Latest  2.0.0 

Homepage  https://github.com/TheArtOfEngineering/Jolt 
License  MIT 
Platforms  ios 8.0, osx 10.9, requires ARC 
Frameworks  Accelerate 
Authors  , 
Swift + Accelerate + Heavy inspiration from Surge
Jolt is a project which was originally a fork of Surge. It has since been spun off into it’s own project due significant API differences. Surge was originally developed during the Swift 1 timeframe, yet Swift has evolved and is continuing to evolve. Therefore, the motivation Jolt was to bring Surge up to date with new Swift features and API Guidelines. Swift’s new API Guidelines are available at swift.org.
Other notable differences
 Jolt is built for both OSX and iOS platforms.
 Jolt can be easily installed with Carthage.

It is possible to create custom generic types that utilize Jolt functions.
struct Plane<T: AccelerateFloatingPoint> { let normal: [T] let distance: T init(normal: [T], point: [T]) { self.normal = T.normalize(normal) self.distance = T.dot(normal, y: point) } init(p1: [T], p2: [T], p3: [T]){ self.normal = T.normalize(T.cross((p2 + p1), y: (p3 + p1))) self.distance = (T.dot(normal, y: p1)) } }
Thank you to Mattt Thompson for the excellent idea of surfacing the Accelerate Framework API and making them Swifty!
Accelerate
Accelerate is a framework that provides highperformance 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.
Because of its relative obscurity and inconvenient APIs, Accelerate is not commonly used by developers… which is a shame, since many applications could benefit from these performance optimizations.
Jolt aims to bring Accelerate to the mainstream, making it as easy (and nearly as fast, in most cases) to perform computation over a set of numbers as for a single member.
Curious about the name Jolt?
The name Jolt is derived from the fact that this project is forked from Surge.
Back in the mid 90’s, Apple, IBM, and Motorola teamed up to create AltiVec (a.k.a the Velocity Engine), which provided a SIMD instruction set for the PowerPC architecture. When Apple made the switch to Intel CPUs, AltiVec was ported to the x86 architecture and rechristened Accelerate. The derivative of Accelerate (and second derivative of Velocity) is known as either jerk, jolt, surge, or lurch, hence the name of this library.
If it’s a derivative of Surge, why didn’t I call it Jounce or Snap?
Well because those are silly.
Disclaimer: Accelerate is not a silver bullet. Under certain conditions, such as performing simple calculations over a small data set, Accelerate can be outperformed by conventional algorithms. Always benchmark to determine the performance characteristics of each potential approach.
Performance
Initial benchmarks on iOS devices and the iOS simulator indicate significant performance improvements over a conventional Swift implementation.
import Jolt
let numbers: [Double] = ...
var sum: Double = 0.0
// Naïve Swift Implementation
sum = reduce(numbers, 0.0, +)
// Jolt Implementations
sum = Jolt.sum(numbers)
sum = numbers.sum()
(Time in seconds, Optimization Level Fast, Whole Module Optimization
)
Operation  n  Swift  Surge  Δ 

sum  100,000,000  0.055  0.112  ~0.5x 
sin  100,000,000  7.803  1.946  ~4x 
exp  100,000,000  6.406  1.427  ~4.5x 
Jolt’s performance characteristics have not yet been thoroughly evaluated, though initial benchmarks show some promise. If anything, a comparison with the original benchmarks from Surge demonstrate just how far the Swift optimizer has come.
Installation
Jolt is Carthage compatible. To install add the following to your Cartfile.
github "TheArtOfEngineering/Jolt"
For additional info on Carthage installation please visit https://github.com/Carthage/Carthage.
Inventory
Jolt functions are named according to their corresponding "Math.h" functions, where applicable (omitting
f
andd
affixes, since type information is communicated and enforced by the language’s type system).
Arithmetic
sum
asum
max
min
mean
meamg
measq
add
mul
div
mod
remainder
sqrt
Auxilliary
abs
ceil
copysign
floor
rec
round
trunc
Exponential
exp
exp2
log
log2
log10
logb
FFT
fft
Hyperbolic
sinh
cosh
tanh
asinh
acosh
atanh
Matrix
add
mul
inv
transpose
Power
pow
Trigonometric
sincos
sin
cos
tan
asin
acos
atan
rad2deg
deg2rad
Usage
Computing Sum of [Double]
import Jolt
let n = [1.0, 2.0, 3.0, 4.0, 5.0]
let sum = n.sum() // 15.0
Computing Product of Two [Double]
s
import Jolt
let a = [1.0, 3.0, 5.0, 7.0]
let b = [2.0, 4.0, 6.0, 8.0]
let product = a * b // [2.0, 12.0, 30.0, 56.0]
License
Jolt is available under the MIT license. See the LICENSE file for more info.
Latest podspec
{ "name": "Jolt", "version": "2.0.0", "license": "MIT", "summary": "Swift + Accelerate + A shameless fork from Surge", "homepage": "https://github.com/TheArtOfEngineering/Jolt", "authors": { "Mattt Thompson": "[email protected]", "Tyler Cloutier": "[email protected]" }, "source": { "git": "https://github.com/TheArtOfEngineering/Jolt.git", "tag": "2.0.0" }, "platforms": { "ios": "8.0", "osx": "10.9" }, "source_files": "Source/*.swift", "frameworks": "Accelerate", "requires_arc": true }
Sun, 06 Mar 2016 03:02:03 +0000