Hierarchical real-time garbage collection

2007

Memory management is a critical issue for correctness and perfor-mance in real-time embedded systems. Recent work on real-time garbage collectors has shown that it is possible to provide guar-antees on worst-case pause times and minimum mutator utiliza-tion time. This paper presents a new hierarchical real-time garbage collection algorithm for mixed-priority and mixed-criticality envi-ronments. With hierarchical garbage collection, real-time program-mers can partition the heap into a number of heaplets and for each partition choose to run a separate collector with a schedule that matches the allocation behavior and footprint of the real-time task using it. This approach lowers worst-case response times of real-time applications by 26%, while almost doubling mutator utiliza-tion – all with only minimal changes to the application code.

Proceedings - Real-Time Systems Symposium, 2009

Managed languages such as Java and C# are increasingly being considered for hard real-time applications because of their productivity and software engineering advantages. Automatic memory management, or garbage collection, is a key enabler for robust, reusable libraries, yet remains a challenge for analysis and implementation of real-time execution environments. This paper comprehensively compares the two leading approaches to hard real-time garbage collection. While there are many design decisions involved in selecting a real-time garbage collection algorithm, for timebased garbage collectors researchers and practitioners remain undecided as to whether to choose periodic scheduling or slackbased scheduling. A significant impediment to valid experimental comparison is that the commercial implementations use completely different proprietary infrastructures. Here, we present Minuteman, a framework for experimenting with realtime collection algorithms in the context of a high-performance execution environment for real-time Java. We provide the first comparison of the two approaches, both experimentally using realistic workloads, and analytically in terms of schedulability.

2005

One of the problems with Java for real-time and embedded real-time systems is the unpredictable behavior of garbage collection (GC). GC introduces unexpected load and causes undesirable delays for real-time applications. In this paper, we propose a technique that reduces and ...

1992

Hardware-assisted garbage collection combines the potential of high average-case allocation rates and memory bandwidth with fast worst-case allocation, fetch, and store times. This paper describes an architecture that allows memory fetch and store operations to execute, on the av erage, nearly as fast as traditional memory. Support for caching garbage-collected memory cells and a protocol designed to minimize communication between the CPU’s cache and memory allow the system to deliver very high performance. The architecture is real-time in that the worst-case time required for a memory fetch or store is approximately six traditional memory cycles, and the time required to allocate an object is bounded by a small constant times the size of the object. A prototype of the proposed architecture has been successfully simulated. Continuing research focuses on measuring the system’s performance under real workloads.

ACM Transactions on Computer Systems, 2011

Managed languages such as Java and C# are increasingly being considered for hard real-time applications because of their productivity and software engineering advantages. Automatic memory management, or garbage collection, is a key enabler for robust, reusable libraries, yet remains a challenge for analysis and implementation of real-time execution environments. This paper comprehensively compares leading approaches to hard real-time garbage collection. There are many design decisions involved in selecting a real-time garbage collection algorithm. For time-based garbage collectors on uni-processors one must choose whether to use periodic, slack-based or hybrid scheduling. A significant impediment to valid experimental comparison of such choices is that commercial implementations use completely different proprietary infrastructures. We present Minuteman, a framework for experimenting with real-time collection algorithms in the context of a high-performance execution environment for real-time Java. We provide the first comparison of the approaches, both experimentally using realistic workloads, and analytically in terms of schedulability. A preliminary version of this work was presented at the 30th IEEE Real-Time Systems Symposium. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies show this notice on the first page or initial screen of a display along with the full citation. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, to redistribute to lists, or to use any component of this work in other works requires prior specific permission and/or a fee. Permissions may be requested from Publications A:2 T. Kalibera et al.