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Hardware-assisted garbage collection
Garbage collection assisted by hardware mechanisms From Wikipedia, the free encyclopedia
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Hardware-assisted garbage collection is the use of specialized hardware mechanisms to improve the efficiency and performance of garbage collection in computer systems. This approach integrates hardware support directly into the processor or memory system to handle tasks traditionally managed by software, such as object allocation, reference counting, or mark-and-sweep operations. It is particularly relevant in real-time systems, embedded systems, and high-performance computing environments where software-only garbage collection may introduce unacceptable pauses or overhead.
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History
Research into hardware-assisted garbage collection dates back to the 1990s. Early work focused on simulation studies to analyze the behavior of such systems.[1] By the early 2000s, proposals emerged for integrating garbage collection into hardware for real-time embedded systems.[2] Modern developments include accelerators for tracing garbage collection and concurrent collectors for functional languages.[3]
The concept of hardware-assisted garbage collection dates back several decades, with early implementations in specialized Lisp machines and research prototypes. Notable historical systems like The Garbage Collected Memory Module, a near-memory co-processor design[4] or Azul Systems' Vega processors, which included hardware support for read barriers to enable pauseless garbage collection[5]
While many early proposals did not achieve widespread adoption, renewed interest has emerged due to the slowing of Moore's law, the prevalence of garbage-collected languages, and the rise of cloud computing and hardware accelerators.
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Mechanisms
Hardware assistance can involve dedicated instructions for memory allocation, reference tracking, or collection phases. For example, some architectures provide support for bitmap-marking or concurrent marking to reduce pauses.[6] In cloud environments, hardware instructions accelerate garbage collection hotspots, improving performance by an order of magnitude.[7][8]
Generational schemes, as noted in general garbage collection literature, can be enhanced with hardware support for real-time operations. Proposals include integrated hardware collectors that run continuously in the background for embedded systems.[9]
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Applications
This technology is explored in contexts like virtual machines for cloud computing, where middleware overhead is reduced. It is also relevant for non-strict functional languages with concurrent collectors.[10] Hardware accelerators have been proposed for tracing garbage collection in modern architectures.[11]
Implementations in the wild
Performance
In controlled benchmarks, off-loading the mark phase to a hardware accelerator cut GC time by 65–80% and total application time by up to 25%.[12] Data-centre JVM studies reported consistent sub-1 ms tail-latency for 99.999 th percentile pauses on 256 GB heaps using Azul's C4 on Vega hardware.[13]
Advantages and challenges
Hardware assistance offers reliable operation, higher performance, and minimal pauses, making it suitable for real-time systems.[14] However, it may require custom hardware, limiting adoption in general-purpose CPUs.[15]
See also
References
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