As Java continues to evolve, the introduction of virtual threads (Project Loom) has fundamentally changed how we think about concurrency and performance. However, for developers using Java 21, 22, or 23, there’s a critical performance trap that many overlook: the stark difference between synchronized blocks and ReentrantLock when it comes to virtual thread compatibility and overall application performance. This issue was completely resolved in Java 24 and later, but if you're still on these earlier virtual thread implementations, understanding this difference could mean the difference between scalable success and production failure.
The Critical Misconception
There's a widespread belief that the JVM automatically manages all locking mechanisms equally. However, this is not true for synchronized blocks. Unlike what many developers assume, synchronized blocks create what are called "pinned threads" when used with virtual threads, effectively negating many of the benefits that virtual threads provide.
Understanding the Fundamental Differences
Synchronized Blocks: The Hidden Bottleneck
When a virtual thread encounters a synchronized block, it becomes pinned to its carrier thread. This means:
- The virtual thread cannot be unmounted from the carrier thread
- The carrier thread becomes blocked, reducing overall throughput
- The lightweight nature of virtual threads is compromised
- Scale can become severely limited
Here's a simple example demonstrating the problem:
public class SynchronizedBottleneck {
private final Object lock = new Object();
private int counter = 0;
public void incrementWithSynchronized() {
synchronized (lock) {
// This block pins the virtual thread to its carrier thread
counter++;
try {
Thread.sleep(100); // Simulating some work
} catch (InterruptedException e) {
Thread.currentThread().interrupt();
}
}
}
public int getCounter() {
synchronized (lock) {
return counter;
}
}
}
ReentrantLock: Virtual Thread Friendly
ReentrantLock, on the other hand, is designed to work seamlessly with virtual threads:
import java.util.concurrent.locks.ReentrantLock;
public class ReentrantLockOptimized {
private final ReentrantLock lock = new ReentrantLock();
private int counter = 0;
public void incrementWithReentrantLock() {
lock.lock();
try {
// Virtual thread can be unmounted during blocking operations
counter++;
Thread.sleep(100); // Simulating some work
} catch (InterruptedException e) {
Thread.currentThread().interrupt();
} finally {
lock.unlock();
}
}
public int getCounter() {
lock.lock();
try {
return counter;
} finally {
lock.unlock();
}
}
}
Performance Comparison: Real-World Impact
Let’s examine the performance differences with a comprehensive benchmark:
import java.time.Duration;
import java.time.Instant;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.locks.ReentrantLock;
import java.util.concurrent.atomic.AtomicLong;
public class ExtremeVirtualThreadTest {
private static final int VIRTUAL_THREAD_COUNT = 50000; // Massive thread count
private static final int WORK_DURATION_MS = 10; // Shorter work
private static final int NUM_RESOURCES = 100; // Many resources
static class SynchronizedCounter {
private final Object[] locks = new Object[NUM_RESOURCES];
private final AtomicLong totalCounter = new AtomicLong(0);
public SynchronizedCounter() {
for (int i = 0; i < NUM_RESOURCES; i++) {
locks[i] = new Object();
}
}
public void doWork(int resourceId) {
synchronized (locks[resourceId]) {
totalCounter.incrementAndGet();
try {
Thread.sleep(WORK_DURATION_MS);
} catch (InterruptedException e) {
Thread.currentThread().interrupt();
}
}
}
public long getTotalCount() {
return totalCounter.get();
}
}
static class ReentrantLockCounter {
private final ReentrantLock[] locks = new ReentrantLock[NUM_RESOURCES];
private final AtomicLong totalCounter = new AtomicLong(0);
public ReentrantLockCounter() {
for (int i = 0; i < NUM_RESOURCES; i++) {
locks[i] = new ReentrantLock();
}
}
public void doWork(int resourceId) {
locks[resourceId].lock();
try {
totalCounter.incrementAndGet();
Thread.sleep(WORK_DURATION_MS);
} catch (InterruptedException e) {
Thread.currentThread().interrupt();
} finally {
locks[resourceId].unlock();
}
}
public long getTotalCount() {
return totalCounter.get();
}
}
psvm(String[] args) throws InterruptedException {
System.out.println("Java Version: " + System.getProperty("java.version"));
System.out.println("Available Processors: " + Runtime.getRuntime().availableProcessors());
System.out.println("Testing with " + VIRTUAL_THREAD_COUNT + " virtual threads");
System.out.println("Using " + NUM_RESOURCES + " independent resources\n");
// Monitor system resources
monitorSystemResources();
benchmarkSynchronized();
System.out.println();
benchmarkReentrantLock();
}
private static void monitorSystemResources() {
System.out.println("=== System Information ===");
Runtime runtime = Runtime.getRuntime();
System.out.println("Max memory: " + runtime.maxMemory() / 1024 / 1024 + " MB");
System.out.println("Total memory: " + runtime.totalMemory() / 1024 / 1024 + " MB");
System.out.println("Free memory: " + runtime.freeMemory() / 1024 / 1024 + " MB");
System.out.println();
}
private static void benchmarkSynchronized() throws InterruptedException {
System.out.println("=== Testing Synchronized Block (Extreme Load) ===");
SynchronizedCounter counter = new SynchronizedCounter();
Instant start = Instant.now();
try (ExecutorService executor = Executors.newVirtualThreadPerTaskExecutor()) {
for (int i = 0; i < VIRTUAL_THREAD_COUNT; i++) {
final int resourceId = i % NUM_RESOURCES;
executor.submit(() -> counter.doWork(resourceId));
}
executor.shutdown();
executor.awaitTermination(10, TimeUnit.MINUTES);
}
Duration duration = Duration.between(start, Instant.now());
System.out.println("Final count: " + counter.getTotalCount());
System.out.println("Time taken: " + duration.toMillis() + " ms");
System.out.println("Throughput: " + String.format("%.2f", VIRTUAL_THREAD_COUNT * 1000.0 / duration.toMillis()) + " ops/sec");
}
private static void benchmarkReentrantLock() throws InterruptedException {
System.out.println("=== Testing ReentrantLock (Extreme Load) ===");
ReentrantLockCounter counter = new ReentrantLockCounter();
Instant start = Instant.now();
try (ExecutorService executor = Executors.newVirtualThreadPerTaskExecutor()) {
for (int i = 0; i < VIRTUAL_THREAD_COUNT; i++) {
final int resourceId = i % NUM_RESOURCES;
executor.submit(() -> counter.doWork(resourceId));
}
executor.shutdown();
executor.awaitTermination(10, TimeUnit.MINUTES);
}
Duration duration = Duration.between(start, Instant.now());
System.out.println("Final count: " + counter.getTotalCount());
System.out.println("Time taken: " + duration.toMillis() + " ms");
System.out.println("Throughput: " + String.format("%.2f", VIRTUAL_THREAD_COUNT * 1000.0 / duration.toMillis()) + " ops/sec");
}
}
The Performance Investigation: What Really Happens at Scale
When I first set out to write about the synchronized vs ReentrantLock performance differences, I decided to put these claims to the test. What I discovered was far more nuanced — and ultimately more shocking — than the typical articles suggest.
Initial Testing: The Surprising Truth
My first benchmark tested 1,000 virtual threads with a single shared resource:
=== Testing Results (1,000 Virtual Threads) ===
Synchronized Block: 102,828 ms (9.72 ops/sec)
ReentrantLock: 103,182 ms (9.69 ops/sec)
Performance difference: Virtually identical
No difference whatsoever. This made me question everything I’d read about virtual thread pinning.
Scaling Up: Still No Clear Winner
Thinking the issue might be lock contention, I increased the complexity to 1,000 virtual threads across 10 independent resources:
=== Testing Results (1,000 Threads, 10 Resources) ===
Synchronized Block: 10,352 ms (96.60 ops/sec)
ReentrantLock: 10,310 ms (96.99 ops/sec)
Performance difference: Still negligible
At this point, I was ready to conclude that the performance claims were overblown. But something told me to push harder.
The Breaking Point: Where Theory Meets Reality
Finally, I decided to test what happens under extreme load — the kind of concurrent pressure that enterprise applications face. I ran 50,000 virtual threads across 100 independent resources:
=== Testing Results (50,000 Virtual Threads, 100 Resources) ===
Environment: Java 21.0.5, 11 CPU cores, 4.6GB max memory
Synchronized Block: 51,596 ms (969.07 ops/sec)
ReentrantLock: 5,830 ms (8,576.33 ops/sec)
Performance improvement: 8.8x faster with ReentrantLock!
This is where synchronized blocks reveal their true cost. At enterprise scale, the difference isn’t just noticeable — it’s devastating.
Why the Dramatic Difference Only Appears at Scale
The results reveal a critical insight: virtual thread pinning isn’t a linear performance degradation — it’s a scalability cliff.
Here’s what happens:
Low Concurrency (< 1,000 threads):
- Sufficient carrier threads available
- Pinning effects are minimal
- Performance difference: Negligible
High Concurrency (> 10,000 threads):
- Carrier thread pool exhaustion
- Virtual threads queue waiting for available carriers
- Performance difference: Up to 10x degradation
The Real-World Implications
This testing reveals why many developers don’t initially notice the problem:
- Development environments rarely stress-test with 50,000+ concurrent operations
- Low-traffic applications never hit the threshold where pinning matters
- The performance cliff only becomes apparent under production-level loads
- By the time you notice, your application is already failing at scale
The Hidden Scalability Ceiling
Your application might be running perfectly with synchronized blocks today, but there’s a hidden ceiling built into your architecture. When traffic increases or you need to handle more concurrent operations, synchronized blocks become the bottleneck that brings everything to a halt.
This is exactly what happens in production environments where applications that worked fine during testing suddenly become unresponsive under real-world load. The 8.8x performance difference at scale explains why some applications experience mysterious slowdowns that seem to come out of nowhere.
Advanced ReentrantLock Features
Beyond virtual thread compatibility, ReentrantLock offers several advantages over synchronized:
1. Interruptible Lock Acquisition
public class InterruptibleLockExample {
private final ReentrantLock lock = new ReentrantLock();
public boolean processWithTimeout(long timeoutMs) {
try {
// Attempt to acquire lock with timeout
if (lock.tryLock(timeoutMs, TimeUnit.MILLISECONDS)) {
try {
// Critical section
performCriticalWork();
return true;
} finally {
lock.unlock();
}
} else {
System.out.println("Could not acquire lock within timeout");
return false;
}
} catch (InterruptedException e) {
Thread.currentThread().interrupt();
return false;
}
}
private void performCriticalWork() {
// Simulate work that might take time
try {
Thread.sleep(50);
} catch (InterruptedException e) {
Thread.currentThread().interrupt();
}
}
}
2. Fair Lock Implementation
public class FairLockExample {
// Fair lock ensures longest-waiting thread gets the lock next
private final ReentrantLock fairLock = new ReentrantLock(true);
private final ReentrantLock unfairLock = new ReentrantLock(false);
public void processWithFairLock() {
fairLock.lock();
try {
// Critical section - threads acquire lock in FIFO order
System.out.println(Thread.currentThread().getName() + " acquired fair lock");
Thread.sleep(10);
} catch (InterruptedException e) {
Thread.currentThread().interrupt();
} finally {
fairLock.unlock();
}
}
public void processWithUnfairLock() {
unfairLock.lock();
try {
// Critical section - any thread might acquire lock next
System.out.println(Thread.currentThread().getName() + " acquired unfair lock");
Thread.sleep(10);
} catch (InterruptedException e) {
Thread.currentThread().interrupt();
} finally {
unfairLock.unlock();
}
}
}
3. Condition Variables
import java.util.concurrent.locks.Condition;
import java.util.concurrent.locks.ReentrantLock;
public class ProducerConsumerExample {
private final ReentrantLock lock = new ReentrantLock();
private final Condition notEmpty = lock.newCondition();
private final Condition notFull = lock.newCondition();
private final Object[] buffer = new Object[10];
private int count = 0;
private int putIndex = 0;
private int takeIndex = 0;
public void produce(Object item) throws InterruptedException {
lock.lock();
try {
// Wait while buffer is full
while (count == buffer.length) {
notFull.await();
}
buffer[putIndex] = item;
putIndex = (putIndex + 1) % buffer.length;
count++;
// Signal that buffer is not empty
notEmpty.signal();
} finally {
lock.unlock();
}
}
public Object consume() throws InterruptedException {
lock.lock();
try {
// Wait while buffer is empty
while (count == 0) {
notEmpty.await();
}
Object item = buffer[takeIndex];
buffer[takeIndex] = null;
takeIndex = (takeIndex + 1) % buffer.length;
count--;
// Signal that buffer is not full
notFull.signal();
return item;
} finally {
lock.unlock();
}
}
}
Monitoring and Debugging Capabilities
ReentrantLock provides better introspection capabilities:
public class LockMonitoring {
private final ReentrantLock lock = new ReentrantLock();
public void demonstrateMonitoring() {
System.out.println("Lock held by current thread: " + lock.isHeldByCurrentThread());
System.out.println("Lock hold count: " + lock.getHoldCount());
System.out.println("Queued threads: " + lock.getQueueLength());
System.out.println("Is fair lock: " + lock.isFair());
lock.lock();
try {
System.out.println("After acquiring lock:");
System.out.println("Lock held by current thread: " + lock.isHeldByCurrentThread());
System.out.println("Lock hold count: " + lock.getHoldCount());
// Demonstrate reentrant behavior
lock.lock();
try {
System.out.println("After reentrant acquisition:");
System.out.println("Lock hold count: " + lock.getHoldCount());
} finally {
lock.unlock();
}
} finally {
lock.unlock();
}
}
}
Best Practices and Migration Strategy
When to Use ReentrantLock
- Virtual thread applications: Always prefer ReentrantLock
- Need timeout on lock acquisition: tryLock() with timeout
- Interruptible lock acquisition: lockInterruptibly()
- Fair lock ordering: Use fair locks when thread ordering matters
- Condition variables: Complex coordination between threads
Lock monitoring: Need to inspect lock state
When Synchronized Might Still Be AcceptablePlatform threads only: If you’re certain virtual threads won’t be used
Simple critical sections: Very short, non-blocking operations
Legacy code: Where migration cost outweighs benefits
Migration Pattern
Here’s a systematic approach to migrate from synchronized to ReentrantLock:
// Before: Synchronized
public class LegacyService {
private final Object lock = new Object();
public void processRequest() {
synchronized (lock) {
// Critical section
performWork();
}
}
}
// After: ReentrantLock
public class ModernService {
private final ReentrantLock lock = new ReentrantLock();
public void processRequest() {
lock.lock();
try {
// Critical section
performWork();
} finally {
lock.unlock();
}
}
}
Real-World Performance Impact
In high-throughput applications using virtual threads, the difference can be dramatic:
- Synchronized blocks: Can limit concurrent virtual threads to the number of carrier threads (typically equal to CPU cores)
- ReentrantLock: Allows true virtual thread concurrency, potentially handling thousands of concurrent operations
Consider a web application handling 10,000 concurrent requests. With synchronized blocks, you might be limited to processing only as many requests as you have CPU cores simultaneously. With ReentrantLock, all 10,000 virtual threads can proceed concurrently, dramatically improving throughput.
Conclusion
The choice between synchronized and ReentrantLock is no longer just about features—it's about future-proofing your applications for the virtual thread era. While synchronized blocks may seem simpler, they can become severe bottlenecks that can bring down entire applications when virtual threads are pinned to carrier threads.
Key takeaways:
- ReentrantLock is virtual thread-friendly and doesn't cause thread pinning
- synchronized blocks pin virtual threads to carrier threads, limiting scalability
- ReentrantLock offers advanced features like timeouts, fair locks, and condition variables
- Migration from synchronized to ReentrantLock should be prioritized in virtual thread applications
As Java continues to embrace virtual threads as the future of concurrency, understanding and implementing these differences isn’t just an optimisation — it’s essential for building scalable, high-performance applications.
The Game Changer: How Java 24 Solves the Pinning Problem Forever
While our performance tests demonstrate the severe impact of synchronized blocks in Java 21, there’s breaking news from the Java ecosystem that changes everything: Java 24 completely eliminates the virtual thread pinning issue with synchronized blocks.
JEP 491: The Technical Breakthrough
Oracle’s engineering team implemented JEP 491: Synchronize Virtual Threads without Pinning, fundamentally redesigning how the JVM handles monitor locks. This represents one of the most significant JVM improvements in recent years.
The Core Problem (Java 21–23)
The root issue was architectural — the JVM’s monitor system was designed for platform threads:
// The fundamental problem in Java 21-23:
synchronized (lock) {
// Monitor ownership tracked by CARRIER thread ID
// Virtual thread cannot unmount - PINNED!
performBlockingOperation();
}
When a virtual thread acquired a synchronized lock, the JVM's monitor mechanism used the carrier thread ID to track ownership. This meant:
Virtual threads couldn’t safely unmount while holding locks
Carrier threads became blocked and unavailable
The virtual thread scheduler couldn’t efficiently reuse platform threads
The Java 24+ Solution
The breakthrough came from making the monitor system virtual thread-aware:
// How it works in Java 24+:
synchronized (lock) {
// Monitor ownership now tracked by VIRTUAL thread ID
// Virtual thread can unmount while holding lock!
performBlockingOperation(); // Carrier thread remains available
}
The Technical Implementation
The solution required a complete overhaul of Java’s locking mechanism:
1. Virtual Thread Identity Tracking
- Monitors now use virtual thread IDs instead of carrier thread IDs
- Lock ownership follows the virtual thread, not the carrier
- Virtual threads can unmount and remount on different carriers while holding locks
2. Enhanced Mount/Unmount Operations
// What happens in Java 24 during synchronized operations:
1. Virtual thread acquires monitor using virtual thread ID
2. During blocking I/O, virtual thread unmounts from carrier
3. Carrier thread becomes available for other virtual threads
4. When ready, virtual thread remounts (possibly different carrier)
5. Execution continues with lock still held
3. Object.wait() Improvements
Even Object.wait() operations benefit:
- Virtual threads unmount while waiting
- When notified, they’re submitted back to the scheduler
- May resume on entirely different carrier threads
Performance Impact Projection
Based on our Java 21 testing results, here’s what Java 24 delivered:
// Our Java 21 Results (50,000 virtual threads):
Synchronized Block: 51,596 ms (969 ops/sec) ❌ Severe pinning
ReentrantLock: 5,830 ms (8,576 ops/sec) ✅ No pinning
// Expected Java 24 Results:
Synchronized Block: ~5,675 ms (8,810 ops/sec) ✅ No more pinning!
ReentrantLock: ~5,641 ms (8,864 ops/sec) ✅ Still no pinning
The 8.8x performance gap disappears completely.
The Engineering Achievement
This fix represents a massive engineering milestone:
- Zero breaking changes: All existing synchronized code works unchanged
- Automatic performance: Simply upgrading to Java 24+ provides the benefits
- Legacy code revival: Millions of lines of existing Java become virtual thread-ready
- Simplified adoption: No more mass synchronized-to-ReentrantLock migrations needed
Monitoring the Improvement
Java 24 also updates the diagnostic capabilities:
// Java 21-23: JFR events fired for synchronized blocks
jdk.VirtualThreadPinned: "Thread pinned due to synchronized block"
// Java 24+: JFR events only for remaining cases
jdk.VirtualThreadPinned: "Thread pinned due to native callback"
// Much rarer
What This Means for Your Applications
If You’re on Java 21–23:
- Critical: Audit your synchronized blocks in high-concurrency code
- Consider: Migrating to ReentrantLock for performance-critical sections
- Test: Verify your application’s behavior under high virtual thread loads
If You’re Planning Java 24+ Migration:
- Relax: Your existing synchronized code will perform optimally
- Focus: Spend optimization time on other bottlenecks
- Benefit: Immediate performance improvements without code changes
The Bigger Picture: Virtual Thread Maturity
Java 24’s synchronized fix removes the biggest adoption barrier for virtual threads:
- No more “synchronized considered harmful” articles needed
- Simplified virtual thread migration strategies
- Legacy application compatibility without performance penalties
- Developer cognitive load reduction — less to worry about
A Note of Caution
While Java 24 eliminates synchronized pinning, some scenarios still cause pinning:
- Native method callbacks that block
- Foreign Function & Memory API operations
- These cases are now clearly identified in monitoring tools
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