PHP8’s JIT accelerator: opening up a new era of performance improvement

With the development of the Internet and the advancement of technology, the response speed of web pages has become one of the important indicators of user experience. one. As a widely used server-side scripting language, PHP has always been loved by developers for its simplicity, ease of learning and powerful functions. However, when processing large and complex business logic, PHP's performance often encounters bottlenecks. To solve this problem, PHP8 introduces a brand new feature: JIT (just in time compilation) accelerator.

The JIT accelerator is an important improvement in PHP8, and its introduction will bring huge performance improvements to developers. In the traditional PHP execution process, the PHP source code is executed line by line through the interpreter. Although this way of interpretation and execution is flexible, it is less efficient. The goal of the JIT accelerator is to increase execution speed by converting source code into machine code.

In PHP8, the JIT accelerator is mainly implemented through two components: Trampolines and Profile-guided Optimization (PGO). Trampolines are a mechanism for transferring control flow to JIT-compiled machine code when PHP execution reaches hot code. PGO is an optimization technology that collects performance data by running programs in a real environment and monitoring their execution, and then optimizes the compilation process based on these data.

Let us demonstrate the performance improvement of the JIT accelerator through a specific example. Let's say we have a simple PHP script that calculates the sum of an array of integers. The following is the traditional PHP code implementation:

<?php
function sum($array) {
    $sum = 0;
    foreach ($array as $value) {
        $sum += $value;
    }
    return $sum;
}

$array = range(1, 100000);
$start = microtime(true);
$result = sum($array);
$end = microtime(true);
$time = $end - $start;
echo "Sum: {$result}
";
echo "Time: {$time} seconds
";
?>

The above code calculates the sum by looping through the array and accumulating each element. Running this script, you can get results similar to the following:

Sum: 5000050000
Time: 0.055449008941649 seconds

Now let us turn on the JIT accelerator and use JIT capabilities to optimize the same code. Simply add the following configuration items to the php.ini file to enable JIT:

opcache.enable=1
opcache.enable_cli=1
opcache.jit_buffer_size=100M
opcache.jit=1255

Running the optimized code, we can get the following results:

Sum: 5000050000
Time: 0.024117946624756 seconds

As you can see, enable After JIT accelerator, the execution time of the script is reduced by half. This is because JIT can compile hot code into machine code, thus avoiding the performance loss of the interpreter.

The introduction of the JIT accelerator not only means a performance improvement in PHP8, it also enables PHP to handle larger-scale and more complex tasks. Especially when using frameworks, libraries, and large applications, the performance advantages of JIT will be more obvious.

However, it should be noted that not all PHP code is suitable for using JIT accelerator. For simple code and small-scale projects, JIT accelerators may not bring significant performance improvements. In addition, since the performance advantages of JIT are mainly reflected in long-running tasks, for short scripts, JIT may add additional overhead.

In summary, PHP8's JIT accelerator is an important feature, which brings significant performance improvements to PHP. By compiling hot code into machine code, JIT reduces the performance loss of the interpreter, thereby speeding up PHP execution. However, developers should weigh the pros and cons based on specific circumstances and use JIT accelerators appropriately. When processing large-scale and complex tasks, the performance advantages of JIT will be fully demonstrated.

(Note: The code examples in this article are only used to demonstrate the performance improvement of the JIT accelerator. The actual effect is affected by many factors, such as hardware performance, code complexity, etc.)

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