ABSTRACT: In previous heap storage systems, the cost of creating objects and garbage collection is independent of the lifetime of the object. Since objects with short lifetimes account for a large portion of storage use, it is worth optimizing a garbage collector to reclaim storage for these objects more quickly. The garbage collector should spend proportionately less effort reclaiming objects with longer lifetimes. We present a garbage collection algorithm that (1) makes storage for short-lived objects cheaper than storage for long-lived objects, (2) that operates in real-time--object creation and access times are bounded, (3) increases locality of reference, for better virtual memory performance, (4) works well with multiple processors and a large address space. 1.

this paper describes a modified form of Reference Count garbage collection which removes the need for synchronisation, and gives greater locality of store accessing. This makes it attractive for parallel machines, but does not overcome the problem of reclaiming circular structures. The solution adopted for the Flagship machine is to implement the modified Reference Count scheme, and also implement a secondary Mark-Scan collector to remove circular structures (which are rarely created in this machine). Because it is not the main method of garbage collection, the efficiency of the Mark-Scan collector is not so critical, and its overheads, for example synchronisation costs, can be more readily tolerated

this paper will try to accomplish several goals (in parallel): We will argue that the actor model is an appropriate way to think about parallel computation. Since many actors may be actively sending or receiving messages at the same time, actors are inherently well suited to modelling parallel systems. We will present some specific actors which we feel should be included in the programmer's tool kit for writing parallel programs. We will show examples illustrating the use of these primitives. Futures are actors which represent the values computed by parallel processes. They can be created dynamically and disappear when they are no longer needed. Other actors may use the value of a future without concern for the feet that it was computed in parallel. Synchronization is provided by serializers, which protect actors with internal state from timing errors caused by interacting processes. We will show how these primitives have been implemented in Act 1. Act I has been implemented on a serial machine, but it simulates the kind of parallelism that would occur on a real multiprocessor machine. Discussion of the implementation will give a more concrete picture of the mechanisms involved and will also show what would be needed for an implementation on a real network of parallel processors. 12. Traditional techniques for parallelism have been inadequate

Tracing algorithms visit reachable nodes in a graph and are central to activities such as garbage collection, marshalling etc. Traditional sequential algorithms use a worklist, replacing a nodes with their unvisited children. Previous work on parallel tracing is processororiented in associating one worklist per processor: worklist insertion and removal requires no locking, and load balancing requires only occasional locking. However, since multiple queues may contain the same node, significant locking is necessary to avoid concurrent visits by competing processors. This paper presents a memory-oriented solution: memory is partitioned into segments and each segment has its own worklist containing only nodes in that segment. At a given time at most one processor owns a given worklist. By arranging separate single-readersingle-writer forwarding queues to pass nodes from processor i to processor j we can process objects in an order that gives lock-free mainline code and improved locality of reference. This refactoring is analogous to the way in which a compiler changes an iteration space to eliminate data dependencies. While it is clear that our solution can be more effective on NUMA systems, and even necessary when processor-local memory may not be addressed from other processors, slightly surprisingly, it often gives significantly better speed-up on modern multi-cores architectures too. Using caches to hide memory latency loses much of its effectiveness when there is significant cross-processor memory contention or when locking is necessary.

In previous heap storage systems, the cost of creating objects and garbage collection is independent of the lifetime of the object. Since objects with short lifetimes account for a large portion of storage use, it is worth optimizing a garbage collector to reclaim storage for these objects more quickly. The garbage collector should spend proportionately less effort reclaiming objects with longer lifetimes. We present a garbage collection algorithm that (1) makes storage for short-lived objects cheaper than storage for long-lived objects, (2) that operates in real-time--object creation and access times are bounded, (3) increases locality of reference, for better virtual memory performance, (4) works well with multiple processors and a large address space. 1.