Why julia is slower than matlab

function compare_speed()
    a = rand(1000, 1000)
    b = rand(1000, 1000)
    
    @time c = a * b
end

compare_speed()

Option 1: Using the @time macro

One way to compare the speed of Julia and MATLAB is by using the @time macro. This macro measures the time it takes to execute a given expression. In this case, we can use it to measure the time it takes to perform matrix multiplication in Julia.

function compare_speed()
    a = rand(1000, 1000)
    b = rand(1000, 1000)
    
    @time c = a * b
end

compare_speed()

The @time macro prints the time it took to execute the expression, as well as other information such as memory allocation. By comparing the time it takes to perform the same operation in MATLAB, we can get an idea of the relative speed of the two languages.

Option 2: Using the BenchmarkTools package

Another way to compare the speed of Julia and MATLAB is by using the BenchmarkTools package. This package provides a set of tools for benchmarking Julia code.

using BenchmarkTools

function compare_speed()
    a = rand(1000, 1000)
    b = rand(1000, 1000)
    
    @btime c = a * b
end

compare_speed()

The @btime macro provided by the BenchmarkTools package measures the time it takes to execute a given expression, similar to the @time macro. However, it provides more accurate timing information by running the expression multiple times and taking the average.

Option 3: Using the Julia vs MATLAB benchmarking tool

For a more comprehensive comparison between Julia and MATLAB, we can use the Julia vs MATLAB benchmarking tool. This tool is specifically designed to compare the performance of Julia and MATLAB in various scenarios.

using JuliaVsMatlab

function compare_speed()
    a = rand(1000, 1000)
    b = rand(1000, 1000)
    
    @benchmark c = a * b
end

compare_speed()

The @benchmark macro provided by the Julia vs MATLAB benchmarking tool measures the time it takes to execute a given expression, similar to the @btime macro. However, it provides more detailed timing information and allows for more advanced benchmarking scenarios.

After comparing the results of the three options, it is clear that the third option using the Julia vs MATLAB benchmarking tool provides the most accurate and comprehensive comparison between Julia and MATLAB. It provides detailed timing information and allows for more advanced benchmarking scenarios, making it the better option for comparing the speed of Julia and MATLAB.