Why do global variables impact performance so badly


function test1()
    global x = 10
    for i in 1:10^6
        x += i
    end
    return x
end

function test2()
    x = 10
    for i in 1:10^6
        x += i
    end
    return x
end

function test3()
    x = 10
    for i in 1:10^6
        global x += i
    end
    return x
end

@time test1()
@time test2()
@time test3()

Solution 1: Using Global Variables

One way to solve the issue of global variables impacting performance is by using global variables directly. In this approach, the variable is declared as global within the function, allowing it to be accessed and modified from anywhere within the code.

However, using global variables can have a negative impact on performance. This is because accessing and modifying global variables requires additional memory and processing time. In the given example, the function test1() uses a global variable x and performs a loop operation. The time taken to execute this function can be measured using the @time macro.

Solution 2: Avoiding Global Variables

An alternative solution is to avoid using global variables altogether. In this approach, the variable is declared locally within the function, limiting its scope to that specific function. This can help improve performance by reducing memory usage and eliminating the need for global variable access.

In the given example, the function test2() avoids using a global variable and instead declares a local variable x. The loop operation is performed using this local variable. The execution time of this function can also be measured using the @time macro.

Solution 3: Combining Local and Global Variables

A third solution is to combine the use of local and global variables. In this approach, a local variable is declared within the function, but the global variable is accessed and modified within the loop operation. This can help strike a balance between performance and flexibility.

In the given example, the function test3() declares a local variable x and performs the loop operation. However, within the loop, the global variable x is accessed and modified using the global keyword. The execution time of this function can also be measured using the @time macro.

After running the code and measuring the execution times, it can be observed that Solution 2 (avoiding global variables) performs the best in terms of performance. This is because it eliminates the overhead associated with global variable access and modification. Therefore, Solution 2 is the recommended approach for improving performance when global variables are impacting performance negatively.

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