# TryJoinads (II.): Task-based parallelism

The implementation of joinad operations for the `Task<'T>`

type is quite similar to the
implementation of `Async<'T>`

, because the two types have similar properties. They both
produce at most one value (or an exception) and they both take some time to complete.

Just like for asynchronous workflows, pattern matching on multiple computations using
`match!`

gives us a parallel composition (with the two tasks running in parallel) and
choice between clauses is non-deterministic, depending on which clause completes first.

Unlike asynchronous workflows, the `Task<'T>`

type does not require any support for
aliasing. A value of type `Task<'T>`

represents a *running* computation that can be
accessed from multiple parts of program. In this sense, the type `Async<'T>`

is more
similar to a function `unit -> Task<'T>`

than to the type `Task<'T>`

itself.

The key difference between tasks and asynchronous workflows is that the latter provides
better support for writing non-blocking computations that involve *asynchronous*
long-running operations such as I/O or waiting for a certain event. Tasks are more
suitable for high-performance CPU-intensive computations.

**Note:** This blog post is a re-publication of a tutorial from the TryJoinads.org
web page. If you read the article there, you can run the examples interactively
and experiment with them: view the article on TryJoinads.

## Parallel list processing

The main example in this article is a tree processing function that can be used to test whether all values in leafs satisfy a given predicate. However, we'll build the example step-by-step, exploring several other examples along the way.

To generate inputs for testing, we will calculate a list containing several large prime
numbers. We will use functional `map`

and `filter`

combinators, but we first implement
parallel version of `map`

(in practice, this is already available in F# libraries or in
the F# PowerPack, but it is an interesting example
of using joinads:

open System.Threading.Tasks open FSharp.Extensions.Joinads /// Applies the specified function to all /// elements of the input list in parallel. let parallelMap (f:'T -> 'R) input = // Recursively process list and spawn tasks let rec loop input = future { match input with | [] -> return [] | x::xs -> // Process current element & the rest of the list match! future { return f x }, loop xs with | y, ys -> return y::ys } // Start the work and wait until it completes (loop input).Result

The function `parallelMap`

contains a nested recursive function `loop`

that returns
a task, which is processing a part of the list in parallel. The declaration of
`loop`

uses a computation builder `future { ... }`

(which is defined in the
`FSharp.Extensions.Joinads`

namespace).

The `loop`

function uses ordinary `match`

to handle the end of the list. If the
list is non-empty, it uses `match!`

to perform two tasks in parallel:

- First, it runs a computation that evaluates
`f x`

- Second, it recursively calls
`loop xs`

to process the rest of the list

When both computations complete, the body of the clause constructs a list
to be returned. The return type of `loop`

is `Task<list<'T>>`

, so the
body of `parallelMap`

uses the `Result`

property to obtain the processed list.

The following snippet defines a function that tests whether a number is
prime and compares the performance of sequential and parallel `map`

function:

// Create a list containing 1000 big numbers let nums = [ for i in 0L .. 1000L -> i + 5000000000000L ] /// Tests whether the specified 64 bit int is a prime let isPrime num = seq { 2L .. int64 (sqrt (float num)) } |> Seq.forall (fun div -> num % div <> 0L) // Turn on the timing and compare the performance #time List.map isPrime nums parallelMap isPrime nums

When you load the code in F# Interactive, you can select and run the `#time`

directive to enable simple performance measuring. F# Interactive then prints
the result of every entered command, together with the time it took to calculate
it. On the author's machine, the time needed to run the sequential version is
about 8 seconds and the time of the parallel version is about 4.5 seconds.

## Building a ballanced tree

Before we can look at tree processing, we need to define a list type and
we need to write a function for constructing lists. The following snippet shows
a standard binary tree declaration together with a function `ballancedOfList`

that
creates ballanced tree from a non-empty list:

type Tree<'T> = | Leaf of 'T | Node of Tree<'T> * Tree<'T> /// Creates a ballanced tree from a non-empty list /// (odd elements are added to the left and even to the right) let rec ballancedOfList list = match list with | [] -> failwith "Cannot create tree of empty list" | [n] -> Leaf n | _ -> // Split the elements into odd and even using their index let left, right = list |> List.mapi (fun i v -> i, v) |> List.partition (fun (i, v) -> i%2 = 0) // Create ballanced trees for both parts let left, right = List.map snd left, List.map snd right Node(ballancedOfList left, ballancedOfList right)

The function is quite simple and it is only shown to make the sample complete.
We use it to construct two trees that we'll later want to process. The first
tree is generated by taking all primes from the `nums`

list shown earlier and
the other contains several additional non-prime numbers:

// Create a list with large prime numbers let primes = nums |> parallelMap (fun v -> isPrime v, v) |> List.filter fst |> List.map snd // Create a list with some additional non-primes let mixed = primes @ [ 2L .. 20L ] // Created ballanced trees from both lists let primeTree = ballancedOfList primes let mixedTree = ballancedOfList mixed

The `primeTree`

tree contains only large prime numbers, so checking if it
contains only prime numbers will take relatively long. The `mixedTree`

contains
several additional numbers, some of them are not primes. This means that
running `isPrime`

on all of the values would take longer, but if we can
return the result immediately after we find a non-prime, the processing is
likely to complete quite quickly.

## Parallel tree processing

Let's now implement a `forall`

function that takes a tree and a predicate
and tests whether the predicate holds for all leafs. We use the `future { ... }`

computation builder and we use `match!`

to handle the `Node`

case by
checking both sub-trees in parallel:

/// Checks whether the specified predicate 'f' /// holds for all Leaf elements of the tree. let forall f tree = let rec loop tree = future { match tree with | Leaf v -> return f v | Node(left, right) -> // Process left and right branch in parallel match! loop left, loop right with | l, r -> return l && r } // Start the recursive processing & wait for the result (loop tree).Result // Test processing on two sample trees forall isPrime mixedTree forall isPrime primeTree

If you run the processing on both `mixedTree`

and `primeTree`

, they will
take similarly long time to complete. However, a sequential version of
the function would be faster for `mixedTree`

, because it would return
`false`

immediately after finding the first non-prime number.

### Adding short-circuiting

Implementing the same functionality using `Task<'T>`

sounds difficult,
but using joinads, the problem becomes quite simple. We add two additional
clauses that handle the case when one branch completes returning `false`

.

Aside from this simple change, we also need to make sure that all remaining
tasks, which are not required to complete, get cancelled.
The cancellation is implemented by creating a .NET `CancellationTokenSource`

before starting the recursive processing. In the body of `loop`

we then check
if the processing has completed and we throw an exception if it has:

open System.Threading /// Behaves like previous 'forall' function, but returns /// immediately when one of the branches returns 'false' let forall f tree = // Create cancellation token for checking let cts = new CancellationTokenSource() let rec loop tree = future { // Stop processing if the function already returned if cts.Token.IsCancellationRequested then failwith "cancelled" match tree with | Leaf v -> return f v | Node(left, right) -> match! loop left, loop right with | false, ? -> return false | ?, false -> return false | l, r -> return l && r } // Wait for the result & cancel all pending work let res = (loop tree).Result cts.Cancel() res // Processing 'mixedTree' is significanlty faster, // because it returns after first non-prime is found! forall isPrime mixedTree forall isPrime primeTree

The changes required to implement short-circuiting are quite small. As already
mentioned, we added two clauses with patterns `false, ?`

and `?, false`

. These
will match when one of the computation completes and returns `false`

while the
other is still running. When that happens, the function `loop`

can return the
final result, but the other task may still continue running.

To actually save CPU power, we need to cancel the other task. This is done using
the standard .NET mechanism. After the task that processes the entire tree
completes, we call `cts.Cancel()`

to trigger the cancellation. All tasks that
are started from that point will throw an exception (which is okay, because
non-deterministic choice ignores exceptions if the first computation succeeds).

As a result, the processing of `mixedTree`

is now significantly faster than the
processing of `primeTree`

. On the author's machine, the first one requires about
0.3s, while the second takes 4 seconds to complete. You can easily test the performance
for different inputs yourself using the `#time`

directive.

## Summary

In principle, the implementation of joinad operations for the `Task<'T>`

type is
very similar to the implementation for asynchronous workflows as discussed in the
previous article. The main difference is that the underlying type is
different - tasks are designed for CPU-intensive computations. Therefore the applications
in this article were quite different. We used tasks to write a parallel `map`

operation for lists and then to implement `forall`

function for trees. The second
was particularly interesting, because joinads make it very easy to implement
*shortcircuiting* behaviour thanks to the non-deterministic choice between clauses.

Full name: TryJoinads.parallelMap

Applies the specified function to all

elements of the input list in parallel.

Applies the specified function to all

elements of the input list in parallel.

type: 'T list

Full name: FSharp.Extensions.Joinads.TopLevelValues.future

type: 'T list

type: 'R list

Full name: TryJoinads.nums

type: int64 list

type: int64

inherits: System.ValueType

Full name: TryJoinads.isPrime

Tests whether the specified 64 bit int is a prime

Tests whether the specified 64 bit int is a prime

type: int64

inherits: System.ValueType

val seq : seq<'T> -> seq<'T>

Full name: Microsoft.FSharp.Core.Operators.seq

--------------------

type seq<'T> = System.Collections.Generic.IEnumerable<'T>

Full name: Microsoft.FSharp.Collections.seq<_>

type: seq<'T>

inherits: System.Collections.IEnumerable

val int64 : 'T -> int64 (requires member op_Explicit)

Full name: Microsoft.FSharp.Core.Operators.int64

--------------------

type int64<'Measure> = int64

Full name: Microsoft.FSharp.Core.int64<_>

type: int64<'Measure>

inherits: System.ValueType

--------------------

type int64 = System.Int64

Full name: Microsoft.FSharp.Core.int64

type: int64

inherits: System.ValueType

Full name: Microsoft.FSharp.Core.Operators.sqrt

val float : 'T -> float (requires member op_Explicit)

Full name: Microsoft.FSharp.Core.Operators.float

--------------------

type float<'Measure> = float

Full name: Microsoft.FSharp.Core.float<_>

type: float<'Measure>

inherits: System.ValueType

--------------------

type float = System.Double

Full name: Microsoft.FSharp.Core.float

type: float

inherits: System.ValueType

from Microsoft.FSharp.Collections

Full name: Microsoft.FSharp.Collections.Seq.forall

type: int64

inherits: System.ValueType

module List

from Microsoft.FSharp.Collections

--------------------

type List<'T> =

| ( [] )

| ( :: ) of 'T * 'T list

with

interface System.Collections.IEnumerable

interface System.Collections.Generic.IEnumerable<'T>

member Head : 'T

member IsEmpty : bool

member Item : index:int -> 'T with get

member Length : int

member Tail : 'T list

static member Cons : head:'T * tail:'T list -> 'T list

static member Empty : 'T list

end

Full name: Microsoft.FSharp.Collections.List<_>

type: List<'T>

Full name: Microsoft.FSharp.Collections.List.map

| Leaf of 'T

| Node of Tree<'T> * Tree<'T>

Full name: TryJoinads.Tree<_>

type: Tree<'T>

Full name: TryJoinads.ballancedOfList

Creates a ballanced tree from a non-empty list

(odd elements are added to the left and even to the right)

Creates a ballanced tree from a non-empty list

(odd elements are added to the left and even to the right)

val list : 'a list

type: 'a list

--------------------

type 'T list = List<'T>

Full name: Microsoft.FSharp.Collections.list<_>

type: 'T list

Full name: Microsoft.FSharp.Core.Operators.failwith

type: (int * 'a) list

type: (int * 'a) list

Full name: Microsoft.FSharp.Collections.List.mapi

type: int

inherits: System.ValueType

Full name: Microsoft.FSharp.Collections.List.partition

type: 'a list

type: 'a list

Full name: Microsoft.FSharp.Core.Operators.snd

Full name: TryJoinads.primes

type: int64 list

type: int64

inherits: System.ValueType

Full name: Microsoft.FSharp.Collections.List.filter

Full name: Microsoft.FSharp.Core.Operators.fst

Full name: TryJoinads.mixed

type: int64 list

Full name: TryJoinads.primeTree

type: Tree<int64>

Full name: TryJoinads.mixedTree

type: Tree<int64>

Full name: TryJoinads.Parallel.forall

Checks whether the specified predicate 'f'

holds for all Leaf elements of the tree.

Checks whether the specified predicate 'f'

holds for all Leaf elements of the tree.

type: Tree<'a>

type: Tree<'a>

type: Tree<'a>

type: bool

inherits: System.ValueType

type: bool

inherits: System.ValueType

Full name: TryJoinads.Shortcircuiting.forall

Behaves like previous 'forall' function, but returns

immediately when one of the branches returns 'false'

Behaves like previous 'forall' function, but returns

immediately when one of the branches returns 'false'

type: CancellationTokenSource

class

interface System.IDisposable

new : unit -> CancellationTokenSource

member Cancel : unit -> unit

member Dispose : unit -> unit

member Token : CancellationToken

static member CreateLinkedTokenSource : token1:CancellationToken * token2:CancellationToken -> CancellationTokenSource

end

Full name: System.Threading.CancellationTokenSource

type: CancellationTokenSource

type: bool

inherits: System.ValueType

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