Upsurge

Accelerate is a framework that provides high-performance functions for matrix math, digital signal processing, and image manipulation. It harnesses SIMD instructions available in modern CPUs to significantly improve performance of certain calculations.

Upsurge is a fork of Surge written in Swift 2.0. Upsurge focuses more on matrix and vector operations. It uses a custom ValueArray class instead of the built-in array. It being a class instead of a struct means that you can manage when and if it gets copied, making memory management more explicit. This also allows defining the += operator to mean addition instead of concatenation.

As opposed to Surge, Upsurge does not support Float. There is a global typealias defining Real as a Double and this single type is used throughout. This is because supporting Float makes the code unnecessarily complicated and in 64-bit achitectures Double is as fast as Float so there is no practial reason to support it.

Installation

Upsurge supports both Cocoapods (pod 'Upsurge') and Carthage (github "aleph7/Upsurge").

Usage

Arrays and vector operations

Upsurge defines the ValueArray class to store a one-dimensional collection of values. But the name you will most likely use is RealArray which is a type alias to ValueArray<Double>. From now on we will refer to it as a RealArray but it all applies to other types of ValueArray.

RealArray is very similar to Swift's Array but it is optimized to reduce unnecessary memory allocation. These are the most important differences:

• Its instances have a fixed size defined on creation. When you create a RealArray you can define a capacity var a = RealArray(capacity: 100) and then append elements up to that capacity. Or you can create it with specific elements var a: RealArray = [1.0, 2.0, 3.0] but then you can't add any more elements after.
• It is a class. That means that creating a new variable will only create a reference and modifying the reference will also modify the original. For instance doing var a: RealArray = [1, 2, 3]; var b = a and then b[0] = 5 will result in a being [5, 2, 3]. If you want to create a copy you need to do var b = RealArray(a) or var b = a.copy().
• You can create an uninitialized RealArray by doing var a = RealArray(capacity: n) or var a = RealArray(count: n). This is good for when you are going to fill up the array yourself. But you can also use var a = RealArray(count: n, repeatedValue: 0.0) if you do want to initialize all the values.

Creating arrays

Create a RealArray with specific literal elements when you know ahead of time what the contents are, and you don't need to add more elements at a later time:

let a: RealArray = [1.0, 3.0, 5.0, 7.0]

Create a RealArray with a capacity and then fill it in when you are loading the contents from an external source or have a very large array:

let a = RealArray(capacity: 100)
for v in intputSource {
    a.append(v)
}

Finally there is a way of initializing both the capacity and the count of a RealArray. You should rarely need this but it's there for when you are doing operations on existing arrays using low-level APIs that take pointers:

func operation(a: RealArray) {
    let N = a.count
    let b = RealArray(count: N)
    vvsqrt(b.mutablePointer, a.pointer, [Int32(N)])
}

Vector arithmetic

You can perform operations on RealArray in an intuitive manner:

let a: RealArray = [1.0, 3.0, 5.0, 7.0]
let b: RealArray = [2.0, 4.0, 6.0, 8.0]
let addition = a + b // [3.0, 7.0, 11.0, 15.0]
let product  = a • b // 100.0

Matrix operations

import Upsurge

let A = RealMatrix([
    [1,  1],
    [1, -1]
])
let C = RealMatrix([
    [3],
    [1]
])

// find B such that A*B=C
let B = inv(A) * C // [2.0, 1.0]′

// Verify result
let r = A*B - C    // zero   

Tensors

The Tensor class makes it easy to manipulate multi-dimensional data. You can easily slice or flatten a tensor to get matrices and vectors that you can operate on.

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License

Upsurge is available under the MIT license. See the LICENSE file for more info.