it will output at 59.94fps. I have a video app where a user monitors live video at 25fps and 30fps, they often output to an external display and there are times when the external display will stutter due to the mismatch in frame rate, ie. using 25fps and outputting at 59.94fps. I thought it was impossible to change the video output frame rate, then in V3.1 of the Blackmagic Camera App I saw an interesting change in their release notes: ‘Support for HDMI Monitoring at Sensor Rate and Resolution’ This means there is some way to modify it, not sure if this is done via a Private API that Apple has allowed Blackmagic to use. If so, how can we access this or is there a way to enable this that is undocumented? Thanks!

My app has a number of heterogeneous GPU workloads that all run concurrently. Some of these should be executed with the highest priority because the app’s responsiveness depends on them, while others are triggered by file imports and the like which should have a low priority. If this was running on the CPU I’d assign the former User Interactive QoS and the latter Utility QoS. Is there an equivalent to this for GPU work?

I am puzzled by the setAddress(_:attributeStride:index:) of MTL4ArgumentTable. Can anyone please explain what the attributeStride parameter is for? The doc says that it is "The stride between attributes in the buffer." but why? Who uses this for what? On the C++ side in the shaders the stride is determined by the C++ type, as far as I know. What am I missing here? Thanks!