Task.Factory的并行代码比线性慢

时间:2012-04-14 08:49:00

标签: .net f# parallel-processing

我正在玩并行编程和F#。我创建了一个集成了1变量函数的函数,然后我尝试以两种不同的方式使它并行:

module Quadrature = 

    let Integrate (f: double -> double) (x1: double) (x2: double) (samples: int64) =
        let step = (x2 - x1) / (double samples)
        let samplePoints = seq {x1 + step .. step .. x2 - step}
        let sum = samplePoints |> Seq.map (fun x -> f x) |> Seq.sum
        let sum = sum + ((f x1) + (f x2)) / 2.0
        step * sum

    let IntegrateWithStep (f: double -> double) (x1: double) (x2: double) (step: double) =
        let samples = (x2 - x1) / step |> round |> int64
        Integrate f x1 x2 samples

    let IntegrateWithTasks (f: double -> double) (x1: double) (x2: double) (samples: int64) (tasks: int) =
        let step = (x2 - x1) / (double samples)
        let samplesPerTask = ceil <| (double samples) / (double tasks)
        let interval = step * samplesPerTask
        let intervals = 
            seq { 
                for i in 0 .. (tasks - 1) do
                    let lowerBound = x1 + (double i) * interval
                    let upperBound = min (lowerBound + interval) x2  
                    yield (lowerBound, upperBound)
                }
        let tasks = intervals 
                    |> Seq.map (fun (a, b) -> Task.Factory.StartNew(fun () -> IntegrateWithStep f a b step))
        tasks |> Seq.map (fun t -> t.Result) |> Seq.sum

    let IntegrateParallel (f: double -> double) (x1: double) (x2: double) (samples: int64) (tasks: int) =
        let step = (x2 - x1) / (double samples)
        let samplesPerTask = ceil <| (double samples) / (double tasks)
        let interval = step * samplesPerTask
        let intervals = 
               [| for i in 0 .. (tasks - 1) do
                    let lowerBound = x1 + (double i) * interval
                    let upperBound = min (lowerBound + interval) x2  
                    yield (lowerBound, upperBound) |]
        intervals |> Array.Parallel.map (fun (a, b) -> IntegrateWithStep f a b step)
                  |> Array.sum

我在具有4个核心的计算机上使用以下输入运行此代码:

let f = (fun x -> - 1.0 + 2.0 * x - 3.0 * x * x + 4.0 * x * x * x ) 
let x1, x2 = 0.0, 1.0
let samples = 100000000L
let tasks = 100

但是,任务工厂的方法总是比线性方法略慢,而使用Parallel.map的方法可以让我加快速度。

我已经尝试将任务数量从数千减少到核心数量,但使用Task.Factory的实现总是慢于线性实现。我做错了什么?

1 个答案:

答案 0 :(得分:1)

请记住,序列是延迟加载的。这是第一次启动任务:

tasks |> Seq.map (fun t -> t.Result) |> Seq.sum

然后你按顺序启动它们并阻止每个结果(调用t.Result时。)你需要将任务列表保存为数组,然后在收集之前调用.WaitAll结果是为了确保它们全部并行开始。

尝试:

let tasks = intervals 
            |> Seq.map (fun (a, b) -> Task.Factory.StartNew(fun () -> IntegrateWithStep f a b step))
            |> Array.ofSeq

tasks.WaitAll()