A concurrent, generational garbage collector for a multithreaded implementation of ML

Concurrent garbage collection algorithms are an emblematic challenge in the area of concurrent program verification. In this paper, we address this problem by proposing a mechanized proof methodology based on the popular RelyGuarantee (RG) proof technique. We design a specific compiler intermediate representation (IR) with strong type guarantees, dedicated support for abstract concurrent data structures, and high-level iterators on runtime internals. In addition, we define an RG program logic supporting an incremental proof methodology where annotations and invariants can be progressively enriched. We formalize the IR, the proof system, and prove the soundness of the methodology in the Coq proof assistant. Equipped with this IR, we prove a fully concurrent garbage collector where mutators never have to wait for the collector.

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“…The algorithm is based on [5], a variant of the well known concurrent mark-and-sweep algorithm due to Doligez, Leroy and Gonthier [4,3].…”

Section: The Concurrent Garbage Collectormentioning

confidence: 99%

“…Many on-the-fly algorithms are inherently racy, and some algorithms never require application threads (called mutators) to wait for the collector thread, which detects and frees unused memory. This paper focuses on an emblematic algorithm in this landscape [5,3,4], where no locks are required -i.e. it is lock-free.…”

Section: Introductionmentioning

confidence: 99%

Verifying a Concurrent Garbage Collector Using a Rely-Guarantee Methodology

Zakowski

Cachera

Demange

et al. 2017

Interactive Theorem Proving

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“…In order to further reduce the pause time of the STW collections, concurrent garbage collections have been developed [6] [7][8] [15]. Concurrent GC uses dedicated GC thread(s) to run concurrently with the mutator thread(s).…”

Section: Related Workmentioning

confidence: 99%

Improve Google Android User Experience with Regional Garbage Collection

He¹,

Yang²,

Li³

2011

Lecture Notes in Computer Science

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Abstract. Google Android is a popular software stack for smart phone, where the user experience is critical to its success. The pause time of its garbage collection in DalvikVM should not be too long to stutter the game animation or webpage scrolling. Generational collection or concurrent collection can be the effective approaches to reducing GC pause time. As of version 2.2, Android implements a non-generational stop-the-world (STW) mark-sweep algorithm. In this paper we present an enhancement called Regional GC for Android that can effectively improve its user experience. During the system bootup period, Android preloads the common runtime classes and data structures in order to save the user applications' startup time. When Android launches a user application the first time, it starts a new process with a new DalvikVM instance to run the application code. Every application process has its separate managed heap; while the system preloaded data space is shared across all the application processes. The Regional GC we propose is similar to a generational GC but actually partitions the heap according to regions instead of generations. One region (called the class region) is for the preloaded data, and the other region (called the user region) is for runtime dynamic data. A major collection of regional GC is the same as DalvikVM's normal STW collection, while a minor collection only marks and sweeps the user region. In this way, the regional GC effectively improves Android in both application performance and user experience. In the evaluation of an Android workload suite (AWS), 2D graphic workload Album Slideshow is improved by 28%, and its average pause time is reduced by 73%. The average pause time reduction across all the AWS applications is 55%. The regional GC can be combined with a concurrent GC to further reduce the pause time. This paper also describes two alternative write barrier designs in the Regional GC. One uses page fault to catch the reference writes on the fly; the other one scans the page table entries to discover the dirty pages. We evaluate the two approaches with the AWS applications, and discuss their respective pros and cons.

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“…Our garbage collector might best be described as a "locally-concurrent/globally-sequential" collector. It is based on the approach of Doligez, Leroy, and Gonthier [24,23]. The heap is organized into a fixed-size local heap for each vproc and a shared global heap ( Figure 5).…”

Section: Runtime Kernelmentioning

confidence: 99%

Programming in Manticore, a Heterogenous Parallel Functional Language

Fluet

Bergström

Ford

et al. 2010

Central European Functional Programming School

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The Manticore project is an effort to design and implement a new functional language for parallel programming. Unlike many earlier parallel languages, Manticore is a heterogeneous language that supports parallelism at multiple levels. Specifically, the Manticore language combines Concurrent ML-style explicit concurrency with fine-grain, implicitly threaded, parallel constructs. These lectures will introduce the Manticore language and explore a variety of programs written to take advantage of heterogeneous parallelism. At the explicit-concurrency level, Manticore supports the creation distinct threads of control and the coordination of threads through first-class synchronous-message passing. Message-passing synchronization, in contrast to shared-memory synchronization, fits naturally with the functional-programming paradigm. At the implicit-parallelism level, Manticore supports a diverse collection of parallel constructs for different granularities of work. Many of these constructs are inspired by common functional-programming idioms.In addition to describing the basic mechanisms, we will present a number of useful programming techniques that are enabled by these mechanisms. Finally, we will briefly discuss some of the implementation techniques used to execute Manticore programs on commodity multicore computers.

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A concurrent, generational garbage collector for a multithreaded implementation of ML

Cited by 189 publications

References 21 publications

Verifying a Concurrent Garbage Collector Using a Rely-Guarantee Methodology

Verifying a Concurrent Garbage Collector Using a Rely-Guarantee Methodology

Improve Google Android User Experience with Regional Garbage Collection

Programming in Manticore, a Heterogenous Parallel Functional Language

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