Memory coherence

Abstract: Scalable shared-memory multiprocessors distribute memory among the processors and use scalable interconnection networks to provide high bandwidth and low latency communication. In addition, memory accesses are cached, buffered, and pipelined to bridge the gap between the slow shared memory and the fast processors. Unless carefully controlled, such architectural optimizations can cause memory accesses to be executed in an order different from what the programmer expects. The set of allowable memory access orderings forms the memory consistency model or event ordering model for an architecture.This paper introduces a new model of memory consistency, called release consistency, that allows for more buffering and pipelining than previously proposed models. A framework for classifying shared accesses and reasoning about event ordering is developed. The release consistency model is shown to be equivalent to the sequential consistency model for parallel programs with sufficient synchronization. Possible performance gains from the less strict constraints of the release consistency model are explored. Finally, practical implementation issues are discussed, concentrating on issues relevant to scalable architectures.

Abstract: SpiNNaker (a contraction of Spiking Neural Network Architecture) is a million-core computing engine whose flagship goal is to be able to simulate the behavior of aggregates of up to a billion neurons in real time. It consists of an array of ARM9 cores, communicating via packets carried by a custom interconnect fabric. The packets are small (40 or 72 bits), and their transmission is brokered entirely by hardware, giving the overall engine an extremely high bisection bandwidth of over 5 billion packets/s. Three of the principal axioms of parallel machine design (memory coherence, synchronicity, and determinism) have been discarded in the design without, surprisingly, compromising the ability to perform meaningful computations. A further attribute of the system is the acknowledgment, from the initial design stages, that the sheer size of the implementation will make component failures an inevitable aspect of day-to-day operation, and fault detection and recovery mechanisms have been built into the system at many levels of abstraction. This paper describes the architecture of the machine and outlines the underlying design philosophy; software and applications are to be described in detail elsewhere, and only introduced in passing here as necessary to illuminate the description.

Abstract: This paper studies the memory coherence problem in designing and implementing a shared virtual memory on looselycoupled multiprocessors. Two classes of algorithms for solving the problem are presented. A prototype shared virtual memory on an Apollo ring has been implemented based on these algorithms. Both theoretical and practical results show that the memory coherence problem can indeed be solved efficiently on a loosely-coupled multiprocessor.

Abstract: We are developing Munin, a system that allows programs written for shared memory multiprocessors to be executed efficiently on distributed memory machines. Munin attempts to overcome the architectural limitations of shared memory machines, while maintaining their advantages in terms of ease of programming. Our system is unique in its use of loosely coherent memory, based on the partial order specified by a shared memory parallel program, and in its use of type-specific memory coherence. Instead of a single memory coherence mechanism for all shared data objects, Munin employs several different mechanisms, each appropriate for a different class of shared data object. These type-specific mechanisms are part of a runtime system that accepts hints from the user or the compiler to determine the coherence mechanism to be used for each object. This paper focuses on the design and use of Munin's memory coherence mechanisms, and compares our approach to previous work in this area.