Igor Skvortsov

Igor Skvortsov/Article - Swift Inline Array

Created Tue, 17 Jun 2025 00:00:00 +0000 Modified Tue, 08 Jul 2025 22:46:24 +0000
3733 Words 17 min
Swift Array MemoryManagement

InlineArray brings stack-speed performance to Swift collections—without sacrificing the elegance of Array.

Illustration

1. Introduction

Why Should You Care About InlineArray?

In most Swift projects, you typically reach for the good old Array. It’s flexible, easy to use, and fits almost every situation—until you start hitting the wall of heap allocations, unpredictable performance, and memory fragmentation.

That’s where InlineArray comes in. This is a fixed-size array type where the first N elements are stored directly inside the structure itself. No heap, no extra noise. And if you outgrow it? It seamlessly switches to heap-backed storage and behaves like a regular array.

Think of InlineArray<Element, N> as an Array with a turbo boost, tailor-made for small collections where speed, stability, and predictability matter most.

1.3 Quick Overview

InlineArray<Element, N> is a generic, fixed-size structure. The Element specifies the type of the items, and the integer literal N tells the compiler how many items to reserve right inside the structure. Because the capacity is known at compile-time, the compiler can optimize access patterns and memory layout.

Under the Hood

In a regular Array, all elements are stored in a separate memory block on the heap. That means malloc and free calls every time the array grows or is deallocated. In contrast, InlineArray stores the first N elements directly inside its own memory (usually on the stack for locals), eliminating the need for heap allocation.

When the number of elements exceeds N, InlineArray switches to dynamic storage: it allocates a heap buffer, copies the inline values over, and continues working like a standard array. This fallback is seamless and safe.

Why InlineArray Matters

  • Fewer allocations. For collections up to size N, there’s no heap allocation. That’s a huge win in real-time or low-latency apps like games or audio/video processing.
  • Better cache locality. Elements live right next to the metadata, making CPU cache hits more likely.
  • Predictable performance. No surprise heap allocations means your code behaves consistently.
  • Less heap fragmentation. Inline storage means fewer tiny objects in the heap, reducing strain on ARC.
  • Safety. Since N is a compile-time constant, the compiler can catch overflows before they happen.

Where InlineArray Shines

  • Real-time scenarios. Low-latency operations without malloc delays.
  • Interfacing with C/C++/Objective-C. You can pass fixed-size buffers without redundant copying.
  • Rendering and graphics. Great for vertex buffers in Metal or shader params in SwiftUI.
  • Networking. Ideal for headers or protocol fields with known size.

In short, InlineArray gives you the best of both worlds: the flexibility of Array and the performance of stack-allocated buffers—all within the comfort of Swift’s familiar API.

2. Background and Motivation

When Swift 1.0 was released, it brought along a shiny new Array type to replace Objective-C’s NSMutableArray. With its clean syntax and built-in safety checks, Array quickly became the go-to tool for storing collections in Swift. But underneath the ergonomic surface lurked a performance cost: every single element was stored on the heap.

Each append, remove, or resizing operation could potentially trigger a memory allocation or copy. For large arrays, that’s expected. But for small, short-lived collections? It feels like using a freight train to deliver a pizza.

To address this, Apple introduced ContiguousArray, a variant of Array that guaranteed elements are laid out contiguously in memory. It offered better cache performance but still relied on heap allocation, which meant it couldn’t fully solve the problems of unpredictable latency, fragmentation, or allocation overhead.

That left a gap—a need for a more lightweight, predictable way to store small collections without hitting the heap.

Enter Swift Evolution Proposal SE-0453, authored by Alejandro Alonso. It proposed a generic type: InlineArray<Element, N>, where N is a compile-time constant representing the number of elements to store inline. As long as you stay under N, all operations (appending, removing, reading) happen directly in the structure’s built-in storage. Once you cross that boundary, InlineArray promotes itself to use a heap buffer, copying over the existing data.

Why This Is a Big Deal

  • Fewer allocations. For collections of size ≤ N, you avoid the overhead of dynamic memory.
  • Denser cache usage. Inline elements and metadata live close together in memory, increasing cache hit rates.
  • Stable latency. Eliminating surprise allocations means better real-time performance for audio, video, games, etc.
  • Less fragmentation. With fewer small heap allocations, ARC and the memory system breathe easier.

What Problems Does InlineArray Solve?

  • Frequent heap allocations that introduce jitter or slowdowns.
  • Memory fragmentation that hurts performance and ARC efficiency.
  • Poor cache locality due to scattered memory blocks.
  • Unpredictable performance in real-time systems.

With InlineArray, you get an Array-like experience that’s supercharged for small datasets. It’s ergonomic, familiar, and ready for performance-critical code where predictability is key.

📎 Read the full Swift Evolution Proposal SE-0453

3. Syntax and Declaration

Getting started with InlineArray in Swift is straightforward. It’s a generic type, and you declare it just like any other generic collection:

var buffer: InlineArray<Int, 4>

Here, Int is the type of elements you want to store, and 4 is the maximum number of items that will be stored inline—meaning directly inside the structure itself, without heap allocation.

This declaration tells the compiler to reserve space for 4 integers right within the structure. If you’re working with a local variable, this buffer typically lives on the stack. If it’s a property on a struct or class, it resides inside the object’s memory. As long as you don’t exceed N, all read/write operations happen without touching the heap.

How to Initialize

You’ve got several ways to create an InlineArray, and they feel very natural if you’re used to Array:

  1. Array literal — the cleanest way to define a set of values inline:
let letters: InlineArray<String, 3> = ["A", "B", "C"]

All three values are stored in the inline buffer.

  1. Initializer from a sequence:
let numbers = InlineArray([1, 2, 3, 4, 5]) as InlineArray<Int, 4>

The first four integers live in the inline buffer. The fifth value? It automatically triggers a heap allocation.

  1. Empty initializer:
var data = InlineArray<Double, 2>()

Start empty and fill it up later.

Adding and Removing Elements

You add elements the usual way using append(_:):

var data = InlineArray<Double, 2>()
data.append(3.14)
data.append(2.71)

No heap is touched yet. But add a third one:

data.append(1.62) // This causes a one-time heap allocation

Once that happens, InlineArray switches to dynamic storage. From that point on, it behaves just like a regular Array.

Project Requirements

  • Swift 6.2 or later
  • Xcode 15.0+

No extra dependencies or libraries are needed. InlineArray is part of the Swift standard library. So if you’re on a recent version of Swift, you’re already set to use it.

4. Memory Layout and Performance Optimization

To really appreciate what makes InlineArray special, it helps to understand how it’s laid out in memory.

When you declare InlineArray<Element, N>, the compiler reserves space for exactly N elements, along with a counter to track how many are currently stored. For local variables, this memory typically lives on the stack. For properties on structs or classes, it’s part of the object’s memory footprint.

As long as you’re within the N element limit, all reads and writes go directly into this reserved memory area using fixed offsets. Here’s why that matters:

  • No heap allocations. Initialization, append, and removal happen without touching dynamic memory.
  • Cache-friendly layout. Data and metadata (like the count) sit next to each other, improving cache hits.
  • Consistent performance. No surprise malloc or free calls means predictable behavior—great for real-time scenarios.

But what happens when you cross the N element threshold?

That’s when InlineArray performs a one-time promotion: it allocates a dynamic buffer on the heap, copies over the existing values, and appends the new element. From there, it continues operating like a traditional Array.

Example:

var coords = InlineArray<CGPoint, 3>([.zero, .init(x: 1, y: 1)])
coords.append(.init(x: 2, y: 2)) // still inline
coords.append(.init(x: 3, y: 3)) // fills the inline buffer
coords.append(.init(x: 4, y: 4)) // triggers heap allocation and copy

You can imagine the internal structure like this:

struct InlineArrayHeader {
    var count: UInt8
    var storage: (T, T, ...)   // N elements inline
    var heapPointer: UnsafeMutablePointer<T>?  // nil until overflow
}

Until you exceed N, everything lives in inlineStorage. Go beyond that, and it transitions to heapStorage.

What the Benchmarks Say

Apple’s tests from WWDC 2025 Session 312 show that for small collections (up to 8–16 elements), InlineArray can:

  1. Cut buffer creation and teardown time by up to 3x compared to Array.
  2. Reduce memory usage by 30–40%, thanks to skipping heap allocation.
  3. Stabilize operation latency, which is crucial in systems where timing matters (games, audio, video).

Once the collection grows well past N, performance trends toward that of regular Array. But for anything within the inline range, the gains are significant.

⚠️ Element-Type Matters

Don’t forget that not all element types behave the same under the hood.

  • Trivial value types (Int, Float, plain-old-data structs) get memcpy’d in and out of the inline buffer with zero extra cost—exactly where InlineArray shines.
  • Reference-counted types (String, classes, existential Any) trigger ARC retain/release on every copy of the array. If you pack these into InlineArray, you’ll likely see your allocation savings eaten up (or even turned into a net slowdown) by all the extra ARC traffic.

InlineArray is proof that sometimes, small is mighty.

5. Interoperability with C and Objective-C

One of the standout advantages of InlineArray is how smoothly it interoperates with low-level C and Objective-C APIs—all without unnecessary data copying.

Because the inline buffer lives directly inside the structure, you can pass its pointer straight into C functions that expect a raw buffer, minimizing overhead.

Passing to C APIs

When you need to call a C function that takes an UnsafeBufferPointer, you can simply use the withUnsafeBufferPointer method:

func processPoints(_ points: UnsafeBufferPointer<CGPoint>)

var coords: InlineArray<CGPoint, 4> = [.zero, .init(x: 1, y: 1), .init(x: 2, y: 2)]
coords.withUnsafeBufferPointer { buffer in
    processPoints(buffer)
}

In this example, Swift provides the pointer to the inline buffer without copying the data to the heap.

⚠️ Just a word of caution: when you hand off a raw pointer like this, you must ensure the data stays valid during the lifetime of the pointer. If you mutate or deallocate the array during that time, undefined behavior can occur. This is highlighted in detail in WWDC 2025 Session 312.

Bridging to Objective-C APIs

Objective-C methods often expect an NSArray or NSData. For NSData, you can create a zero-copy bridge using NSData(bytesNoCopy:length:freeWhenDone:):

let rawArray: InlineArray<UInt8, 8> = [0x01, 0x02, 0x03]
let data = rawArray.withUnsafeBufferPointer { buffer in
    return NSData(bytesNoCopy: UnsafeMutableRawPointer(mutating: buffer.baseAddress!), length: buffer.count, freeWhenDone: false)
}
// You can now pass `data` into Objective-C methods without copying

Under the hood, Swift marks InlineArray with internal semantics like @_semantics("cArray") to let the runtime know it represents a contiguous buffer. That helps maintain correct lifetime management even when used across ARC and C runtime boundaries.

This level of interop makes InlineArray a great fit for performance-critical systems where allocation overhead is unacceptable—think audio/video engines, networking stacks, or rendering pipelines.

🔗 Watch WWDC 2025 Session 312 for an in-depth demo of safely bridging Swift data to C APIs, including the use of Span<Element> for efficient, copy-free buffer access.

6. Generics and InlineArray

One of the most elegant aspects of InlineArray is how seamlessly it plugs into Swift’s generics ecosystem. Thanks to its conformance to Sequence, Collection, and MutableCollection, you can use familiar high-level APIs like map, filter, and reduce right out of the box—with zero friction.

Functional Goodness

Here’s an example using map to square each number:

let numbers: InlineArray<Int, 5> = [1, 2, 3]
let squares = numbers.map { $0 * $0 }   // InlineArray<Int, 5>

Because the resulting collection also fits within the inline capacity (N = 5), there are no heap allocations for either numbers or squares.

Same goes for filter:

let evens = numbers.filter { $0.isMultiple(of: 2) }  // InlineArray<Int, 5>

Extensions and Algorithms

Since InlineArray conforms to RandomAccessCollection, you can extend its functionality through generic extensions just like with Array:

extension RandomAccessCollection where Element: Comparable {
    func median() -> Element? {
        guard !isEmpty else { return nil }
        let sorted = self.sorted()
        return sorted[count / 2]
    }
}

let data: InlineArray<Double, 7> = [3.1, 4.2, 1.5, 2.6]
let med = data.median()  // 2.6

This function operates entirely within the inline buffer (inlineStorage) as long as the collection stays within the size limit, ensuring fast, cache-friendly operations.

Mind the Heap

A quick heads-up: operations that conform to RangeReplaceableCollection, like insert(contentsOf:), may cause an inline buffer overflow. That triggers a one-time transition to heap-backed storage. So in generic code, it’s wise to anticipate how large your collection might grow and choose an appropriate value for N.

Takeaways

Using generics with InlineArray feels almost indistinguishable from working with Array. But under the hood, you’re getting serious performance benefits when your data stays within the inline bounds. That makes InlineArray a smart tool for crafting predictable, high-performance algorithms without sacrificing the expressiveness of Swift.

7. Embedding InlineArray into iOS Systems and Frameworks

One of the best things about InlineArray is how easily it fits into iOS frameworks like SwiftUI, Metal, and Core Graphics. You get real performance benefits without re-architecting your entire app.

SwiftUI and ForEach

In SwiftUI, you often use collections to render dynamic content. A typical use case looks like this:

struct PointsView: View {
    var points: InlineArray<CGPoint, 8>

    var body: some View {
        ForEach(points.indices, id: \.
            self.points[index].x
        ) { index in
            Circle()
                .position(points[index])
        }
    }
}

Here, points.indices returns a range without triggering extra allocations. Accessing elements by index is just as fast as with a regular array, but you benefit from InlineArray’s stack storage when under capacity.

Metal and Core Graphics

When working with GPU code, it’s all about speed and minimal allocations. Vertex buffers, for example, often consist of a small, fixed number of elements. With InlineArray, you can prepare input data and pass a direct pointer to the inline buffer:

let vertices: InlineArray<Vertex, 16> = [...]
let vertexBuffer = device.makeBuffer(
    bytes: vertices.withUnsafeBufferPointer { $0.baseAddress! },
    length: MemoryLayout<Vertex>.stride * vertices.count
)

Because you’re using the inline buffer directly, there’s no intermediate copy—the GPU receives data straight from your structure.

Codable and Serialization

If you’re encoding or decoding small, fixed-size collections, InlineArray works just like a regular array with Codable. The decoder knows the inline capacity and allocates memory accordingly, avoiding redundant reallocations:

struct Payload: Codable {
    var header: InlineArray<UInt8, 4>
    var values: InlineArray<Double, 10>
}

During decoding, Swift fills the inline buffers directly. If you exceed the capacity, it gracefully switches to heap-backed storage.

The Bottom Line

With InlineArray, you can optimize performance-critical paths in your SwiftUI, Metal, and networking code with minimal changes. It acts like a regular array but saves you heap allocations when it counts. For mobile apps, where CPU time and memory are precious, this can make a real impact.

8. Under the Hood: How the Compiler Handles InlineArray

To truly understand how InlineArray delivers its performance benefits, we need to peek behind the curtain at how Swift compiles and optimizes it. This chapter walks through the compilation process step-by-step.

8.1 Parsing and AST Generation

When you write something like:

var buffer: InlineArray<Int, 4>

Swift’s parser turns this into an Abstract Syntax Tree (AST), a hierarchical structure that captures the shape and meaning of your code. Here, the AST encodes that you’re working with a generic type InlineArray where the element type is Intand the inline capacity is 4. This gives the compiler enough context to reason about size, memory layout, and type behavior early on.

8.2 SIL: Swift Intermediate Language

Next, the AST is lowered into SIL (Swift Intermediate Language). SIL is a high-level, SSA-based representation that lets the compiler analyze and optimize your code before lowering it further. At this stage:

  • InlineArray<Element, N> is modeled as a struct with an inline storage tuple for N elements and an optional pointer to a heap buffer.
  • Calls like append and indexed access are broken down into simpler SIL instructions.
  • Capacity checks and conditional branching (“are we still within inline capacity?”) are made explicit.

Because N is known at compile time, SIL can specialize the code—inlining functions, removing checks, and reducing runtime overhead.

8.3 LLVM IR and Optimizations

From SIL, the compiler generates LLVM Intermediate Representation (IR), which is much closer to machine code. Here, InlineArray might be lowered to something like:

%InlineArray = type { i32 /*count*/, [N x Element], Element* /*heapPtr*/ }

LLVM then runs aggressive optimizations:

  • Dead code elimination. If a heap fallback is never triggered, that code path is removed.
  • Load/store simplifications. Fixed-size arrays mean access offsets are predictable.
  • Inlining and loop unrolling. Loops over small InlineArrays are often fully unrolled.

All of this leads to tight, fast machine code that behaves consistently.

8.4 Runtime Metadata and Reflection

To support Swift features like introspection, debugging, and tools like SwiftUI previews or Playgrounds, the compiler also emits metadata for InlineArray. This includes:

  • The actual value of N (capacity).
  • Alignment and size information for Element.
  • Descriptions of methods like append, removeLast, and the initializer.

This metadata ensures runtime tools can understand and interact with InlineArray, even if its storage model is more complex than a regular array.

Peeking Inside: Developer Tools

Want to see all this magic for yourself? Swift gives you tools to inspect intermediate representations:

# View SIL (Swift Intermediate Language)
swiftc -emit-sil MyFile.swift

# View LLVM IR (Low-level Intermediate Representation)
swiftc -emit-ir MyFile.swift
  • SIL shows how operations like append or subscript access break down.
  • LLVM IR shows the underlying memory layout and which optimizations kicked in.

By exploring these outputs, you can better understand how your code translates into performance—and even catch unexpected heap promotions or optimization misses.

⚠️ InlineArray isn’t just a syntactic feature. It’s a low-level performance tool, and the compiler plays a key role in unlocking its full power. From AST to runtime, Swift carefully tracks inline capacity and specializes code paths to keep things fast and memory-efficient.

9. Best Practices and Common Pitfalls

InlineArray is a powerful tool for optimizing small collections, but like all low-level performance features, it requires thoughtful use. In this section, we’ll look at when it’s a great fit, when to avoid it, and how to debug issues effectively.

When to Use (and When Not To)

✅ Use **InlineArray** when:

  • You know the max size is small and predictable. If your collection never grows beyond a few dozen elements, InlineArray helps you skip heap allocations.
  • You create and discard the collection frequently. This is common in real-time scenarios like UI rendering, audio processing, or frame updates in games.
  • Latency is a concern. No surprise malloc calls means smoother response times.

🚫 Avoid **InlineArray** when:

  • Collection size can vary dramatically. Frequent overflows into heap storage negate the benefits.
  • You choose a very large **N**. Inline buffers that are too big can blow up stack usage or object size, hurting performance.
  • You need complex mutation. Frequent inserts/removals in the middle of the array may be better served by Arrayor another data structure.
// ✅ Ideal usage
func renderPoints(_ pts: InlineArray<CGPoint, 8>) {
    // Fast, stack-friendly rendering
}

// 🚫 Problematic if collection size varies a lot
var dynamicPoints = InlineArray<CGPoint, 4>()
for point in stream {
    dynamicPoints.append(point) // triggers heap fallback repeatedly
}

Common Pitfalls

  • Inline buffer overflow. Adding an element beyond N triggers heap allocation. This transition is seamless, but can cause performance spikes if it happens often.
  • Poor choice of **N**. Too small? Frequent heap promotions. Too large? Stack overflow risk.
// 🚨 Danger: Huge inline buffer on the stack
var largeInline: InlineArray<Int, 1024> = []
  • Alignment issues. For complex types (like SIMD vectors), memory alignment can cause padding inside the buffer. If you access the buffer as raw memory, misalignment can lead to bugs:
struct Vec16 { var data: (Float, Float, ..., Float) }
var vecs: InlineArray<Vec16, 2> = [...] // memory layout may be padded

Debugging and Diagnostics

🧰 Here are some tools and techniques to help you catch and fix issues:

  1. Compiler warnings. Swift warns you if N isn’t a compile-time constant or is too large. Use this to sanity-check your choices.
-Xfrontend -debug-inlining
  1. Sanitizers. Enable AddressSanitizer and ThreadSanitizer in your Xcode scheme:
-sanitize=address
-sanitize=thread

These catch out-of-bounds accesses and threading issues early.

  1. Runtime assertions. Accessing an invalid index triggers a preconditionFailure with details. Watch for these in logs.
  2. Intermediate code inspection. You can dump SIL or LLVM IR to analyze when inline storage is used vs. when heap fallback occurs:
swiftc -Xllvm -sil-print-inline -emit-sil MyFile.swift
  1. Custom logging. You can override append to log when heap fallback happens:
extension InlineArray {
    mutating func append(_ newElement: Element) {
        if count == N {
            print("[InlineArray] Switching to heap-backed storage, N=\(N)")
        }
        // Original append logic
    }
}
  1. Profile ARC overhead. If you store reference-types (classes, String, existential Any), don’t just measure allocation speed—measure retain/release cost too:
var refArray = InlineArray<MyClass, 4>()
let start = CFAbsoluteTimeGetCurrent()

for _ in 0..<100_000 {
    refArray.append(MyClass())
    refArray.removeLast()
}

let end = CFAbsoluteTimeGetCurrent()
print("Time with ARC traffic: \(end - start) seconds")

That loop reveals if ARC calls eat your inline-buffer gains. If they do, stick with a normal Array for reference-heavy workloads.

This helps you profile how often you hit the inline capacity limit.

Summary

Used wisely, InlineArray is a fantastic performance tool. Just be aware of its limits. Choose N carefully, avoid unpredictable growth, and leverage the right tooling to monitor your usage. That way, you can enjoy the speed without the surprises.

10. Conclusion

InlineArray might look like a small addition to Swift’s standard library, but its impact on performance-critical code can be profound. It brings together the predictability of stack allocation with the flexibility of dynamic storage, offering a hybrid model that’s especially powerful for small, frequently-used collections.

Used thoughtfully, it helps eliminate unnecessary heap allocations, reduce memory fragmentation, and improve cache locality—all while using familiar, expressive Swift syntax.

To get the most out of InlineArray:

  • Choose the right value for N. Think of it as a performance budget.
  • Understand your data’s growth patterns.
  • Monitor fallback to heap storage with tools and logging.

And perhaps most importantly: measure. Inline arrays won’t replace regular arrays across the board, but in the right places, they offer a tangible boost in speed and consistency.

In the world of Swift, where ergonomics often take the front seat, InlineArray is a rare case of low-level control done right. It gives you just enough power to write fast code—without giving up the elegance that makes Swift such a joy to use.