Understanding Garbage Collection Algorithms

In the realm of programming and software development, managing memory efficiently is paramount. One of the techniques used for this purpose is garbage collection (GC), a process that automatically reclaims memory occupied by objects that are no longer in use. Garbage collection algorithms come in various flavors, each with its own set of strengths and weaknesses. In this comprehensive article, we will explore the inner workings of four prominent garbage collection algorithms: Serial, Parallel, CMS (Concurrent Mark-Sweep), and G1 (Garbage-First).

Understanding Garbage Collection

Before diving into the specifics of each garbage collection algorithm, let’s begin with a brief overview of the core concept:

Garbage Collection (GC) automates memory management by identifying and reclaiming memory that is no longer accessible to the program, thereby preventing memory leaks and enhancing system stability. A GC algorithm typically involves two main tasks:

1. Marking: Identifying which objects in memory are still reachable (live) and which are not (garbage). This is often done by starting from a set of root objects and traversing the entire object graph through references.
2. Sweeping: Reclaiming memory occupied by the garbage objects, updating memory management data structures, and making memory available for future allocations.

Now, let’s delve into the inner workings of each garbage collection algorithm

1. Serial Garbage Collection

Operation

• Single-Threaded: Serial GC operates in a single thread and suspends all application threads during collection, earning the nickname “stop-the-world.”
• Mark-Sweep Algorithm: It uses a simple mark-sweep algorithm where it marks live objects during the marking phase and sweeps away the garbage objects in the sweeping phase.

Example: Let’s consider a simple Java program with the following objects in memory:

class Node {
    int value;
    Node next;
}

Node node1 = new Node(); // Object A
Node node2 = new Node(); // Object B
Node node3 = new Node(); // Object C

node1.next = node2; // Object A references Object B
node2.next = node3; // Object B references Object C

Here’s how serial garbage collection works:

1. Pause the Application

• All application threads are paused. No new object creation or reference changes can occur during this phase.

2. Marking Phase

• The GC starts from root objects. In our example, the root objects are node1, node2, and node3.
• It follows references to traverse the object graph. So, it marks node1, node2, and node3 as live objects.
• Any object not reachable from the roots (e.g., any objects not connected to node1, node2, or node3) is considered garbage.

3. Sweeping Phase

• The GC sweeps through the heap and reclaims memory occupied by the garbage objects (objects not marked as live).
• In our example, if there were any unreferenced objects in memory, they would be removed, and their memory would be made available for future allocations.

4. Resume Application

• After the garbage collection process is complete, the application threads are resumed, and the program continues its execution.

2. Parallel Garbage Collection

Operation

• Multithreaded: Parallel GC uses multiple threads to perform the collection, making it more suitable for multi-core systems.
• Mark-Sweep Algorithm: Similar to serial GC, it employs a mark-sweep algorithm.

Example: Continuing with the previous example, let’s see how parallel garbage collection works:

1. Pause the Application

• Like in serial GC, all application threads are paused.

2. Marking Phase

• Multiple threads work in parallel to mark live objects.
• Each thread can mark a portion of the object graph concurrently, improving the efficiency of the marking phase.

3. Sweeping Phase

• Similar to the serial version, the sweeping phase reclaims memory occupied by the garbage objects.
• Multiple threads collaborate to perform this task efficiently.

4. Resume Application

• After the garbage collection process is complete, the application threads are resumed, and the program continues its execution.

3. CMS (Concurrent Mark-Sweep) Garbage Collection

Operation

• Concurrent: CMS is designed to minimize pause times by performing most of the marking and sweeping concurrently with the application threads.
• Initial Mark: An initial mark phase identifies the root objects to be collected.
• Concurrent Mark: Concurrently with the application, it marks live objects.
• Concurrent Sweep: Garbage objects are swept concurrently, and memory is reclaimed.

Example: Using the same example, let’s explore how CMS garbage collection works:

1. Pause the Application

• Initially, an application pause occurs to perform the initial marking phase.

2. Initial Marking Phase

• The GC identifies the root objects (node1, node2, and node3) and marks them as live.
• This phase is short and involves a brief pause.

3. Concurrent Marking Phase

• Concurrently with the application, CMS marks live objects by following references.
• The application can continue executing during this phase.

4. Concurrent Sweeping Phase

• Garbage objects are swept concurrently, and memory is reclaimed.
• This phase runs in parallel with the application, further reducing pause times.

5. Resume Application

• After the concurrent phases are complete, the application continues running without long stop-the-world pauses.

4. G1 (Garbage-First) Garbage Collection

Operation

• Region-Based: G1 divides the heap into regions and uses a more sophisticated algorithm compared to mark-sweep.
• Predictable Pauses: G1 aims to provide predictable pause times by collecting the regions with the most garbage first.
• Concurrent Phases: Most phases are concurrent, including marking and evacuation.

Example: Let’s continue with the same example and see how G1 garbage collection works:

1. Pause the Application

• Initially, there is a pause to start the GC, but it’s relatively short.

2. Initial Marking Phase

• The GC identifies the root objects (node1, node2, and node3) and marks them as live.
• This phase is short and involves a brief pause.

3. Concurrent Marking Phase

• Concurrently with the application, G1 marks live objects, following references.
• The application can continue executing during this phase.

4. Evacuation Phase

• G1 identifies regions with the most garbage and prioritizes collecting them.
• Live objects from those regions are evacuated to other regions.
• This phase runs concurrently, and regions are collected incrementally.

5. Finalisation Phase

• Remaining garbage in the old regions is collected, and memory is reclaimed.
• This phase is also concurrent.

6. Resume Application

• After the concurrent phases are complete, the application continues running without long stop-the-world pauses.

Conclusion

Each garbage collection algorithm, be it Serial, Parallel, CMS, or G1, has its own set of characteristics and trade-offs. The choice of the algorithm depends on your application’s specific requirements, hardware capabilities, and performance goals. Understanding how these algorithms work at a granular level can help you make informed decisions about memory management in your software projects.