Parallel computers with tens of thousands of processors are typically programmed in a data parallel style, as opposed to the control parallel style used in multiprocessing. The success of data parallel algorithms—even on problems that at first glance seem inherently serial—suggests that this style of programming has much wider applicability than was previously thought.
Assuming the existence of garbage collection makes it easier to design implementations of dynamic-sized concurrent data structures. However, this assumption limits their applicability. We present a methodology that, for a significant class of data structures, allows designers to first tackle the easier problem of designing a garbage-collection-dependent implementation, and then apply our methodology to achieve a garbage-collection-independent one. Our methodology is based on the well-known reference counting technique, and employs the double compare-and-swap operation.
Algorithms for a multiprocessing compactifying garbage collector are presented and discussed. The simple case of two processors, one performing LISP-like list operations and the other performing garbage collection continuously, is thoroughly examined. The necessary capabilities of each processor are defined, as well as interprocessor communication and interlocks. Complete procedures for garbage collection and for standard list processing primitives are presented and thoroughly explained. Particular attention is given to the problems of marking and relocating list cells while another processor may be operating on them. The primary aim throughout is to allow the list processor to run unimpeded while the other processor reclaims list storage The more complex cases involving several list processors and one or more garbage collection processors are also briefly discussed.
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