How does HotSpot optimizations (inlining, EA) behave in multithreaded code?

HotSpot optimizations such as inlining and escape analysis (EA) significantly improve the performance of Java applications. However, their behavior can vary in multithreaded environments. Inlining is performed by the JIT (Just-In-Time) compiler, which replaces method calls with the method's body to reduce overhead, while EA analyzes object usage to minimize allocations and reduce garbage collection pressure. In a multithreaded context, the effectiveness of these optimizations depends on the level of contention for shared resources and the way objects are accessed across threads.

For instance, if multiple threads frequently access a shared method that has been optimized through inlining, the impact of inlining may diminish due to potential cache coherency issues. On the other hand, escape analysis can be more beneficial in multithreaded environments when objects created inside a thread-local context are effectively optimized, leading to fewer allocations and improved performance.

Example of HotSpot Optimizations in Multithreaded Code

// Example in Java
public class ThreadOptimizationExample {
    
    private static class MyClass {
        void doWork() {
            // Simulate work
            for (int i = 0; i < 1000; i++) {
                Math.sqrt(i);
            }
        }
    }
    
    public static void main(String[] args) {
        Runnable task = () -> {
            MyClass myClass = new MyClass();
            myClass.doWork();
        };
        
        Thread thread1 = new Thread(task);
        Thread thread2 = new Thread(task);
        
        thread1.start();
        thread2.start();
        
        try {
            thread1.join();
            thread2.join();
        } catch (InterruptedException e) {
            Thread.currentThread().interrupt();
        }
    }
}