Training a Neural Network with Metal Performance Shaders

At a glance

Project structure

Source bundle/
├── MPSTrainingClassifier/
│   ├── main.mm
│   ├── MNISTClassifierGraph.h
│   ├── MNISTClassifierGraph.mm
│   └── Controls.h
├── Common/
│   ├── MNISTDataSet.mm
│   ├── DataSources.h
│   ├── DataSources.mm
│   ├── MNISTDataSet.h
│   ├── Helpers.h
│   └── Helpers.mm
├── Configuration/
│   └── SampleCode.xcconfig
└── MPSTrainingHelloWorld.xcodeproj/
    └── .xcodesamplecode.plist

Structure observations

• Architecturally prominent files are ranked from entry points and role-named declarations; resource-only paths are omitted.
• Primary languages: C/Objective-C header, Objective-C++.
• The verified tree contains 3 project/configuration file(s) and 4 source declaration(s).

Overall architecture

flowchart LR
    N1["main"]
    N2["Metal / MetalPerformanceShaders APIs"]
    N1 --> N2

Reference code

MPSTrainingClassifier/main.mm:156 — architecture anchor

int main(int argc, const char * argv[]) {
    // ...
        gDevice = MTLCreateSystemDefaultDevice();
    // ...
}

Interpretation

The arrows summarize the source-visible entry, role-named types or folders, and framework direction; when nodes come from structural folders, the sequence is a high-level interpretation rather than proof that every adjacent node calls the next. Ownership is claimed only where the next section cites a stored property or assignment. The diagram is intentionally limited to the dominant path into Metal Performance Shaders.

Ownership and state

classDiagram
    main --> MetalPerformanceShadersAPIs : uses

Ownership evidence

Common/MNISTDataSet.mm:14 — stored dependency or nearest verified ownership anchor

@interface NSData (gunzip)

- (NSData *)gunzippedData;

@end

Composition arrows indicate a source-visible construction expression or locally owned value state; aggregation means the owner stores or receives a dependency without proving exclusive lifetime ownership.

Concurrency, scheduling, and thread safety

Evidence limit: actor isolation, async/await, or Task creation does not by itself prove background-thread execution; Sendable conformance alone does not prove thread-safe mutation.

No source-visible execution, scheduling, or synchronization boundary was found in the indexed source.

@MainActor/MainActor.run, DispatchQueue.main, and RunLoop.main are reported as distinct isolation, queue, and event-loop mechanisms. A plain Task is kept separate from Task.detached; neither is labeled as a background thread.

State propagation, frameworks, and dependencies

Evidence limit: an import proves a source-level compilation dependency at the cited line; it does not prove runtime use, architectural adoption, or whether a Swift package is a direct application dependency.

receive(on:) describes downstream delivery scheduling, while subscribe(on:) describes upstream subscription/request/cancel scheduling. An import Combine alone establishes neither behavior nor a Store, reducer, Redux, or other application architecture.

Class and protocol design

Common/DataSources.h:34 — representative type boundary

#ifndef DataSources_h
@interface ConvDataSource : NSObject<MPSCNNConvolutionDataSource>{
    // ...
}
@end    /* ConvDataSource */
#endif /* DataSources_h */

No local protocol conformance is claimed as protocol-oriented design; external framework conformances are listed only as dependencies.

Access control

Reference code

Common/DataSources.h:34 — representative boundary

#ifndef DataSources_h
@interface ConvDataSource : NSObject<MPSCNNConvolutionDataSource>{
    // ...
}
@end    /* ConvDataSource */
#endif /* DataSources_h */

Swift declarations without a modifier are internal; explicit private, fileprivate, private(set), public, or open entries above are interpreted by language semantics. Objective-C/C samples instead rely on header and implementation boundaries, which are not equivalent to Swift lexical privacy.

Logic ownership and placement

Design patterns

Main application flow

sequenceDiagram
    participant ConvDataSource
    participant MPSCommandBuffer
    participant _convWtsAndBias
    participant commandBuffer
    ConvDataSource->>MPSCommandBuffer: commandBufferFromCommandQueue()
    ConvDataSource->>_convWtsAndBias: synchronizeOnCommandBuffer()
    ConvDataSource->>commandBuffer: commit()
    ConvDataSource->>commandBuffer: waitUntilCompleted()

Reference code

Common/DataSources.mm:177 — checkpointWithCommandQueue()

-(void) checkpointWithCommandQueue:(nonnull id<MTLCommandQueue>) commandQueue{
    @autoreleasepool{
        MPSCommandBuffer *commandBuffer = [MPSCommandBuffer commandBufferFromCommandQueue:gCommandQueue];
        [_convWtsAndBias synchronizeOnCommandBuffer:commandBuffer];
        [commandBuffer commit];
        [commandBuffer waitUntilCompleted];
    }
}

Naming conventions

• Types: DataSource: ConvDataSource.
• Protocols: no local protocol declaration in the scanned source.
• Methods: gunzippedData, init, getRandomTrainingBatchWithDevice, initWithKernelWidth, dataType, descriptor, weights, biasTerms.
• Files: Common/MNISTDataSet.mm, Common/MNISTDataSet.h, MPSTrainingClassifier/MNISTClassifierGraph.h, MPSTrainingClassifier/MNISTClassifierGraph.mm.

Architecture takeaways

• main is the main source-visible entry or composition anchor for this sample.
• Framework work reaches Metal, MetalPerformanceShaders, random through a deliberately small high-level chain; the detailed API graph remains inside the cited implementation files.
• Stored-property evidence identifies lifecycle collaboration; it does not by itself prove exclusive object ownership.
• Access-control conclusions separate verified language visibility from the likely design rationale.
• The source does not justify labeling the design protocol-oriented.

Source map

• Official Apple documentation