Garbage Collector Algorithm Research Articles

Kilobyte Virtual Machine Memory Management

Java Virtual Machines use various automatic garbage collector algorithms to manage memory in the object lifecycle. However, these algorithms have some drawbacks. In order to improve embedded systems memory management, we implement a new garbage collector algorithm on Kilobyte Virtual Machine. This algorithm apply the mark-sweep and compaction of the memory garbage collection in pages most used in the recent past, and the mark-sweep garbage collection without compacting the memory in pages used the least in the near past.

A performance comparison of garbage collector algorithms in Java Virtual Machine

In programming languages with automatic memory management garbage collection plays an important role of cleaning unused memory. Garbage collection algorithms have been developed for many years and aim to maximize the application’s performance. This paper presents and compares a performance of five garbage collection algorithms present in current version of Java 12 in three applications with different object lifetime span. The analysis covered the system responsiveness, garbage collector workload and application throughput at high application load.

Packer: Parallel Garbage Collection Based on Virtual Spaces

The fundamental challenge of garbage collector (GC) design is to maximize the recycled space with minimal time overhead. For efficient memory management, in many GC designs the heap is divided into large object space (LOS) and normal object space (non-LOS). When either space is full, garbage collection is triggered even though the other space may still have plenty of room, thus leading to inefficient space utilization. Also, space partitioning in existing GC designs implies different GC algorithms for different spaces. This not only prolongs the pause time of garbage collection, but also makes collection inefficient on multiple spaces. To address these problems, we propose Packer, a parallel garbage collection algorithm based on the novel concept of virtual spaces. Instead of physically dividing the heap into multiple spaces, Packer manages multiple virtual spaces in one physical space. With multiple virtual spaces, Packer offers efficient memory management. With one physical space, Packer avoids the problem of an inefficient space utilization. To reduce the garbage collection pause time, we also propose a novel parallelization method that is applicable to multiple virtual spaces. Specifically, we reduce the compacting GC parallelization problem into a discreted acyclic graph (DAG) traversal parallelization problem, and apply it to both normal and large object compaction.

Profile-based pretenuring

Pretenuring can reduce copying costs in garbage collectors by allocating long-lived objects into regions that the garbage collector will rarely, if ever, collect. We extend previous work on pretenuring as follows: (1) We produce pretenuring advice that is neutral with respect to the garbage collector algorithm and configuration. We thus can and do combine advice from different applications. We find for our benchmarks that predictions using object lifetimes at each allocation site in Java programs are accurate, which simplifies the pretenuring implementation. (2) We gather and apply advice to both applications and Jikes RVM, a compiler and runtime system for Java written in Java. Our results demonstrate that building combined advice into Jikes RVM from different application executions improves performance, regardless of the application Jikes RVM is compiling and executing. This build-time advice thus gives user applications some benefits of pretenuring, without any application profiling. No previous work uses profile feedback to pretenure in the runtime system. (3) We find that application-only advice also consistently improves performance, but that the combination of build-time and application-specific advice is almost always noticeably better. (4) Our same advice improves the performance of generational, Older First, and Beltway collectors, illustrating that it is collector neutral . (5) We include an immortal allocation space in addition to a nursery and older generation, and show that pretenuring to immortal space has substantial benefit.

Pretenuring for Java

Pretenuring can reduce copying costs in garbage collectors by allocating long-lived objects into regions that the garbage collector with rarely, if ever, collect. We extend previous work on pretenuring as follows. (1) We produce pretenuring advice that is neutral with respect to the garbage collector algorithm and configuration. We thus can and do combine advice from different applications. We find that predictions using object lifetimes at each allocation site in Java prgroams are accurate, which simplifies the pretenuring implementation. (2) We gather and apply advice to applications and the Jalapeño JVM, a compiler and run-time system for Java written in Java. Our results demonstrate that building combined advice into Jalapeño from different application executions improves performance regardless of the application Jalapeño is compiling and executing. This build-time advice thus gives user applications some benefits of pretenuring without any application profiling. No previous work pretenures in the run-time system. (3) We find that application-only advice also improves performance, but that the combination of build-time and application-specific advice is almost always noticeably better. (4) Our same advice improves the performance of generational and Older First colleciton, illustrating that it is collector neutral .

Nonintrusive Cloning Garbage Collection with Stock Operating System Support

It is well accepted that automatic garbage collection simplifies programming, promotes modularity, and reduces development effort. However it is commonly believed that these advantages do not counteract the perceived price: excessive overheads, possible long pause times while garbage collections occur, and the need to modify existing code. Even though there are publically available garbage collector implementations that can be used in existing programs, they do not guarantee short pauses, and some modification of the application using them is still required. In this paper we describe a snapshot-at-beginning concurrent garbage collector algorithm and its implementation. This algorithm guarantees short pauses, and can be easily implemented on stock UNIX-like operating systems. Our results show that our collector performs comparable to other garbage collection implementations on uniprocessor machines and outperforms similar collectors on multiprocessor machines. We also show our collector to be competitive in performance with explicit deallocation. Our collector has the added advantage of being non-intrusive. Using a dynamic linking technique and effective root set inferencing, we have been able to successfully run our collector even in commercial programs where only the binary executable and no source code is available. In this paper we describe our algorithm, its implementation, and provide both an algorithmic and a performance comparison between our collector and other similar garbage collectors. ©1997 by John Wiley & Sons, Ltd.