A distributed garbage collection algorithm
Proc. of a conference on Functional programming languages and computer architecture
Distributed garbage collection using reference counting
Volume II: Parallel Languages on PARLE: Parallel Architectures and Languages Europe
An efficient garbage collection scheme for parallel computer architectures
Volume II: Parallel Languages on PARLE: Parallel Architectures and Languages Europe
Indirect reference counting: a distributed garbage collection algorithm
PARLE '91 Proceedings on Parallel architectures and languages Europe : volume I: parallel architectures and algorithms: volume I: parallel architectures and algorithms
Space efficient conservative garbage collection
PLDI '93 Proceedings of the ACM SIGPLAN 1993 conference on Programming language design and implementation
Garbage collection: algorithms for automatic dynamic memory management
Garbage collection: algorithms for automatic dynamic memory management
PPOPP '97 Proceedings of the sixth ACM SIGPLAN symposium on Principles and practice of parallel programming
A real-time garbage collector based on the lifetimes of objects
Communications of the ACM
IEEE Standard for Scalable Coherent Interface, Science: IEEE Std. 1596-1992
IEEE Standard for Scalable Coherent Interface, Science: IEEE Std. 1596-1992
Efficient parallel global garbage collection on massively parallel computers
Proceedings of the 1994 ACM/IEEE conference on Supercomputing
A Survey of Distributed Garbage Collection Techniques
IWMM '95 Proceedings of the International Workshop on Memory Management
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We compare two dynamic memory management schemes for distributed-memory parallel computers, one based on reference counting and the other based on global mark-and-sweep. We present a simple model in which one can analyze performance of the two types of GC schemes, and show experimental results. The two important observations drawn from the analysis are: 1) the performance of reference counting largely depends on shapes of data structures; specifically, it is bad when applications use deeply nested data structures such as distributed trees. 2) the cost of reference counting has a portion that is independent of the heap size while that of global mark-and-sweep does not. We confirmed these observations through experiments using three parallel applications.