在 fsi 4.0.30319.1 和 2.0.0.0 上运行 f# 相同代码的巨大性能差异

Question

我正在使用两个版本的 fsi.exe 运行相同的 F# 代码，我可以在 FSharp-2.0.0.0 安装下找到该代码：

C:\Program Files\FSharp-2.0.0.0\bin\fsi.exe - Microsoft (R) F# 2.0 Interactive build 2.0.0

C:\Program Files\FSharp-2.0.0.0\v4.0\bin\fsi.exe - Microsoft (R) F# 2.0 Interactive build 4.0.30319.1

我发现相同的代码在 2.0.0.0 版本上的运行速度大约是原来的三倍。这有什么意义吗？我的环境或代码是否有问题？

顺便说一句，我尝试使用 v4.0 版本的原因是能够使用 TPL 并比较我的代码的顺序和并行实现。当我的并行实现比顺序实现慢得多时，经过一番绞尽脑汁后，我意识到并行版本在不同的 fsi.exe 下运行，就在那时我意识到代码的相同（顺序）版本要慢得多在4.0版本下。

预先感谢您的任何帮助

是

代码：

module Options

//Gaussian module is from http://fssnip.net/3g, by Tony Lee
open Gaussian

//The European Option type
type EuropeanOption = 
        {StockCode: string
         StockPrice: float
         ExercisePrice: float
         NoRiskReturn: float
         Volatility: float
         Time: float
        }

//Read one row from the file and return a European Option
//File format is:
//StockCode<TAB>StockPrice,ExercisePrice,NoRiskReturn,Volatility,Time
let convertDataRow(line:string) =
    let option = List.ofSeq(line.Split('\t'))
    match option with
    | code::data::_ -> 
        let dataValues = (data.Split(','))
        let euopt = {StockCode = code; 
                     StockPrice = float (dataValues.[0]); 
                     ExercisePrice = float (dataValues.[1]); 
                     NoRiskReturn = float (dataValues.[2]); 
                     Volatility = float (dataValues.[3]); 
                     Time = float (dataValues.[4])
                     }
        euopt
    | _ -> failwith "Incorrect Data Format" 

//Returns the future value of an option. 
//0 if excercise price is greater than the sum of the stock price and the calculated asset price at expiration. 
let futureValue sp ep nrr vol t =
    //TODO: Is there no better way to get the value from a one-element sequence?
    let assetPriceAtExpiration = sp+sp*nrr*t+sp*sqrt(t)*vol*(Gaussian.whiteNoise |> Seq.take 1  |> List.ofSeq |> List.max)
    [0.0;assetPriceAtExpiration - ep] |> List.max

//Sequence to hold the values generated by the MonteCarlo iterations
//50,000 iterations is the minimum for a good aprox to the Black-Scholes equation
let priceValues count sp ep nrr vol t = 
    seq { for i in 1..count
          -> futureValue sp ep nrr vol t
    }

//Discount a future to a present value given the risk free rate and the time in years
let discount value noriskreturn time =
    value * exp(-1.0*noriskreturn*time) 

//Get the price for a European Option and a given number of Monte Carlo iterations (use numIters >= 50000)
let priceOption europeanOption numIters =
    let futureValuesSeq = priceValues numIters europeanOption.StockPrice europeanOption.ExercisePrice europeanOption.NoRiskReturn europeanOption.Volatility europeanOption.Time
    //The simulated future value is just the average of all the MonteCarlo runs
    let presentValue = discount (futureValuesSeq |> List.ofSeq |> List.average) europeanOption.NoRiskReturn europeanOption.Time
    //Return a list of tuples with the stock code and the calculated present value
    europeanOption.StockCode + "_to_" + string europeanOption.Time + "_years \t" + string presentValue 


module Program =

    open Options
    open System
    open System.Diagnostics
    open System.IO

    //Write to a file
    let writeFile path contentsArray = 
        File.WriteAllLines(path, contentsArray |> Array.ofList)

    //TODO: This whole "method" is sooooo procedural.... is there a more functional way?

    //Unique code for each run
    //TODO: Something shorter, please
    let runcode = string DateTime.Now.Month + "_" + string DateTime.Now.Day + "_" + string DateTime.Now.Hour + "_" + string DateTime.Now.Minute + "_" + string DateTime.Now.Second

    let outputFile = @"C:\TMP\optionpricer_results_" + runcode + ".txt"

    let statsfile = @"C:\TMP\optionpricer_stats_" + runcode + ".txt"

    printf "Starting"
    let mutable stats = ["Starting at: [" + string DateTime.Now + "]" ]

    let stopWatch = Stopwatch.StartNew()

    //Read the file
    let lines = List.ofSeq(File.ReadAllLines(@"C:\tmp\9000.txt"))

    ignore(stats <- "Read input file done at: [" + string stopWatch.Elapsed.TotalMilliseconds + "]"::stats)
    printfn "%f" stopWatch.Elapsed.TotalMilliseconds

    //Build the list of European Options
    let options = lines |> List.map convertDataRow

    ignore(stats <- ("Created Options done at: [" + string stopWatch.Elapsed.TotalMilliseconds + "]")::stats)
    printfn "%f" stopWatch.Elapsed.TotalMilliseconds

    //Calculate the option prices
    let results = List.map (fun o -> priceOption o 50000) options

    ignore(stats <- "Option prices calculated at: [" + string stopWatch.Elapsed.TotalMilliseconds + "]"::stats)
    printfn "%f" stopWatch.Elapsed.TotalMilliseconds

    //Write results and statistics
    writeFile outputFile results
    ignore(stats <- "Output file written at: [" + string stopWatch.Elapsed.TotalMilliseconds + "]"::stats)

    ignore(stats <- "Total Ellapsed Time (minus stats file write): [" + string (stopWatch.Elapsed.TotalMilliseconds / 60000.0) + "] minutes"::stats)
    printfn "%f" stopWatch.Elapsed.TotalMilliseconds

    writeFile statsfile (stats |> List.rev)
    stopWatch.Stop()
    ignore(Console.ReadLine())

Answer 1

我还没有运行你的代码，但看起来你正在创建很多链接列表。这是非常低效的，但列表的表示近年来发生了变化，并且新的表示速度较慢。