JuliaMain.jl

println("started")

# ]add BenchmarkTools
# ]add MAT
using BenchmarkTools # for benchmark
const BenchmarkTools.DEFAULT_PARAMETERS.samples = 700;
const BenchmarkTools.DEFAULT_PARAMETERS.evals = 1;
using DelimitedFiles # for readdlm, writedlm
using Statistics # for median
using LinearAlgebra # for eigen, pinv, svd, cholesky
using Random # for randperm
using MAT

const operationMode = 2; # 0 for test only # 1 for partial benchmark # 2 for full benchmark
const saveData = true; # true for saving Runtimes to csv and mat
const JuliaFlag = true; # run Julia benchmark
const JuliaSIMDFlag = true; # run Julia SIMD benchmark
const debugging = false;

if BLAS.vendor() == :mkl
    # MKL

    ### Julia
    if JuliaFlag
        include("JuliaBench.jl")
        tRunTime, mRunTime = JuliaBench(operationMode)

        if saveData
            # Main RunTime Table write
            writedlm(
                joinpath(
                    "RunTimeData",
                    "RunTimeJulia$(BLAS.vendor())Table.csv",
                ),
                tRunTime,
                ',',
            )
            # RunTime save
            file = matopen(
                joinpath("RunTimeData", "RunTimeJulia$(BLAS.vendor()).mat"),
                "w",
            )
            write(file, "mRunTime", mRunTime)
            close(file)
        end
    end

    ### Julia SIMD
    if JuliaSIMDFlag
        include("JuliaBenchSIMD.jl")
        tRunTime, mRunTime = JuliaBenchSIMD(operationMode)

        if saveData
            # Main RunTime Table write
            writedlm(
                joinpath(
                    "RunTimeData",
                    "RunTimeJulia$(BLAS.vendor())SIMDTable.csv",
                ),
                tRunTime,
                ',',
            )
            # RunTime save
            file = matopen(
                joinpath("RunTimeData", "RunTimeJulia$(BLAS.vendor())SIMD.mat"),
                "w",
            )
            write(file, "mRunTime", mRunTime)
            close(file)
        end
    end


else
    # openBLAS

    ## BLAS threads = 1
    BLAS.set_num_threads(1)

    ### Julia
    if JuliaFlag
        include("JuliaBench.jl")
        tRunTime, mRunTime = JuliaBench(operationMode)

        if saveData
        # Main RunTime Table write
            writedlm(
                joinpath(
                    "RunTimeData",
                    "RunTimeJulia$(BLAS.vendor())Table.csv",
                ),
                tRunTime,
                ',',
            )
        # RunTime save
            file = matopen(
                joinpath("RunTimeData", "RunTimeJulia$(BLAS.vendor()).mat"),
                "w",
            )
            write(file, "mRunTime", mRunTime)
            close(file)
        end
    end



    ### Julia SIMD
    if JuliaSIMDFlag
        include("JuliaBenchSIMD.jl")
        tRunTime, mRunTime = JuliaBenchSIMD(operationMode)

        if saveData
        # Main RunTime Table write
            writedlm(
                joinpath(
                    "RunTimeData",
                    "RunTimeJulia$(BLAS.vendor())SIMDTable.csv",
                ),
                tRunTime,
                ',',
            )
        # RunTime save
            file = matopen(
                joinpath("RunTimeData", "RunTimeJulia$(BLAS.vendor())SIMD.mat"),
                "w",
            )
            write(file, "mRunTime", mRunTime)
            close(file)
        end
    end

    ## BLAS threads = 4
    BLAS.set_num_threads(4)

    ### Julia
    if JuliaFlag
        include("JuliaBench.jl")
        tRunTime, mRunTime = JuliaBench(operationMode)

        if saveData
        # Main RunTime Table write
            writedlm(
                joinpath(
                    "RunTimeData",
                    "RunTimeJulia$(BLAS.vendor())Table_4Thread.csv",
                ),
                tRunTime,
                ',',
            )
        # RunTime save
            file = matopen(
                joinpath(
                    "RunTimeData",
                    "RunTimeJulia$(BLAS.vendor())_4Thread.mat",
                ),
                "w",
            )
            write(file, "mRunTime", mRunTime)
            close(file)
        end
    end



    ### Julia SIMD
    if JuliaSIMDFlag
        include("JuliaBenchSIMD.jl")
        tRunTime, mRunTime = JuliaBenchSIMD(operationMode)

        if saveData
        # Main RunTime Table write
            writedlm(
                joinpath(
                    "RunTimeData",
                    "RunTimeJulia$(BLAS.vendor())SIMDTable_4Thread.csv",
                ),
                tRunTime,
                ',',
            )
        # RunTime save
            file = matopen(
                joinpath(
                    "RunTimeData",
                    "RunTimeJulia$(BLAS.vendor())SIMD_4Thread.mat",
                ),
                "w",
            )
            write(file, "mRunTime", mRunTime)
            close(file)
        end
    end

end

if debugging
    # Debug and performance trace
    include("JuliaBench.jl")
    matrixSize = 20
    mX = randn(matrixSize, matrixSize)
    mY = randn(matrixSize, matrixSize)
    allFunctions = [
        MatrixGeneration,
        MatrixAddition,
        MatrixMultiplication,
        MatrixQuadraticForm,
        MatrixReductions,
        ElementWiseOperations,
        MatrixExp,
        MatrixSqrt,
        Svd,
        Eig,
        CholDec,
        MatInv,
        LinearSystem,
        LeastSquares,
        CalcDistanceMatrix,
        KMeans,
    ]
    # debug the code
    # Juno.@enter allFunctions[2](matrixSize, mX, mY) # copy paste to REPL
    # timing and memory
    @time allFunctions[2](matrixSize, mX, mY)
    # bad practices used in coding
    # Juno.@trace allFunctions[1](matrixSize, mX, mY)
    # profiles the code
    # using Profile
    # Profile.clear();
    # @profile allFunctions[2](matrixSize, mX, mY)
    # Profile.print(combine = true)
    # profiletree=Juno.profiletree()
    # Juno.profiler()
    # advanced tool for diagnosing type-related problems
    # @code_warntype allFunctions[2](matrixSize, mX, mY)
end