axiom-concurrency-profiling

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Use when profiling async/await performance, diagnosing actor contention, or investigating thread pool exhaustion. Covers Swift Concurrency Instruments template, task visualization, actor contention analysis, thread pool debugging.

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NPX Install

npx skill4agent add charleswiltgen/axiom axiom-concurrency-profiling

Concurrency Profiling — Instruments Workflows

Profile and optimize Swift async/await code using Instruments.

When to Use

Use when:
  • UI stutters during async operations
  • Suspecting actor contention
  • Tasks queued but not executing
  • Main thread blocked during async work
  • Need to visualize task execution flow
Don't use when:
  • Issue is pure CPU performance (use Time Profiler)
  • Memory issues unrelated to concurrency (use Allocations)
  • Haven't confirmed concurrency is the bottleneck

Swift Concurrency Template

What It Shows

TrackInformation
Swift TasksTask lifetimes, parent-child relationships
Swift ActorsActor access, contention visualization
Thread StatesBlocked vs running vs suspended

Statistics

  • Running Tasks: Tasks currently executing
  • Alive Tasks: Tasks present at a point in time
  • Total Tasks: Cumulative count created

Color Coding

  • Blue: Task executing
  • Red: Task waiting (contention)
  • Gray: Task suspended (awaiting)

Workflow 1: Diagnose Main Thread Blocking

Symptom: UI freezes, main thread timeline full
  1. Profile with Swift Concurrency template
  2. Look at main thread → "Swift Tasks" lane
  3. Find long blue bars (task executing on main)
  4. Check if work could be offloaded
Solution patterns:
swift
// ❌ Heavy work on MainActor
@MainActor
class ViewModel: ObservableObject {
    func process() {
        let result = heavyComputation()  // Blocks UI
        self.data = result
    }
}

// ✅ Offload heavy work
@MainActor
class ViewModel: ObservableObject {
    func process() async {
        let result = await Task.detached {
            heavyComputation()
        }.value
        self.data = result
    }
}

Workflow 2: Find Actor Contention

Symptom: Tasks serializing unexpectedly, parallel work running sequentially
  1. Enable "Swift Actors" instrument
  2. Look for serialized access patterns
  3. Red = waiting, Blue = executing
  4. High red:blue ratio = contention problem
Solution patterns:
swift
// ❌ All work serialized through actor
actor DataProcessor {
    func process(_ data: Data) -> Result {
        heavyProcessing(data)  // All callers wait
    }
}

// ✅ Mark heavy work as nonisolated
actor DataProcessor {
    nonisolated func process(_ data: Data) -> Result {
        heavyProcessing(data)  // Runs in parallel
    }

    func storeResult(_ result: Result) {
        // Only actor state access serialized
    }
}
More fixes:
  • Split actor into multiple (domain separation)
  • Use Mutex for hot paths (faster than actor hop)
  • Reduce actor scope (fewer isolated properties)

Workflow 3: Thread Pool Exhaustion

Symptom: Tasks queued but not executing, gaps in task execution
Cause: Blocking calls exhaust cooperative pool
  1. Look for gaps in task execution across all threads
  2. Check for blocking primitives
  3. Replace with async equivalents
Common culprits:
swift
// ❌ Blocks cooperative thread
Task {
    semaphore.wait()  // NEVER do this
    // ...
    semaphore.signal()
}

// ❌ Synchronous file I/O in async context
Task {
    let data = Data(contentsOf: fileURL)  // Blocks
}

// ✅ Use async APIs
Task {
    let (data, _) = try await URLSession.shared.data(from: fileURL)
}
Debug flag:
SWIFT_CONCURRENCY_COOPERATIVE_THREAD_BOUNDS=1
Detects unsafe blocking in async context.

Workflow 4: Priority Inversion

Symptom: High-priority task waits for low-priority
  1. Inspect task priorities in Instruments
  2. Follow wait chains
  3. Ensure critical paths use appropriate priority
swift
// ✅ Explicit priority for critical work
Task(priority: .userInitiated) {
    await criticalUIUpdate()
}

Thread Pool Model

Swift uses a cooperative thread pool matching CPU core count:
AspectGCDSwift Concurrency
ThreadsGrows unboundedFixed to core count
BlockingCreates new threadsSuspends, frees thread
DependenciesHiddenRuntime-tracked
Context switchFull kernel switchLightweight continuation
Why blocking is catastrophic:
  • Each blocked thread holds memory + kernel structures
  • Limited threads means blocked = no progress
  • Pool exhaustion deadlocks the app

Quick Checks (Before Profiling)

Run these checks first:
  1. Is work actually async?
    • Look for suspension points (
      await
      )
    • Sync code in async function still blocks
  2. Holding locks across await?
    swift
    // ❌ Deadlock risk
    mutex.withLock {
        await something()  // Never!
    }
  3. Tasks in tight loops?
    swift
    // ❌ Overhead may exceed benefit
    for item in items {
        Task { process(item) }
    }
    
    // ✅ Structured concurrency
    await withTaskGroup(of: Void.self) { group in
        for item in items {
            group.addTask { process(item) }
        }
    }
  4. DispatchSemaphore in async context?
    • Always unsafe — use
      withCheckedContinuation
      instead

Common Issues Summary

IssueSymptom in InstrumentsFix
MainActor overloadLong blue bars on main
Task.detached
,
nonisolated
Actor contentionHigh red:blue ratioSplit actors, use
nonisolated
Thread exhaustionGaps in all threadsRemove blocking calls
Priority inversionHigh-pri waits for low-priCheck task priorities
Too many tasksTask creation overheadUse task groups

Safe vs Unsafe Primitives

Safe with cooperative pool:
  • await
    , actors, task groups
  • os_unfair_lock
    ,
    NSLock
    (short critical sections)
  • Mutex
    (iOS 18+)
Unsafe (violate forward progress):
  • DispatchSemaphore.wait()
  • pthread_cond_wait
  • Sync file/network I/O
  • Thread.sleep()
    in Task

Resources

WWDC: 2022-110350, 2021-10254
Docs: /xcode/improving-app-responsiveness
Skills: axiom-swift-concurrency, axiom-performance-profiling, axiom-synchronization