Having the ability to run duties in parallel is good, it could pace up issues for certain when you’ll be able to make the most of a number of CPU cores, however how can we truly implement these sort of operations in Swift? 🤔

There are a number of methods of working parallel operations, I had an extended article concerning the Grand Central Dispatch (GCD) framework, there I defined the variations between parallelism and concurrency. I additionally demonstrated find out how to arrange serial and concurrent dispatch queues, however this time I would prefer to focus a bit extra on duties, employees and jobs.

Think about that you’ve got an image which is 50000 pixel vast and 20000 pixel lengthy, that is precisely one billion pixels. How would you alter the colour of every pixel? Effectively, we may do that by iterating by every pixel and let one core do the job, or we may run duties in parallel.

The Dispatch framework provides a number of methods to unravel this subject. The primary answer is to make use of the concurrentPerform operate and specify some variety of employees. For the sake of simplicity, I’ll add up the numbers from zero to 1 billion utilizing 8 employees. 💪

```
import Dispatch
let employees: Int = 8
let numbers: [Int] = Array(repeating: 1, depend: 1_000_000_000)
var sum = 0
DispatchQueue.concurrentPerform(iterations: employees) { index in
let begin = index * numbers.depend / employees
let finish = (index + 1) * numbers.depend / employees
print("Employee #(index), objects: (numbers[start..<end].depend)")
sum += numbers[start..<end].cut back(0, +)
}
print("Sum: (sum)")
```

Cool, however nonetheless every employee has to work on numerous numbers, perhaps we should not begin all the employees without delay, however use a pool and run solely a subset of them at a time. That is fairly a simple process with operation queues, let me present you a primary instance. 😎

```
import Basis
let employees: Int = 8
let numbers: [Int] = Array(repeating: 1, depend: 1_000_000_000)
let operationQueue = OperationQueue()
operationQueue.maxConcurrentOperationCount = 4
var sum = 0
for index in 0..<employees {
let operation = BlockOperation {
let begin = index * numbers.depend / employees
let finish = (index + 1) * numbers.depend / employees
print("Employee #(index), objects: (numbers[start..<end].depend)")
sum += numbers[start..<end].cut back(0, +)
}
operationQueue.addOperation(operation)
}
operationQueue.waitUntilAllOperationsAreFinished()
print("Sum: (sum)")
```

Each of the examples are above are extra ore much less good to go (if we glance by at potential information race & synchronization), however they rely upon extra frameworks. In different phrases they’re non-native Swift options. What if we may do one thing higher utilizing structured concurrency?

```
let employees: Int = 8
let numbers: [Int] = Array(repeating: 1, depend: 1_000_000_000)
let sum = await withTaskGroup(of: Int.self) { group in
for i in 0..<employees {
group.addTask {
let begin = i * numbers.depend / employees
let finish = (i + 1) * numbers.depend / employees
return numbers[start..<end].cut back(0, +)
}
}
var abstract = 0
for await consequence in group {
abstract += consequence
}
return abstract
}
print("Sum: (sum)")
```

Through the use of process teams you’ll be able to simply setup the employees and run them in parallel by including a process to the group. Then you’ll be able to look forward to the partial sum outcomes to reach and sum all the pieces up utilizing a thread-safe answer. This strategy is nice, however is it potential to restrict the utmost variety of concurrent operations, identical to we did with operation queues? 🤷♂️

```
func parallelTasks<T>(
iterations: Int,
concurrency: Int,
block: @escaping ((Int) async throws -> T)
) async throws -> [T] {
strive await withThrowingTaskGroup(of: T.self) { group in
var consequence: [T] = []
for i in 0..<iterations {
if i >= concurrency {
if let res = strive await group.subsequent() {
consequence.append(res)
}
}
group.addTask {
strive await block(i)
}
}
for strive await res in group {
consequence.append(res)
}
return consequence
}
}
let employees: Int = 8
let numbers: [Int] = Array(repeating: 1, depend: 1_000_000_000)
let res = strive await parallelTasks(
iterations: employees,
concurrency: 4
) { i in
print(i)
let begin = i * numbers.depend / employees
let finish = (i + 1) * numbers.depend / employees
return numbers[start..<end].cut back(0, +)
}
print("Sum: (res.cut back(0, +))")
```

It’s potential, I made just a little helper operate just like the `concurrentPerform`

methodology, this manner you’ll be able to execute quite a few duties and restrict the extent of concurrency. The primary concept is to run quite a few iterations and when the index reaches the utmost variety of concurrent objects you wait till a piece merchandise finishes and you then add a brand new process to the group. Earlier than you end the duty you additionally must await all of the remaining outcomes and append these outcomes to the grouped consequence array. 😊

That is it for now, I hope this little article will aid you to handle concurrent operations a bit higher.